Multi-Objective Optimization

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

Chapter Chapter 10 in Search Methodologies, 2005, pp 273-316 from Springer

Abstract: 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 (search for similar items in EconPapers)
Date: 2005
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DOI: 10.1007/0-387-28356-0_10

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