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Daniela Zaharie Date contact Departamentul de Informatic˘ a Facultatea de Matematic˘ si Informatic˘ a Universitatea de Vest din Timi¸ soara +40 729 639 576 blvd. V. Pˆ arvan, 4 [email protected] 300223, Timi¸ soara, Romania Data s ¸i locul nas ¸terii 1 septembrie 1965, Arad Domenii de interes Algoritmi evolutivi, ret ¸ele neuronale artificiale, analiza datelor, prelucrarea imaginilor, calcul paralel ¸ si distribuit, statistic˘ a computat ¸ional˘ a, modele computat ¸ionale ˆ ın biologie Educat ¸ie Facultatea de Matematic˘ si Informatic˘ a, Universitatea de Vest din Timi¸ soara, Romania Doctorat, Matematic˘ a (Teoria Probabilit˘ at ¸ilor ¸ si Statistic˘ a, 1992-1997 Titlul tezei: Model˘ari stohastice ale ret ¸elelor neuronale ¸ si aplicat ¸ii Coordonator: prof.dr. Gheorghe Constantin Licent ¸a, Matematic˘ a, specializarea Informatic˘ a, 1987 (¸ sef˘ a de promot ¸ie) Experient ¸˘ a profesional˘ a Profesor din 2009 Departamentul de Informatic˘ a, Facultatea de Matematic˘ si Informatic˘ a, Universitatea de Vest din Timi¸ soara Conferent ¸iar 1999 - 2009 Departamentul de Informatic˘ a, Facultatea de Matematic˘ si Informatic˘ a, Universitatea de Vest din Timi¸ soara 2001 - 2009 Catedra de Teoria Probabilit˘ at ¸ilor ¸ si Matematici Aplicate, Facultatea de Matematic˘ a ¸ si Informatic˘ a, Universitatea de Vest din Timi¸ soara 1999 - 2001 Lector 1992 - 1999 Catedra de Teoria Probabilit˘ at ¸ilor ¸ si Matematici Aplicate, Facultatea de Matematic˘ a ¸ si Informatic˘ a, Universitatea de Vest din Timi¸ soara Asistent 1990-1992 Catedra de Informatic˘ a, Facultatea de Matematic˘ si Informatic˘ a, Universitatea de Vest din Timi¸ soara Analist-programator 1987 - 1990 Centrul de Calcul, IAEM Timisoara Activitate didactic˘ a Cursuri nivel licent ¸˘a: Algoritmi ¸ si structuri de date (2015-prezent), Algoritmic˘ a (2003-2014), Algoritmi ¸ si programare (1993-2001), Ret ¸ele neuronale (1996-2007), Statistic˘ a (1996-1999), Calcul ¸ stiint ¸ific (1999-2000), Introducere ˆ ın informatic˘ a (1993-1996), Inteligent ¸˘ a artificial˘ a (1993-1996). Cursuri nivel master: Data mining (romˆ an˘ si englez˘ a, 2015-prezent), Algoritmi metaeuristici (romˆ an˘ si englez˘ a, 2015-prezent), Calcul neuronal ¸ si calcul evolutiv (romˆ an˘ si englez˘ a, 2007-2014), Biostatistic˘ si bioinformatic˘ a (2007-2016). Pozit ¸ii consultative s ¸i administrative prodecan la Facultatea de Matematic˘ si Informatic˘ a din 2016 membru al Senatului Universit˘ at ¸ii de Vest din Timi¸ soara 2012 - 2015 membru ˆ ın Consiliul Facult˘ at ¸ii de Matematic˘ si Informatic˘ a 2004-2015 1 of 43
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Page 1: Daniela Zaharie - doctorat.uvt.rodoctorat.uvt.ro/wp-content/uploads/2017/05/CV-Appendix_ZaharieDaniela... · Evaluare teze de doctorat: membru ^ n comisie la 46 teze din Romania (de

Daniela Zaharie

Date contact Departamentul de InformaticaFacultatea de Matematica si InformaticaUniversitatea de Vest din Timisoara +40 729 639 576blvd. V. Parvan, 4 [email protected], Timisoara, Romania

Data si loculnasterii

1 septembrie 1965, Arad

Domenii deinteres

Algoritmi evolutivi, retele neuronale artificiale, analiza datelor, prelucrarea imaginilor,calcul paralel si distribuit, statistica computationala, modele computationale ınbiologie

Educatie Facultatea de Matematica si Informatica, Universitatea de Vest din Timisoara,Romania

Doctorat, Matematica (Teoria Probabilitatilor si Statistica, 1992-1997

• Titlul tezei: Modelari stohastice ale retelelor neuronale si aplicatii• Coordonator: prof.dr. Gheorghe Constantin

Licenta, Matematica, specializarea Informatica, 1987 (sefa de promotie)

Experientaprofesionala

Profesor din 2009Departamentul de Informatica, Facultatea de Matematica si Informatica, Universitateade Vest din Timisoara

Conferentiar 1999 - 2009Departamentul de Informatica, Facultatea de Matematica si Informatica, Universitateade Vest din Timisoara 2001 - 2009

Catedra de Teoria Probabilitatilor si Matematici Aplicate, Facultatea de Matematicasi Informatica, Universitatea de Vest din Timisoara 1999 - 2001

Lector 1992 - 1999Catedra de Teoria Probabilitatilor si Matematici Aplicate, Facultatea de Matematicasi Informatica, Universitatea de Vest din Timisoara

Asistent 1990-1992Catedra de Informatica, Facultatea de Matematica si Informatica, Universitateade Vest din Timisoara

Analist-programator 1987 - 1990Centrul de Calcul, IAEM Timisoara

Activitatedidactica • Cursuri nivel licenta: Algoritmi si structuri de date (2015-prezent), Algoritmica

(2003-2014), Algoritmi si programare (1993-2001), Retele neuronale (1996-2007),Statistica (1996-1999), Calcul stiintific (1999-2000), Introducere ın informatica(1993-1996), Inteligenta artificiala (1993-1996).

• Cursuri nivel master: Data mining (romana si engleza, 2015-prezent), Algoritmimetaeuristici (romana si engleza, 2015-prezent), Calcul neuronal si calcul evolutiv(romana si engleza, 2007-2014), Biostatistica si bioinformatica (2007-2016).

Pozitiiconsultative siadministrative

prodecan la Facultatea de Matematica si Informatica din 2016

membru al Senatului Universitatii de Vest din Timisoara 2012 - 2015

membru ın Consiliul Facultatii de Matematica si Informatica 2004-2015

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responsabil al programului de studii de licenta Informatica Aplicata

din 2008

membru CNATDCU, comisia Informatica 2011 - 2012, 2015 - 2016

secretar stiintific la Departamentul de Informatica 2004 - 2012

Activitatieditoriale

Co-editor:• Analele Universitatii de Vest din Timisoara (seria Matematica si Informatica)• seria SYNASC (Proceedings of the Symposium of Symbolic and Numeric Algorithms

for Scientific Computing)Membru al comitetului editorial:• Soft Computing. A Fusion of Foundations, Methodologies and Applications• Swarm and Evolutionary Computing

Activitati deevaluare sirecenzare

Reviste: IEEE Transactions on Evolutionary Computing, IEEE Transactions onSystems, Man and Cybernetics, Applied Soft Computing, Information Sciences,Applied Mathematics and Computation, Soft Computing, Neurocomputing, MemeticComputing, Journal of Global Optimization, Computational Intelligence, EvolutionaryComputation, Computational Optimization and Applications, Patterns Analysisand Applications, Central European Journal on Computer Science etc.Conferinte: cel putin 10 conferinte internationale/an (incluzand CEC, GECCO,FOGA, ANTS, IEEE SMC, IEEE SSCI, HAIS, NICSO, NaBIC, SOCO, FedCSIS,SACI, CompStat, IADIS-Data Mining etc.)Evaluare activitate de cercetare:• Evaluare aplicatii submise la ANCS• Evaluare aplicatii submise la National Research Foundation from South Africa• Evaluare dosare pentru pozitii academice (10 la universitati din Romania; 1

pentru Budapest Univesity of Technology and Economics, Hungary; 1 pentruRobert Gordon University, Aberdeen, UK; 2 pentru Arab Open University,Kuwait)

Evaluare teze de doctorat: membru ın comisie la 46 teze din Romania (de la 6universitati), 4 teze din Franta, 5 teze din Finlanda, o teza din Olanda, o teza dinSpania si o theza din Africa de Sud.

