Multiobjective optimization using evolutionary algorithms — A comparative case study

  • Eckart Zitzler
  • Lothar Thiele
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1498)


Since 1985 various evolutionary approaches to multiobjective optimization have been developed, capable of searching for multiple solutions concurrently in a single run. But the few comparative studies of different methods available to date are mostly qualitative and restricted to two approaches. In this paper an extensive, quantitative comparison is presented, applying four multiobjective evolutionary algorithms to an extended 0/1 knapsack problem.


Genetic Algorithm Test Problem Pareto Front Multiobjective Optimization Knapsack Problem 
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Copyright information

© Springer-Verlag Berlin Heidelberg 1998

Authors and Affiliations

  • Eckart Zitzler
    • 1
  • Lothar Thiele
    • 1
  1. 1.Computer Engineering and Communication Networks Laboratory (TIK)Swiss Federal Institute of Technology ZurichZurichSwitzerland

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