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Fieldsend, “Dominance measures formulti-<strong>objective</strong> simulated annealing,” in Proceedings of the 2004 IEEECongress on Evolutionary Computation (CEC’04), 2004, pp. 23–30.[18] B. Suman and P. Kumar, “A survey of simulated annealing as a toolfor single and multi<strong>objective</strong> optimization,” Journal of the OperationalResearch Society, vol. 57, no. 10, pp. 1143–1160, 2006.[19] K. Deb, A. Pratap, S. Agarwal, and T. Meyarivan, “A fast and elitistmulti<strong>objective</strong> genetic algorithm: NSGA-II,” IEEE Transactions onEvolutionary Computation, vol. 6, no. 2, 2002.[20] J. D. Knowles and D. W. Corne, “Approxmating the nondominated frontusing the pareto archived evolution strategy,” Evolutionary Computation,vol. 8, no. 2, pp. 149–172, 2000.[21] S. Bandyopadhyay, S. K. Pal, and B. Aruna, “<strong>Multi</strong>-<strong>objective</strong> GAs,quantitative indices and pattern classification,” IEEE Transactions onSystems, Man and Cybernetics-B, vol. 34, no. 5, pp. 2088–2099, 2004.[22] H. Ishibuchi and T. Murata, “A multi-<strong>objective</strong> genetic local search algorithmand its application to flowshop scheduling,” IEEE Transactionson Systems, Man and Cybernetics-Part C: Applications and Reviews,vol. 28, no. 3, pp. 392–403, August, 1998.[23] J. R. Schott, “Fault tolerant design using single and multi-criteria geneticalgorithms,” Ph.D. dissertation, 1995.[24] H. Ishibuchi, T. Yoshida, and T. Murata, “Balance between geneticserach and local serach in memetic algorithms for multi<strong>objective</strong>permutation flowshop scheduling,” IEEE-Transactions on EvolutionaryComputation, vol. 6, no. 6, pp. 721–741, 1984.[25] E. Zitzler and L. Thiele, “An evolutionary algorithm for multi<strong>objective</strong>optimization: The strength pareto approach,” Gloriastrasse 35, CH-8092Zurich, Switzerland, Tech. Rep. 43, 1998.[26] E. J. Hughes, “Evolutionary many-<strong>objective</strong> optimization: Many onceor one many?” in Proceedings of 2005 Congress on EvolutionaryComputation, Edinburgh, Scotland, UK, September 2-5, 2005, pp. 222–227.[27] H. Ishibuchi, T. Doi, and Y. Nojima, “Incorporation of scalarizing fitnessfunctions into evolutionary multi<strong>objective</strong> optimization algorithms,” InParallel Problem Solving from Nature IX ( PPSN-IX), vol. 4193, pp.493–502, September 2006.[28] J. Fieldsend, R. Everson, and S. Singh, “Using unconstrained elitearchives for multi-<strong>objective</strong> optimisation,” IEEE Transactions on EvolutionaryComputation, vol. 7, no. 3, pp. 305–323, 2003.[29] A. K. Jain and R. C. Dubes, <strong>Algorithm</strong>s for Clustering Data. EnglewoodCliffs, NJ: Prentice-Hall, 1988.[30] G. Toussaint, “Pattern recognition and geometrical complexity,” inProc. Fifth International Conf. on Pattern Recognition, Miami Beach,December 1980, pp. 1324–1347.[31] K. Deb, “<strong>Multi</strong>-<strong>objective</strong> genetic algorithms: problem difficulties andconstruction of test problems,” Evolutionary Computation, vol. 7, no. 3,pp. 205–230, 1999.[32] http://www.dcs.ex.ac.uk/people/kismith/mosa/results/tec/.[33] E. Zitzler, K. Deb, and L. Thiele, “Comparison of multi<strong>objective</strong>evolutionary algorithms: Empirical results,” Evolutionary Computation,vol. 8, no. 2, pp. 173–195, 2000.[34] S. Saha, S.Sur-Kolay, S. Bandyopadhyay, and P. Dasgupta, “<strong>Multi</strong><strong>objective</strong>genetic algorithm for k-way equipartitioning of a point setwith application to CAD-VLSI,” in Proceedings of 9th InternationalConference on Information Technology (ICIT 2006). IEEE ComputerSociety, December, 2006, pp. 281–284.[35] S. Bandyopadhyay, U. Maulik, and A. Mukhopadhyay, “<strong>Multi</strong><strong>objective</strong>genetic clustering for pixel classification in remote sensing imagery,”IEEE Transactions Geoscience and Remote Sensing (In Press), 2006.[36] A. Mukhopadhyay, U. Maulik, and S. Bandyopadhyay, “Efficient twostagefuzzy clustering of microarray gene expression data,” in Proceedingsof 9th International Conference on Information Technology (ICIT2006). IEEE Computer Society, December, 2006, pp. 11–14.Sanghamitra Bandyopadhyay (SM’05) did herBachelors in Physics and Computer Science in 1988and 1991 respectively. Subsequently, she did herMasters in Computer Science from Indian Instituteof Technology (IIT), Kharagpur in 1993 and Ph.D inComputer Science from Indian Statistical Institute,Calcutta in 1998. Currently she is an AssociateProfessor, Indian Statistical Institute, Kolkata, India.Dr. Bandyopadhyay is the first recipient of DrShanker Dayal Sharma Gold Medal and InstituteSilver Medal for being adjudged the best all roundpost graduate performer in IIT, Kharagpur in 1994. She has worked in LosAlamos National Laboratory, Los