Prezentariinvitate

• Summer School on Image Processing, SSIP 2016, Szeged, Hungary, 7-16 iulie2016

• Workshop on Stochastic Geometry and Big Data, INRIA - Sophia Antipolis, 24noiembrie, 2015

• Scientific seminar of the Computer Vision Center, University Autonoma deBarcelona, 18 aprilie, 2013

• 18th International Conference on Soft Computing, Brno, 27-29 iunie, 2012• IDEAS Research Seminar, Robert Gordon University Aberdeen, 17 mai, 2011• Doctoral Summer School ”Evolutionary Computing Optimization and Data Mining”,

Iasi, 2010-2014

Premii Premiul ”Professor Zdzislaw Pawlak Best Paper Award” acordat de Polish InformationProcessing Society in cadrul simpozionului ”Advances in Artificial Intelligence andApplications (AAIA)”, 2007

Proiecte decercetare

• RO-PN - II: NatComp - New natural computing models for complexity andcomplex problems solving, 2007-2009 (responsabil echipa de cercetare)

• RO-CEEX: MaternQual - Integrated system for complex evaluation of risk factorsand prediction in obstetrics, 2006-2008 (responsabil echipa de cercetare)

• H2020: SESAME Net - Supercomputing Expertise for Small And Medium Enterprises,H2020-EINFRA, 2015-2017

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• H2020: VI-SEEM - a unified Virtual Research Environment for South EasternEurope and Eastern Mediterranean, H2020-EINFRA, 2015-2017

• FP7: HOST - High Performance Computing Service Center, 2012-2014• FP7: HP-SEE - High-Performance Computing Infrastructure for South East

Europe’s Research Communities, 2010 - 2012• FP7: SPRERS - Strengthening the Participation of Romania at European R&D

in Software Services, 2010-2011• ESA-Pecs: GiSHEO - On Demand Grid Services for Higher Education and

Training in Earth Observation, 2009-2010• RO-PNII-ID-PCE: AMICAS - Automated Management in Cloud and Sky Computing

Environments, 2012-2016• RO-PNII-ID-PCE: REVISAL - Modelling and simulation of the dynamics of

thymocyte populations and the cellular components of medulla under normaland pathological conditions, 2012-2016

• RO-PN - II: Asistsys - Integrated system for patients with severe neuromotorproblems, 2009-2011

• RO-CEEX: GRIDMOSI - Virtual organization based on Grid technology for highperformance modelling, simulation and optimization, 2005 -2008

• RO-CEEX: MedioGrid - Parallel and distributed graphical processing on Gridinfrastructure of geographical and environmental data, 2005 -2008

• RO-CEEX: SIAPOM - Integrated system for analysis and optimal multi-disciplinarydesign, 2006-2008

• RO-CNCS, ViaSan: Bio-View software for simulating biological processes, 2004-2005

• RO-CNCS: Stochastic modelling, approximation theory and numerical approacheswith applications in turbulence and economy, 2002-2004

Publicatii • 27 lucrari ın reviste• 60 lucrari ın volume ale conferintelor• 2 capitole de carte• lista publicatiilor este ın Anexa A

Citari • cca 854 citari in SCOPUS• cca 1300 citari in Scholar Google• o lista a citarilor pentru o selectie de lucrari este in Anexa B

Limbaje deprogramare

• C, C++, Java, Pascal, Python, Lisp, Fortran, Matlab, Mathematica, R

Limbi straine • engleza (mediu), franceza (ıncepator)

Asociatiiprofesionale

Membru:• Romanian Association for Artificial Intelligence• IEEE CIS Task Force on Differential Evolution

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Anexa A. Publicatii (D. Zaharie)

Lucrari ın reviste:

1. D. Zaharie, R.D. Moleriu, F.A. Mic - Modeling the development of the post-natal mouse thymus in the absence ofbone marrow progenitors, Scientific Reports 6, Article number: 36159 (2016), doi:10.1038/srep36159, 2016.

2. J. Li, A. Agathos, D. Zaharie, J. M. Bioucas-Dias, A. Plaza, X. Li - Minimum Volume Simplex Analysis: A FastAlgorithm for Linear Hyperspectral Unmixing, IEEE Transactions on Geoscience and Remote Sensing, Volume:53,Issue: 9, Pages 5067 - 5082, 2015.

3. R.D. Moleriu, D. Zaharie, L.C. Moatar-Moleriu, A.T. Gruia, A.A. Mic, F.A. Mic - Insights into the mechanisms ofthymus involution and regeneration by modeling the glucocorticoid-induced perturbation of thymocyte populationsdynamics, Journal of Theoretical Biology, Volume 348, Pages 80-99, 2014.

4. G. Iuhasz, V. Negru, D. Zaharie - Neuroevolution based multi-agent system with ontology based template creationfor micromanagement in real-time strategy games, Information Technology and Control, Volume 43, Issue 1, pp.98-109, 2014.

5. D. Petcu, S. Panica, M. Frncu, M. Neagul, D. Zaharie, G. Macariu, D. Gorgan, T. Stefanut - Experiences inbuilding a Grid-based platform to serve Earth observation training activities , Computer Standards & Interfaces,Volume 34, Issue 6, Pages 493-508, 2012.

6. D. Petcu, S. Panica, M. Neagul, M. Frincu, D. Zaharie, R. Ciorba, A. Dinis - Earth observation data processingin distributed systems, Informatica. An International Journal of Computing and Informatics, Slovenian SocietyInformatika, vol. 34 (4), pg. 463-476, 2010.

7. F. Zamfirache, D. Zaharie, C. Craciun - Nature inspired metaheuristics for task scheduling in static and dynamiccomputing environments, Scientific Bulletin of Politehnica University of Timisoara, Transactions on AutomaticControl and Computer Science, vol 55(69), nr. 3, pp. 133-142, 2010

8. D. Zaharie - Influence of crossover on the behavior of the Differential Evolution Algorithm, Applied Soft Computing,vol 9, issue 3, pg. 1126-1138, 2009.

9. C. Chira, A. Gog, D. Zaharie, D. Dumitrescu - Complex Dynamics in a Collaborative Evolutionary Search Model,Creative Mathematics and Informatics, vol. 17, no. 3, pg. 346-356, 2008.

10. D. Petcu, D. Gorgan, F. Pop, D. Tudor, D. Zaharie - Satellite Image Processing on a Grid-Based Platform,International Journal of ”Computing”, 2008, Vol. 7, Issue 2, pg. 51-58, 2008.

11. D. Lungeanu, D. Zaharie, S. Holban, E. Bernad, M. Bari, R. Noaghiu - Exploratory Analysis of Medical CodingPractices: the Relevance of Reported Data Quality in Obstetrics-Gynaecology, in Stud Health Technol Inform.Amsterdam: IOS Press, ISBN 978-1-58603-864-9, ISSN 0926-9630, pg. : 839-844, 2008.

