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Multi-Objective Optimization

In: Search Methodologies

Author

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  • Kalyanmoy Deb

    (Indian Institute of Technology, Kanpur Genetic Algorithms Laboratory (KanGAL), Department of Mechanical Engineering)

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.

Suggested Citation

  • Kalyanmoy Deb, 2005. "Multi-Objective Optimization," Springer Books, in: Edmund K. Burke & Graham Kendall (ed.), Search Methodologies, chapter 0, pages 273-316, Springer.
    • Handle: RePEc:spr:sprchp:978-0-387-28356-2_10
    DOI: 10.1007/0-387-28356-0_10
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