Alamos, USA, in 1997, University of NewSouth Wales, Sydney, Australia, in 1999, Department of Computer Scienceand Engineering, University of Texas at Arlington, USA, in 2001, Universityof Maryland, Baltimore County, USA, in 2004, Fraunhofer Institute AiS, St.Augustin, Germany, in 2005 and Tsinghua University, China, in 2006. Shehas delivered lectures at Imperial College, London, UK, Monash University,Australia, University of Aizu, Japan, University of Nice, France, UniversityKebangsaan Malaysia, Kuala Lumpur, Malaysia, and also made academicvisits to many more Institutes/Universities around the world. She is a co-authorof 3 books and more than 100 research publications. Dr. Bandyopadhyayreceived the Indian National Science Academy (INSA) and the Indian ScienceCongress Association (ISCA) Young Scientist Awards in 2000, as well as theIndian National Academy of Engineering (INAE) Young Engineers’ Awardin 2002. She has guest edited several journal special issues including IEEETransactions on Systems, Man and Cybernetics, Part - B. Dr. Bandyopadhyayhas been the Program Chair, Tutorial Chair, Associate Track Chair and aMember of the program committee of many international conferences. Herresearch interests include Pattern Recognition, Data Mining, Evolutionary andSoft Computation, Bioinformatics and Parallel and Distributed Systems.Sriparna Saha received her B.Tech degree in ComputerScience and Engineering from Kalyani Govt.Engineering College, University of Kalyani, Indiain 2003. She did her M.Tech in Computer Sciencefrom Indian Statistical Institute, Kolkata in 2005.She is the recipient of Lt Rashi Roy Memorial GoldMedal from Indian Statistical Institute for outstandingperformance in M.Tech (Computer Science). Atpresent she is pursuing her Ph.D. from Indian StatisticalInstitute, Kolkata, India. She is a co-authorof about 10 papers. Her research interests include<strong>Multi</strong><strong>objective</strong> <strong>Optimization</strong>, Pattern Recognition, Evolutionary <strong>Algorithm</strong>s,and Data Mining.Ujjwal Maulik (SM’05) is currently a Professor inthe Department of Computer Science and Engineering,Jadavpur University, Kolkata, India. Dr. Maulikdid his Bachelors in Physics and Computer Sciencein 1986 and 1989 respectively. Subsequently, he didhis Masters and Ph.D in Computer Science in 1991and 1997 respectively. He was the Head of the schoolof Computer Science and Technology Department ofKalyani Govt. Engg. College, Kalyani, India during1996-1999. Dr. Maulik has worked in Center forAdaptive Systems Application, Los Alamos, NewMexico, USA in 1997, University of New South Wales, Sydney, Australiain 1999, University of Texas at Arlington, USA in 2001, Univ. of MarylandBaltimore County, USA in 2004 and Fraunhofer Institute AiS, St. Augustin,Germany in 2005. He has also visited many Institutes/Universities around theworld for invited lectures and collaborative research. He is a senior memberof IEEE and a Fellow of IETE, India. Dr. Maulik is a co-author of 2 booksand about 100 research publications. He is the recipient of the Govt. of IndiaBOYSCAST fellowship in 2001. Dr. Maulik has been the Program Chair,Tutorial Chair and a Member of the program committee of many internationalconferences and workshops. His research interests include Artificial Intelligenceand Combinatorial <strong>Optimization</strong>, Soft Computing, Pattern Recognition,Data Mining, Bioinformatics, VLSI and Distributed System.
Kalyanmoy Deb is currently a Professor of MechanicalEngineering at Indian Institute of TechnologyKanpur, India and is the director of Kanpur Genetic<strong>Algorithm</strong>s Laboratory (KanGAL). He is therecipient of the prestigious Shanti Swarup BhatnagarPrize in Engineering Sciences for the year 2005. Hehas also received the ‘Thomson Citation LaureateAward’ from Thompson Scientific for having highestnumber of citations in Computer Science during thepast ten years in India. He is a fellow of IndianNational Academy of Engineering (INAE), IndianNational Academy of Sciences, and International Society of Genetic andEvolutionary Computation (ISGEC). He has received Fredrick Wilhelm BesselResearch award from Alexander von Humboldt Foundation in 2003. His mainresearch interests are in the area of computational optimization, modelingand design, and evolutionary algorithms. He has written two text books onoptimization and more than 190 international journal and conference researchpapers. He has pioneered and a leader in the field of evolutionary multi<strong>objective</strong>optimization. He is associate editor of two major international journalsand an editorial board members of five major journals. More informationabout his research can be found from http://www.iitk.ac.in/kangal/deb.htm.15
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