12. N. Bonchis, St. Balint, D. Zaharie - The Ramsey optimal growth model on finite horizon. An. Univ. Vest Timis.,Ser. Mat.-Inform. 45, No. 1, 59-76, 2007.

13. D. Zaharie - Extensions of Differential Evolution Algorithms for Multimodal Optimization, Analele Univ. Timisoaravol. XLII, ISSN 1224-970X, Timisoara, pg. 331-345, 2004.

14. C. Jichici, V. Negru, D. Pop, D. Zaharie, H. Popa - A Predictive Model for Learning Objects Quality Evaluation, Sci. Ann. Cuza Univ. 15, Iasi, pp.153-166, 2004.

15. D. Zaharie - Multi-objective Optimization with Adaptive Pareto Differential Evolution, in Memoriile SectiilorStiintifice, Seria IV, Tomul XXVI, pp. 223-239, Ed. Academiei Romane, 2003.

16. D. Zaharie - Parameter Adaptation in Differential Evolution by Controlling the Population Diversity, Analele Univ.Timisoara, vol. XXXX, issue 2, 2002.

17. D. Zaharie - On the Explorative Power of Differential Evolution Algorithms, Analele Univ. Timisoara, vol. XXXIX,pp.249-260, 2001

18. D. Zaharie - On an evolutionary algorithm for global optimization, Analele Univ.Timisoara, vol. XXXVIII, fasc.2, pg. 203-216, 2000.

19. D. Zaharie - Iterated morphological operators implemented through cellular neural networks, Analele Univ.Timisoara,vol. XXXVII (special issue on Computer Science), pg. 169-178, 1999.

20. O. Francois, D. Zaharie - Markovian Perturbations of Discrete Iterations. Lyapunov Functions, global minimizationand associative memory, Mathematical and Computer Modelling, 29, pp. 81-94, 1999.

21. D.Zaharie - Some Properties of Binary Stochastic Networks, Analele Universitatii din Bucuresti, 1999.

22. D. Zaharie - A Class of Adaptive Recurrent Neural Networks and Image Enhancement, Analele St. ale UniversitatiiAl. I. Cuza, Iasi, seria Informatica, tom VIII, pg. 177-185, 1998.

23. D. Zaharie - On Stochastically Perturbed Differential Systems, Annali dell’Universita di Ferrara, Sez. VII, Sc.Mat.,vol. XLII, pp. 77-85, 1996.

24. D. Zaharie - A Markovian Study of Recurrent Neural Networks with Stochastic Dynamics, Informatica, LithuanianAcademy of Science, Vilnius, vol. 7, nr. 2, pp. 255-266, 1996.

25. D. Zaharie - Learning Algorithms for Feedback Neural Networks with Stochastic Dynamics, Analele Universitatiidin Timisoara, vol. XXXIII, fasc. 2, seria Matematica-Informatica, pp. 287-299, 1995.

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26. D. Zaharie - On the Stochastic Modelling of Feedback Neural Networks, Analele Universitatii din Timisoara, vol.XXXI, fasc. 2, seria Matematica-Informatica, pp. 281-297, 1993.

27. D. Zaharie - On the Models of Random Automata, Analele Universitatii din Timisoara, vol. XXVIII, fasc. 2-3,seria Stiinte Matematice, pp. 211-222, 1990.

Capitole de carti

1. D. Zaharie, D. Lungeanu, F. Zamfirache - Interactive Search of Rules in Medical Data Using MultiobjectiveEvolutionary Algorithms, chapter in Genetic and Evolutionary Computation: Medical Applications, Stephen Smithand Stefano Cagnoni (eds), John Wiley & Sons, pp 133-148, 2010

2. D. Petcu, D. Zaharie, M. Neagul, S. Panica, M. Frincu, D. Gorgan, T. Stefanut and V. Bacu - Remote SensedImage Processing on Grids for Training in Earth Observation , in Yung-Sheng Chen (Ed.), Image Processing,INTECH, chapter 8, pp 115-140, 2009.

Lucrari ın volume ale conferintelor

1. M. Erascu, F. Micota, D. Zaharie - A scalable hybrid approach for applications placement in the cloud, 2015 Confer-ence on Grid, Cloud & High Performance Computing in Science (ROLCG), 28-30 October 2015, 10.1109/ROLCG.2015.7367232,2015.

2. R. Dogaru, F. Micota, D. Zaharie - Searching for Taxonomy-based Similarity Measures for Medical Data, 7thBalkan Conference in Informatics, BCI 2015, 2-4 September, DOI:10.1145/2801081.2801102, 2015.

3. R. Dogaru, F. Micota, D. Zaharie - Taxonomy-based dissimilarity measures for profile identification in medicaldata , SISY 2015, 10.1109/SISY.2015.7325369, pg. 149-154, 2015.

4. L. Moatar-Moleriu, V. Negru, D. Zaharie - Evolutionary Estimation of Parameters in Computational Models ofThymocyte Dynamics, LSSC’13, June, Sozopol, Springer LNCS 8353, pg. 264-271, 2014.

5. D. Zaharie, L. Moatar-Moleriu, V. Negru - Particularities of Evolutionary Parameter Estimation in Multi-stageCompartmental Models of Thymocyte Dynamics, GECCO’13, July 6-10, Amsterdam, pg. 303-310, 2013.

6. G. Iuhasz, V. Negru, D. Zaharie - Neuroevolution based multi-agent system for micromanagement in real-time strat-egy games, Proceedings of the Fifth Balkan Conference in Informatics, pg 32-39, ACM doi:10.1145/2371316.2371324,2012

7. D. Zaharie - Differential Evolution: from Theoretical Results to Practical Insights, in Proc. of 18th InternationalConference on Soft Computing, June 27-29, Brno, Czech Republic, pg. 126-131, 2012.

8. A.C. Zvoianu, G. Kronberger, M. Kommenda, D. Zaharie, M. Affenzeller - Improving the Parsimony of RegressionModels for an Enhanced Genetic Programming Process, LNCS 6927, pp. 264-271, 2012.

9. D. Petcu, D. Zaharie, S. Panica, A.S. Hussein, A. Sayed; H. El-Shishiny, Fuzzy clustering of large satellite imagesusing high performance computing, Proc. SPIE 8183, High-Performance Computing in Remote Sensing, 818302(12 October 2011); doi: 10.1117/12.898281, 2011

10. D. Zaharie, L. Perian, V. Negru - A View Inside the Classification with Non-Nested Generalized Exemplars, IADISEuropean Conference on Data Mining, 24-26 July, Rome, Italy, pg.19-26, 2011

11. D. Zaharie, L.Perian, V. Negru, F. Zamfirache - Evolutionary pruning of non-nested generalized exemplars, inProc.of the 6th IEEE International Symposium on Computational Intelligence and Informatics, Timisoara, 19-21mai 2011, pg 57-62, 2011.

12. F. Zamfirache, M. Frincu, D. Zaharie - Population based Metaheuristics for Tasks Scheduling in HeterogenousDistributed Systems, in I.Dimov, S. Dimova, N. Kolkovska (eds), Proc. of NMA 2010 Conference, LNCS 6046, pg.321-327, 2011.

