Multi-objective Optimization using Evolutionary Algorithms

This is a progress report describing my research during the last one and a half year, performed during part A of my Ph.D. study. The research field is multi-objective optimization using evolutionary algorithms, and the reseach has taken place in a collaboration with Aarhus Univerity, Grundfos and the Alexandra Institute. My research so far has been focused on two main areas, i) multi-objective evolutionary algorithms (MOEAs) with different variation operators, and ii) decreasing the cardinality of the resulting population of MOEAs. The outcome of the former is a comparative analysis of MOEA versions using different variation operators on a suite of test problems. The latter area has given rise to both a new branch of multiobjective optimization (MOO) called MODCO (Multi-Objective Distinct Candidates Optimization) and a new MOEA which makes it possible for the user to directly set the cardinality of the resulting set of solutions. To motivate and cover my previous and future work, the progress report is divided into three main parts:

[1]  Rainer Storn,et al.  Differential Evolution-A simple evolution strategy for fast optimization , 1997 .

[2]  Marco Laumanns,et al.  SPEA2: Improving the strength pareto evolutionary algorithm , 2001 .

[3]  Kalyanmoy Deb,et al.  Multi-objective optimization using evolutionary algorithms , 2001, Wiley-Interscience series in systems and optimization.

[4]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..

[5]  Marco Laumanns,et al.  Scalable multi-objective optimization test problems , 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).

[6]  Kalyanmoy Deb,et al.  Finding Knees in Multi-objective Optimization , 2004, PPSN.

[7]  Jouni Lampinen,et al.  GDE3: the third evolution step of generalized differential evolution , 2005, 2005 IEEE Congress on Evolutionary Computation.

[8]  Lothar Thiele,et al.  A Tutorial on the Performance Assessment of Stochastic Multiobjective Optimizers , 2006 .

[9]  Bogdan Filipic,et al.  DEMO: Differential Evolution for Multiobjective Optimization , 2005, EMO.

[10]  Tea Tusar,et al.  Differential Evolution versus Genetic Algorithms in Multiobjective Optimization , 2007, EMO.

[11]  Joshua D. Knowles,et al.  An Evolutionary Approach to Multiobjective Clustering , 2007, IEEE Transactions on Evolutionary Computation.

[12]  Kalyanmoy Deb,et al.  A Local Search Based Evolutionary Multi-objective Optimization Approach for Fast and Accurate Convergence , 2008, PPSN.

[13]  Peter Dueholm Justesen,et al.  Multiobjective Distinct Candidates Optimization (MODCO): A Cluster-Forming Differential Evolution Algorithm , 2009, EMO.