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Multi-Objective Optimization

  • Kalyanmoy Deb

Abstract

Many real-world search and optimization problems are naturally posed as non-linear programming problems having multiple objectives. Due to the lack of suitable solution techniques, such problems were artificially converted into a single-objective problem and solved. The difficulty arose because such problems give rise to a set of trade-off optimal solutions (known as Pareto-optimal solutions), instead of a single optimum solution. It then becomes important to find not just one Pareto-optimal solution, but as many of them as possible. This is because any two such solutions constitutes a trade-off among the objectives and users would be in a better position to make a choice when many such trade-off solutions are unveiled.

Keywords

Objective Vector Pareto Archive Evolution Strategy Archive Member Domination Count Ideal Objective Vector 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media, LLC 2005

Authors and Affiliations

  • Kalyanmoy Deb
    • 1
  1. 1.Kanpur Genetic Algorithms Laboratory (KanGAL), Department of Mechanical EngineeringIndian Institute of TechnologyKanpurIndia

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