13. D. Dumitrescu, R. Lung, R. Nagy, D. Zaharie, A. Bartha, D. Logofatu - Evolutionary Detection of New Classesof Equilibria: Application in Behavioral Games. PPSN (2)’2010. pp.432 441, 2010

14. D. Dumitrescu, R. Lung, R. Nagy, D. Zaharie, A. Bartha - Exploring evolutionary detected fuzzy equilibria: A linkbetween normative theory and real life, Proceedings of the 12th Annual Genetic and Evolutionary ComputationConference, GECCO ’10 , pp. 539-540, 2010

15. F. Zamfirache, D. Zaharie, C. Craciun - Evolutionary task scheduling in static and dynamic environments, ICCC-CONTI 2010 - IEEE International Joint Conferences on Computational Cybernetics and Technical Informatics,Proceedings , art. no. 5491336, pp. 619-624, 2010

16. I.Zaharie, D. Zaharie - On The Non-Isothermal Crystallization of Fe60Gd5Cr15B20 Amorphous Alloys, in A.Angelopoulos, T. Fildisis (eds), AIP Conference Proceedings Volume 1203, 7th International Conference of theBalkan Physical Union pp. 335-340, 2010

17. C. Craciun, M. Nicoara, D. Zaharie, Enhancing the Scalability of Metaheuristics by Cooperative Coevolution, inI. Lirkov, S. Margenov, and J. Wasniewski (Eds.): Proc. of LSSC 2009, LNCS 5910, pp. 310-317, 2010.

18. M. Neagul, S. Panica, D. Petcu, D. Zaharie, D. Gorgan - Web and grid services for training in Earth observation, Proceedings of the 5th IEEE International Workshop on Intelligent Data Acquisition and Advanced ComputingSystems: Technology and Applications, IDAACS’2009 , art. no. 5342986, pp. 241-246, 2009.

19. Gog, C. Chira, D. Dumitrescu, D. Zaharie - Analysis of Some Mating and Collaboration Strategies in EvolutionaryAlgorithms, in V. Negru et al. (eds), Proceedings of SYNASC 2008, IEEE Computer Society, pp 538-542, 2009.

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20. D. Zaharie - Statistical properties of differential evolution and related random search algorithms, in Paula Brito(ed.) Proceedings of International Conference on Computational Statistics Porto, Portugal, August 24-29, Physica-Verlag HD, ISBN978-3-7908-2083-6, pg. 473-485, 2008.

21. D. Zaharie, D. Petcu, S. Panica - A Hierarchical Approach in Distributed Evolutionary Algorithms for Multiob-jective Optimization , in I. Lirkov, S. Margenov, J. Wasniewski (eds) Proc. of LSSC 2007 - 6th InternationalConference on Large Scale Computing, LNCS 4818, ISBN-10 3-540-78825-5 Springer, pp. 505-514, 2008.

22. D. Zaharie, D. Lungeanu, F. Zamfirache - Interactive Search of Rules in Medical Data Using MultiobjectiveEvolutionary Algorithms , in Proceedings of the 2008 GECCO Conference Genetic and Evolutionary Computa-tion (workshop MedGEC–medical applications of genetic and evolutionary computation), Atlanta august 2008,ISBN:978-1-60558-131-6, pg. 2065-2072, 2008.

23. D. Lungeanu, D. Zaharie, F. Zamfirache - Influence of Missing Values Treatment on Classification Rules Evolvedfrom Medical Data. In I. Bichindaritz, P. Perner, L. G. Shapiro (Eds.): Advances in Data Mining. 8th IndustrialConference, ICDM 2008, Leipzig, Germany, July 2008, Poster and Workshop Proceedings. IbaI Publishing 2008,ISBN 978-3-940501-03-5, pg. 86-95, 2008.

24. S. Panica, D. Petcu, D. Zaharie - Evolutionary multi-objective optimization on Grid environments, in H. Burkhart(ed.), Procs. PDCN 2008, Parallel and Distributed Computing and Networks - 2008, Innsbruck, 11-14 feb., ActaPress, ISBN 978-0-88986-713-0, editor H. Burkhart, pg. 81-86, 2008.

25. R. Dogaru, D. Zaharie, D. Lungeanu, E. Bernad, M. Bari - A Framework for Mining Association Rules in Dataon Perinatal Care, Proceedings of CONTI 2008 (Conference on Technical Informatics, session on BiomedicalInformatics), Timisoara 4-6 iunie, vol 1, ISSN 1844-539X, pg. 147-152, 2008.

26. D. Zaharie, D. Lungeanu, S. Holban - Feature ranking based on weights estimated by multiobjective optimizationIn: J.Roth, J.Gutirrez, A.P. Abraham (eds.), Proceedings of IADIS First European Conference on Data Mining,5-7 iulie 2007, Lisabona, ISBN 978-972-8924-40-9, pg. 124-128, 2007.

27. D. Petcu, D. Zaharie, D. Gorgan et al.- MedioGrid: A grid-based platform for satellite image processing, in Proc.of 4th IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems, sep 06-08,2007 Dortmund, pg: 137-142, 2007.

28. D. Zaharie, S. Panica, M. Stoia-Djeska, M. Dragan, D. Petcu - Airfoil shape optimization by coupling computationalfluid dynamics with evolutionary multiobjective optimization, in M. Ganzha, M. Paprzycki, T. Pelech-Pilichowski(eds), Procs. Proceedings of the International Multiconference on Computer Science and Information Technology(IMCSIT 2007), October 15 17, 2007, Wisla, Poland, vol. 2, ISSN 1896-7094, pg. 323-325, 2007

29. D. Zaharie - A comparative analysis of crossover variants in differential evolution in M. Ganzha, M. Paprzycki, T.Pelech-Pilichowski (eds), Proc. of International Multiconference on Computer Science and Information TechnologyIMCSIT 2007, 15-17 oct., Wisla, Poland, ISSN 1896-7094, pg. 171-181, 2007

30. D. Petcu, D. Zaharie, H. Popa, M. Frincu, A. Eckstein - Grid Services Based on Heuristic Methods for Multi-Objective Optimization Problems, Procs. CSCS-16, 16th Intern. Conference on Control Systems and ComputerScience, Bucuresti, 22-25 May, 2007, EdituraPrintech, vol. 2, ISBN 978-973-718-743-7, pg. 136-141, 2007.

31. S. Panica, D. Petcu, D. Zaharie - A Grid-enabled Framework for Evolutionary Multiobjective Optimization,Procs. SACCS 2007, Iasi, 9th Internat. Symposium on Automatic Control and Computer Science, Proceedings,CD version, ISSN 1843-665-X, 2007.

32. D. Zaharie, D. Lungeanu, S. Holban, D. Navolan - Extracting prediction rules from medical data using evolutionaryalgorithms, Rev Med Chir Soc Med Nat Iasi (ISSN 0048-7848), Vol 111, Nr. 2 Supl.2: pg.197-202, 2007.

33. H. Popa, D.Pop, V. Negru, D. Zaharie - A Multi-Agent System for Knowledge Discovery from Databases, Proc.of SYNASC’07, IEEE Computer Society, ISBN 0-7695-3078-8, pg. 275-281, 2007.

34. D. Zaharie, S. Holban, D. Lungeanu, D. Navolan - A computational Intelligence Approach for Ranking Risk Factorsin Preterm Birth. In: Szakal A. (ed.). Proceedings of 4th International Symposium on Applied ComputationalIntelligence and Informatics - SACI2007, mai 2007, Timisoara, ISBN: 1-4244-1234-X, pg. 135-140, 2007.

35. D. Zaharie, F.Zamfirache, V.Negru, D.Pop, H. Popa - A Comparison of Quality Criteria for Unsupervised Cluster-ing of Documents Based on Differential Evolution, Proc. of International Conference on Knowledge Engineering:Principles and Techniques, Cluj-Napoca, 7-8 iunie, 2007, 114-121, 2007.

36. D. Zaharie, G. Ciobanu - Distributed Evolutionary Algorithms Inspired by Membranes in Continuous OptimizationProblems , in H.J. Hoogeboom, G. Paun, G. Rozenberg (eds), Pre-Proceedings of 7th Workshop on MembraneComputing, Leiden, 17-21 iulie, pp. 522-537, 2006.

37. D. Zaharie, D. Petcu - Communication Strategies in Distributed Evolutionary Algorithms for Multi-objectiveOptimization , Proc. of 7th International Conference on Technical Informatics, Timisoara, june 8-9, vol. 1, pp.145-150,2006.

38. D. Zaharie - Distributed Clustering Based on Representatives Evolved by Crowding Differential Evolution , in R.Matousek, P. Osmera (eds), Proc. of 12th International Conference on Soft Computing, Brno, may 31 - june 2,pp. 51-56, 2006.

39. D. Zaharie, F. Zamfirache - Diversity Enhancing Mechanisms for Evolutionary Optimization in Static and Dy-namic Environments , Proc. of 3rd Romanian-Hungarian Joint Symposium on Applied Computational Intelli-gence,Timisoara, may 25-26, pp. 460-471,2006.

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40. D. Zaharie, F. Zamfirache - Dealing with noise in ant-based clustering , Proc. IEEE Congress of EvolutionaryComputation 2005, Edinburgh , 2-5 sept 2005, pg. 2395-2402.

41. D. Zaharie, F. Zamfirache - Ant-based clustering of medical data , HCMC 2005, First East European Conferenceon ”Health Care Modelling and Computation” (eds: F. Gorunescu, E. El-Darzi, M. Gorunescu), pg. 332-343,2005.

42. D. Zaharie - Density-based clustering with crowding differential evolution , Proc. 7 th Symposium on Symbolicand Numeric Algorithms for Scientific Computing, 25-29 sept. 2005, pg. 72-79, 2005.

43. I.Zaharie, D. Zaharie - Evolutionary optimization of molecular clusters, Proc. of 4th Conference on Isotopic andMolecular Processes, Cluj-Napoca, sept. 22-24, 2005 STUDIA UNIVERSITATIS BABES-BOLYAI, PHYSICA, L,4a, pg. 447-450, 2005.

44. D. Zaharie - Extensions of Differential Evolution Algorithms for Multimodal Optimization, in D. Petcu et.al (eds.),Proc. of SYNASC’04, 6th International Symposium of Symbolic and Numeric Algorithms for Scientific Computing,Timisoara, september 26-30, pp. 523-534, 2004.

45. D. Zaharie - A Multipopulation Differential Evolution Algorithm for Multimodal Optimization , in R. Matousek,P. Osmera (eds.), Proc. of Mendel 2004, 10th International Conference on Soft Computing, Brno, june 2004, pp.17-22, 2004.

46. C. Grosan, D. Zaharie - Base Changing Strategies in an Adaptive Representation Evolutionary Algorithm , Proc.of SACI’04 (1st Romanian-Hungarian Joint Symposium on Applied Computational Intelligence,Timisoara, may2004, pp. 79-88, 2004.

47. D. Zaharie, D. Petcu - Adaptive Pareto Differential Evolution and its Parallelization, Proc. of 5th InternationalConference on Parallel Processing and Applied Mathematics, Czestochowa, Poland, sept. 2003 , Lecture Notes inComputer Science Volume 3019, pp 261-268, 2004.

48. I.Zaharie, D. Zaharie -On the Determination of the Crystallization Energy in non-Isothermal Processes by usingEvolutionary Algorithms, 3rd Conference on Isotopic and Molecular Processes, Cluj-Napoca, sept. 2003, StudiaUniversitatis Babes-Bolyai, Physica special issue 2, XLVIII, pg. 317-320,2003.

49. D. Zaharie, D. Petcu - Parallel implementation of multi-population differential evolution In Proc. of 2nd Workshopon Concurrent Information Processing and Computing (CIPC’03), Sinaia, Romania, eds. D. Grigoras et al., 2003.

50. D. Zaharie - Control of Population Diversity and Adaptation in Differential Evolution Algorithms, in R. Matousek,P. Osmera (eds.), Proc. of Mendel 2003, 9th International Conference on Soft Computing, Brno, Czech Republic,june 2003, pp. 41-46, 2003.

51. D. Zaharie - Critical Values for the Control Parameters of Differential Evolution Algorithms, in R. Matousek, P.Osmera (eds.), Proc. of Mendel 2002, 8th International Conference on Soft Computing, Brno,Czech Republic, june2002, pp. 62-67, 2002.

52. D. Zaharie - On the Statistical Properties of Evolutionary Algorithms for Global Optimization, Proc. of the 9thSymposium of Mathematics and its Applications, ”Politehnica” Univ. Timisoara, nov. 2001.

53. D. Zaharie - Recombination Operators for Evolutionary Algorithms, Proc. of the XXVII Summer School of”Mathematics and its Applications in Engineering and Economics”, Sozopol, Bulgaria, june 2001.

54. D. Zaharie - Image Processing through Nonlinear Dynamical Systems, Proc. of the 8th Symposium of Mathematicsand its Applications, ”Politehnica” Univ. Timisoara, nov. 1999, pg. 413-420.

55. D. Zaharie - Nonlinear adaptive filters for image processing implemented through recurrent neural networks, Intern.Conference on Technical Informatics (Conti’98), Timisoara, 29-30 October, Bull. UPT, vol. 43(57), no.4, pp.12-21,1998.

56. D. Zaharie – Markovian modelling of stochastic neural networks with binary units, PAMM Conference (PC-122),Constanta, July 26- August 3, Bull. for Applied and Computer Mathematics, 1566-LXXXVI-B, pp.61-68, 1998.

57. D. Zaharie - Asymptotic behaviour of a class of nonlinear adaptive systems applied in image processing, PAMMConference (PC-122), Arad, July 22-25, Bull. for Applied and Computer Mathematics, 1566-LXXXVI-B, pp.505-514, 1998.

58. D. Zaharie - Networks of Binary Units with Stochastic Threshold, Proc. of the 6th Symposium of Mathematicsand its Applications, Timisoara, pp. 204-210, 1995.

59. D. Zaharie, I. Zaharie - Recurrent Neural Networks with Weighted Multiple-Time Step Parallel Dynamics, Proc.of International Conference on Technical Informatics, Timisoara, pp. 159-165, 1994.

60. D. Zaharie, I. Zaharie - Stability of Feedback Neural Networks with Stochastic Synaptic Weights, Proc. of the 6thSymposium of Mathematics and its Applications, Timisoara, pp. 310-317, 1993.

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Appendix B. Citari1 (D. Zaharie)

Citari pentru D. Zaharie - D. Zaharie - Parameter Adaptation in Differential Evolution by Controlling thePopulation Diversity, Analele Univ. Timisoara (Proc. of SYNASC 2002), vol. XXXX, issue 2, 2002

1. Hu, Z., Su, Q., Yang, X., Xiong, Z.; Not guaranteeing convergence of differential evolution on a class of multimodalfunctions; 2016; Applied Soft Computing Journal; 41; 479; 487; 4; 10.1016/j.asoc.2016.01.001

2. Qiu, X., Xu, J.-X., Tan, K.C., Abbass, H.A.; Adaptive Cross-Generation Differential Evolution Operators forMultiobjective Optimization; 2016; IEEE Transactions on Evolutionary Computation; 20; 2; 7138611; 232; 244; 3;10.1109/TEVC.2015.2433672

3. Qiu, X., Xu, W., Tan, K.C., Xu, J.-X.; A new framework for self-adapting control parameters in multi-objectiveoptimization; 2015; GECCO 2015 - Proceedings of the 2015 Genetic and Evolutionary Computation Conference;743; 750; 10.1145/2739480.2754714

4. Thangavelu, S., Jeyakumar, G., Shunmuga Velyautham, C.; Population variance based empirical analysis ofthe behavior of differential evolution variants; 2015; Applied Mathematical Sciences; 9; 65-68; 3249; 3263; 1;10.12988/ams.2015.54312

5. Islam, S.M., Das, S., Ghosh, S., Roy, S., Suganthan, P.N.; An adaptive differential evolution algorithm with novelmutation and crossover strategies for global numerical optimization; 2012; IEEE Transactions on Systems, Man,and Cybernetics, Part B: Cybernetics; 42; 2; 6046144; 482; 500; 206; 10.1109/TSMCB.2011.2167966

6. Das, S., Suganthan, P.N.; Differential evolution: A survey of the state-of-the-art; 2011; IEEE Transactions onEvolutionary Computation; 15; 1; 5601760; 4; 31; 1552; 10.1109/TEVC.2010.2059031

7. Shan, D.M., Chen, Z.N., Wu, X.H.; Signal optimization for UWB radio systems; 2005; IEEE Transactions onAntennas and Propagation; 53; 7; 2178; 2184; 26; 10.1109/TAP.2005.850755

8. Jeyakumar, G., Velayutham, C.S.; Hybridizing differential evolution variants through heterogeneous mixing in adistributed framework; 2016; Studies in Computational Intelligence; 611; 107; 151; 10.1007/978-81-322-2544-7 4

9. Jeyakumar, G., Shunmuga Velayutham, C.; Hybridizing differential evolution variants through heterogeneousmixing in a distributed framework; 2015; Hybrid Soft Computing Approaches: Research and Applications; 611;107; 151; 2; 10.1007/978-81-322-2544-7 4

10. Reddy, R.R., Jeyakumar, G.; Differential evolution with added components for early detection and avoidanceof premature convergence in solving unconstrained global optimization problems; 2015; International Journal ofApplied Engineering Research; 10; 5; 13579; 13594;

11. Thangavelu, S., Jeyakumar, G., Balakrishnan, R.M., Velayutham, C.S.; Theoretical analysis of expected populationvariance evolution for a differential evolution variant; 2015; Smart Innovation, Systems and Technologies; 32; 403;416; 10.1007/978-81-322-2208-8 37

12. Basak, A., Maity, D., Das, S.; A differential invasive weed optimization algorithm for improved global numericaloptimization; 2013; Applied Mathematics and Computation; 219; 12; 6645; 6668; 18; 10.1016/j.amc.2012.12.057

13. Ghosh, S., Roy, S., Das, S., Abraham, A., Islam, S.M.; Peak-to-average power ratio reduction in OFDM systemsusing an adaptive differential evolution algorithm; 2011; 2011 IEEE Congress of Evolutionary Computation, CEC2011; 5949853; 1941; 1949; 3; 10.1109/CEC.2011.5949853

14. Basak, A., Pal, S., Abhyankar, A.R., Panigrahi, B.K.; Modified equivalent bilateral exchange of transmissionpricing using DIWO; 2010; 2010 Joint International Conference on Power Electronics, Drives and Energy Systems,PEDES 2010 and 2010 Power India; 5712557; ; 10.1109/PEDES.2010.5712557

15. Dasgupta, S., Das, S., Biswas, A., Abraham, A.; On stability and convergence of the population-dynamics indifferential evolution; 2009; AI Communications; 22; 1; 1; 20; 47; 10.3233/AIC-2009-0440

16. Das, S., Abraham, A., Konar, A.; Modeling and analysis of the population-dynamics of differential evolutionalgorithm; 2009; Studies in Computational Intelligence; 178; 111; 135; 10.1007/978-3-540-93964-1 3

17. Mukhopadhyay, A., Roy, A., Das, S., Das, S., Abraham, A.; Population-variance and explorative power of har-mony search: An analysis; 2008; 3rd International Conference on Digital Information Management, ICDIM 2008;4746793; 775; 781; 11; 10.1109/ICDIM.2008.4746793

1Sursa: SCOPUS - documente principale s aditionale. Lista include doar citari la lucrari citate de cel putin 15 ori8 of 43

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Citari pentru D. Zaharie - Critical Values for the Control Parameters of Differential Evolution Algorithms,in R. Matousek, P. Osmera (eds.), Proc. of Mendel 2002, 8th International Conference on Soft Computing,Brno,Czech Republic, june 2002, pp. 62-67, 2002.

1. Kukkonen, S., Coello Coello, C.A.; Generalized differential evolution for numerical and evolutionary optimization;2017; Studies in Computational Intelligence; 663; 253; 279; 10.1007/978-3-319-44003-3 11

2. Maciel, L., Gomide, F., Ballini, R.; A differential evolution algorithm for yield curve estimation; 2016; Mathematicsand Computers in Simulation; 129; 10; 30; 10.1016/j.matcom.2016.04.004

3. Campelo, F., Botelho, M.; Experimental investigation of recombination operators for differential evolution; 2016;GECCO 2016 - Proceedings of the 2016 Genetic and Evolutionary Computation Conference; 221; 228; 10.1145/2908812.2908852

4. Zheng, F., Zecchin, A.C., Maier, H.R., Simpson, A.R.; Comparison of the searching behavior of NSGA-II,SAMODE, and borg MOEAs applied to water distribution system design problems; 2016; Journal of Water Re-sources Planning and Management; 142; 7; 4016017; 10.1061/(ASCE)WR.1943-5452.0000650

5. Santhosh, E.C., Sangwai, J.S.; A hybrid differential evolution algorithm approach towards assisted history matchingand uncertainty quantification for reservoir models; 2016; Journal of Petroleum Science and Engineering; 142; 21;35; 10.1016/j.petrol.2016.01.038

6. Hu, Z., Su, Q., Yang, X., Xiong, Z.; Not guaranteeing convergence of differential evolution on a class of multimodalfunctions; 2016; Applied Soft Computing Journal; 41; 479; 487; 10.1016/j.asoc.2016.01.001

7. Dragoi, E.-N., Dafinescu, V.; Parameter control and hybridization techniques in differential evolution: a survey;2016; Artificial Intelligence Review; 45; 4; 447; 470; 10.1007/s10462-015-9452-8

8. Dragoi, E.N., Curteanu, S.; The use of differential evolution algorithm for solving chemical engineering problems;2016; Reviews in Chemical Engineering; 32; 2; 149; 180; 10.1515/revce-2015-0042

9. Cavalini, A.A., Lobato, F.S., Koroishi, E.H., Steffen, V.; Model updating of a rotating machine using the self-adaptive differential evolution algorithm; 2016; Inverse Problems in Science and Engineering; 24; 3; 504; 523;10.1080/17415977.2015.1047364

10. Lynn, N., Mallipeddi, R., Suganthan, P.N.; Self-adaptive ensemble differential evolution with sampled parametervalues for unit commitment; 2016; Lecture Notes in Computer Science (including subseries Lecture Notes inArtificial Intelligence and Lecture Notes in Bioinformatics); 9873 LNCS; 1; 16; 10.1007/978-3-319-48959-9 1

11. Raghu, R., Jeyakumar, G.; Mathematical modelling of migration process to measure population diversity of Dis-tributed Evolutionary Algorithms; 2016; Indian Journal of Science and Technology; 9; 31; 82410; 10.17485/ijst/2016/v9i31/82410

12. Kylheiko, K., Luukka, P., Jantunen, A., Heinrich, T.; How to win innovation races in high-tech industries? Anevolutionary optimisation model; 2016; International Journal of Technology Intelligence and Planning; 11; 1; 62;91; 10.1504/IJTIP.2016.074240

13. Moreno, L., Martin, F., Muoz, M.L., Garrido, S.; Differential Evolution Markov Chain Filter for Global Lo-calization; 2016; Journal of Intelligent and Robotic Systems: Theory and Applications; 82; 03.apr; 513; 536;10.1007/s10846-015-0245-8

14. Li, F.-W., Zhang, X.-Y., Zhu, J., Huang, Q.; Network security situation prediction based on APDE-RBF neuralnetwork; 2016; Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics; 38; 12; 2869; 2875;10.3969/j.issn.1001-506X.2016.12.28

15. Kukkonen, S., Coello, C.A.C.; Applying exponential weighting moving average control parameter adaptationtechnique with generalized differential evolution; 2016; 2016 IEEE Congress on Evolutionary Computation, CEC2016; 7744398; 4755; 4762; 10.1109/CEC.2016.7744398

16. Cihan, A., Birkholzer, J.T., Bianchi, M.; ”Optimal well placement and brine extraction for pressure managementduring CO< inf> 2< /inf> sequestration”; 2015; International Journal of Greenhouse Gas Control; 42;175; 187; 10.1016/j.ijggc.2015.07.025

17. Kushida, J.-I., Hara, A., Takahama, T.; Rank-based differential evolution with multiple mutation strategies forlarge scale global optimization; 2015; 2015 IEEE Congress on Evolutionary Computation, CEC 2015 - Proceedings;7256913; 353; 360; 10.1109/CEC.2015.7256913

18. Jin, C., Qin, A.K., Tang, K.; Local ensemble surrogate assisted crowding differential evolution; 2015; 2015 IEEECongress on Evolutionary Computation, CEC 2015 - Proceedings; 7256922; 433; 440; 10.1109/CEC.2015.7256922

19. Zheng, F., Zecchin, A.C., Simpson, A.R.; Investigating the run-time searching behavior of the differential evolutionalgorithm applied to water distribution system optimization; 2015; Environmental Modelling and Software; 69;292; 307; 10.1016/j.envsoft.2014.09.022

20. Mallipeddi, R., Lee, M.; An evolving surrogate model-based differential evolution algorithm; 2015; Applied SoftComputing Journal; 34; 770; 787; 10.1016/j.asoc.2015.06.010

21. Fan, Q., Yan, X.; Self-adaptive differential evolution algorithm with discrete mutation control parameters; 2015;Expert Systems with Applications; 42; 3; 1551; 1572; 10.1016/j.eswa.2014.09.046

22. Yang, M., Li, C., Cai, Z., Guan, J.; Differential evolution with auto-enhanced population diversity; 2015; IEEETransactions on Cybernetics; 45; 2; 6868218; 302; 315; 10.1109/TCYB.2014.2339495

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23. Gil, D., Roche, D., Borris, A., Giraldo, J.; Terminating evolutionary algorithms at their steady state; 2015;Computational Optimization and Applications; 61; 2; 9722; 489; 515; 10.1007/s10589-014-9722-4

24. Thangavelu, S., Jeyakumar, G., Balakrishnan, R.M., Velayutham, C.S.; Theoretical analysis of expected populationvariance evolution for a differential evolution variant; 2015; Smart Innovation, Systems and Technologies; 32; 403;416; 10.1007/978-81-322-2208-8 37

25. Locatelli, M., Vasile, M.; (Non) convergence results for the differential evolution method; 2015; OptimizationLetters; 9; 3; 413; 425; 10.1007/s11590-014-0816-9

26. Raghu, R., Jeyakumar, G.; Empirical analysis on the population diversity of the sub-population in distributeddifferential evolution algorithm; 2015; International Journal of Control Theory and Applications; 8; 5; 1809; 1816;

27. Thangavelu, S., Jeyakumar, G., Shunmuga Velyautham, C.; Population variance based empirical analysis of the be-havior of differential evolution variants; 2015; Applied Mathematical Sciences; 9; 65-68; 3249; 3263; 10.12988/ams.2015.54312

28. Drozdik, M., Aguirre, H., Akimoto, Y., Tanaka, K.; Comparison of parameter control mechanisms in multi-objective differential evolution; 2015; Lecture Notes in Computer Science (including subseries Lecture Notes inArtificial Intelligence and Lecture Notes in Bioinformatics); 8994; 89; 103; 10.1007/978-3-319-19084-6 8

29. Miruna Joe Amali, S., Baskar, S.; Surrogate assisted-hybrid differential evolution algorithm using diversity control;2015; Expert Systems; 32; 4; 531; 545; 10.1111/exsy.12105

30. Al-Dabbagh, R.D., Botzheim, J., Al-Dabbagh, M.D.; Comparative analysis of a modified differential evolutionalgorithm based on bacterial mutation scheme; 2015; IEEE SSCI 2014 - 2014 IEEE Symposium Series on Com-putational Intelligence - SDE 2014: 2014 IEEE Symposium on Differential Evolution, Proceedings; 7031532;10.1109/SDE.2014.7031532

31. Martn, F., Monje, C.A., Moreno, L., Balaguer, C.; DE-based tuning of PI?D? controllers; 2015; ISA Transactions;59; 398; 407; 10.1016/j.isatra.2015.10.002

32. Zheng, F.; Comparing the real-time searching behavior of four differential-evolution variants applied to water-distribution-network design optimization; 2015; Journal of Water Resources Planning and Management; 141; 10;4015016; 10.1061/(ASCE)WR.1943-5452.0000534

33. Al-Nemer, A.A., Issaka, M.B., Awotunde, A.A., Al-Hashem, H.S.; Global optimization strategies for well testsin dual porosity reservoirs; 2015; SPE Middle East Oil and Gas Show and Conference, MEOS, Proceedings;2015-January; 716; 739;

34. P. Silva, R.C., Lopes, R.A., R. Freitas, A.R., Guimar?es, F.G.; A study on self-configuration in the differentialevolution algorithm; 2015; IEEE SSCI 2014 - 2014 IEEE Symposium Series on Computational Intelligence - SDE2014: 2014 IEEE Symposium on Differential Evolution, Proceedings; 7031531; 10.1109/SDE.2014.7031531

35. Al-Dabbagh, R.D., Mekhilef, S., Baba, M.S.; Parameters’ fine tuning of differential evolution algorithm; 2015;Computer Systems Science and Engineering; 30; 2; 125; 139;

36. Maier, H.R., Kapelan, Z., Kasprzyk, J., Kollat, J., Matott, L.S., Cunha, M.C., Dandy, G.C., Gibbs, M.S., Keedwell,E., Marchi, A., Ostfeld, A., Savic, D., Solomatine, D.P., Vrugt, J.A., Zecchin, A.C., Minsker, B.S., Barbour, E.J.,Kuczera, G., Pasha, F., Castelletti, A., Giuliani, M., Reed, P.M.; Evolutionary algorithms and other metaheuristicsin water resources: Current status, research challenges and future directions; 2014; Environmental Modelling andSoftware; 62; 271; 299; 10.1016/j.envsoft.2014.09.013

37. Coelho, L.D.S., Ayala, H.V.H., Mariani, V.C.; A self-adaptive chaotic differential evolution algorithm using gammadistribution for unconstrained global optimization; 2014; Applied Mathematics and Computation; 234; 452; 459;10.1016/j.amc.2014.01.159

38. Raghunathan, T., Ghose, D.; Differential evolution based 3-D guidance law for a realistic interceptor model; 2014;Applied Soft Computing Journal; 16; 20; 33; 10.1016/j.asoc.2013.11.017

39. Drozdik, M., Tanaka, K., Aguirre, H., Verel, S., Liefooghe, A., Derbel, A.B.; An analysis of differential evolutionparameters on rotated bi-objective optimization functions; 2014; Lecture Notes in Computer Science (includingsubseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 8886; 143; 154;

40. Qin, A.K., Tang, K., Pan, H., Xia, S.; Self-adaptive differential evolution with local search chains for real-parametersingle-objective optimization; 2014; Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC2014; 6900636; 467; 474; 10.1109/CEC.2014.6900636

41. Dai, Q.-W., Jiang, F.-B., Dong, L.; Nonlinear inversion for electrical resistivity tomography based on chaoticDE-BP algorithm; 2014; Journal of Central South University; 21; 5; 2018; 2025; 10.1007/s11771-014-2151-9

42. Segura, C., Coello, C.A.C., Segredo, E., Len, C.; An analysis of the automatic adaptation of the crossover ratein differential evolution; 2014; Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC 2014;6900585; 459; 466; 10.1109/CEC.2014.6900585

43. Aalto, J., Lampinen, J.; A mutation and crossover adaptation mechanism for differential evolution algorithm;2014; Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC 2014; 6900532; 451; 458;10.1109/CEC.2014.6900532

44. Kazimipour, B., Li, X., Qin, A.K.; Effects of population initialization on differential evolution for large scaleoptimization; 2014; Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC 2014; 6900624;2404; 2411; 10.1109/CEC.2014.6900624

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45. Subramanian, S.V., Delaurentis, D.A.; A hybrid differential evolution self-organizing-map algorithm for optimiza-tion of expensive black-box functions; 2014; AIAA AVIATION 2014 -15th AIAA/ISSMO Multidisciplinary Analysisand Optimization Conference; ;

46. Locatelli, M., Maischberger, M., Schoen, F.; Differential evolution methods based on local searches; 2014; Com-puters and Operations Research; 43; 1; 169; 180; 10.1016/j.cor.2013.09.010

47. Das, S., Mandal, A., Mukherjee, R.; An adaptive differential evolution algorithm for global optimization in dynamicenvironments; 2014; IEEE Transactions on Cybernetics; 44; 6; 6587535; 966; 978; 10.1109/TCYB.2013.2278188

48. Roche, D., Gil, D., Giraldo, J.; Detecting loss of diversity for an efficient termination of EAs; 2014; Proceedings- 15th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, SYNASC 2013;6821196; 561; 566; 10.1109/SYNASC.2013.79

49. Chiu, Y.-C.; Application of differential evolutionary optimization methodology for parameter structure identifica-tion in groundwater modeling; 2014; Hydrogeology Journal; 22; 8; 1731; 1748; 10.1007/s10040-014-1172-7

50. Yang, K., Mu, L., Yang, D., Zou, F., Wang, L., Jiang, Q.; Multiobjective memetic estimation of distributionalgorithm based on an incremental tournament local searcher; 2014; Scientific World Journal; 2014; 836272;10.1155/2014/836272

51. Peng, H., Wu, Z.-J., Zhou, X.-Y., Deng, C.-S.; Dynamic differential evolution algorithm based on elite local learn-ing; 2014; Tien Tzu Hsueh Pao/Acta Electronica Sinica; 42; 8; 1522; 1530; 10.3969/j.issn.0372-2112.2014.08.010

52. Kushida, J.-I., Hara, A., Takahama, T., Kido, A.; Island-based differential evolution with varying subpopulationsize; 2013; 2013 IEEE 6th International Workshop on Computational Intelligence and Applications, IWCIA 2013- Proceedings; 6624798; 119; 124; 10.1109/IWCIA.2013.6624798

53. Juszczuk, P., Boryczka, U.; The differential evolution with the entropy based population size adjustment for thenash equilibria problem; 2013; Lecture Notes in Computer Science (including subseries Lecture Notes in ArtificialIntelligence and Lecture Notes in Bioinformatics); 8083 LNAI; 691; 700; 10.1007/978-3-642-40495-5 69

54. Zhou, Y., Li, X., Gao, L.; A novel two-layer hierarchical differential evolution algorithm for global optimization;2013; Proceedings - 2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013; 6722250;2916; 2921; 10.1109/SMC.2013.497

55. Sarkar, S., Patra, G.R., Das, S., Chaudhuri, S.S.; Fuzzy clustering of image pixels with a fitness-based adaptivedifferential evolution; 2013; Lecture Notes in Computer Science (including subseries Lecture Notes in ArtificialIntelligence and Lecture Notes in Bioinformatics); 8297 LNCS; PART 1; 179; 188; 10.1007/978-3-319-03753-0 17

56. Escalona-Vargas, D.I., Gutirrez, D., Lopez-Arevalo, I.; Performance of different metaheuristics in EEG source local-ization compared to the Cramr-Rao bound; 2013; Neurocomputing; 120; 597; 609; 10.1016/j.neucom.2013.04.010

57. Hu, Z., Xiong, S., Su, Q., Zhang, X.; Sufficient conditions for global convergence of differential evolution algorithm;2013; Journal of Applied Mathematics; 2013; 193196; 10.1155/2013/193196

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68. Wang, Z., Zhang, W.; Spectrum sharing with limited channel feedback; 2013; IEEE Transactions on WirelessCommunications; 12; 5; 6493533; 2524; 2532; 10.1109/TWC.2013.032513.121510

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77. Falco, I.D.; Differential Evolution for automatic rule extraction from medical databases; 2013; Applied Soft Com-puting Journal; 13; 2; 1265; 1283; 10.1016/j.asoc.2012.10.022

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93. Yang, Z., Li, X., Bowers, C.P., Schnier, T., Tang, K., Yao, X.; An efficient evolutionary approach to parameteridentification in a building thermal model; 2012; IEEE Transactions on Systems, Man and Cybernetics Part C:Applications and Reviews; 42; 6; 6105579; 957; 969; 10.1109/TSMCC.2011.2174983

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118. Yamaguchi, S.; An automatic control parameter tuning method for differential evolution; 2011; Electrical Engi-neering in Japan (English translation of Denki Gakkai Ronbunshi); 174; 3; 25; 33; 10.1002/eej.21047

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142. Chakraborty, P., Roy, G.G., Das, S., Jain, D., Abraham, A.; An improved harmony search algorithm with differ-ential mutation operator; 2009; Fundamenta Informaticae; 95; 4; 401; 426; 10.3233/FI-2009-157

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96. Ali, M., Pant, M., Nagar, A.; Two new approach incorporating centroid based mutation operators for differentialevolution; 2011; World Journal of Modelling and Simulation; 7; 1; 16; 28;

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Citari pentru D. Zaharie - Extensions of Differential Evolution Algorithms for Multimodal Optimization, in D.Petcu et.al (eds.), Proc. of SYNASC’04, 6th International Symposium of Symbolic and Numeric Algorithms forScientific Computing, Timisoara, september 26-30, pp. 523-534, 2004.

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23. Mashwani, W.K.; Enhanced versions of differential evolution: State-of-the-art survey; 2014; International Journalof Computing Science and Mathematics; 5; 2; 107; 126; 10.1504/IJCSM.2014.064064

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47. Tvrdk, J., Polkov, R.; Enhanced competitive differential evolution for constrained optimization; 2010; Proceedingsof the International Multiconference on Computer Science and Information Technology, IMCSIT 2010; 5; 5680058;909; 915;

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6. Piotrowski, A.P.; Review of Differential Evolution population size; 2017; Swarm and Evolutionary Computation;32; 1; 24; 10.1016/j.swevo.2016.05.003

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8. Dragoi, E.-N., Curteanu, S., Cascaval, D., Galaction, A.-I.; Artificial Neural Network Modeling of Mixing Effi-ciency in a Split-Cylinder Gas-Lift Bioreactor for Yarrowia lipolytica Suspensions; 2016; Chemical EngineeringCommunications; 203; 12; 1600; 1608; 10.1080/00986445.2016.1206892

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