Abstract
The paper describes a new preference method and its use in multiobjective optimization. These preferences are developed with a goal to reduce the cognitive overload associated with the relative importance of a certain criterion within a multiobjective design environment involving large numbers of objectives. Their successful integration with several genetic-algorithm-based design search and optimization techniques (weighted sums, weighted Pareto, weighted co-evolutionary methods, and weighted scenarios) are described and theoretical results relating to complexity and sensitivity of the algorithm are presented and discussed. Its usefulness was demonstrated in a real-world project of conceptual airframe design.
Keywords
Multi-objective optimizationMathematical optimizationEvolutionary algorithmComputer sciencePareto principleGenetic algorithmPreferenceEvolutionary computationAirframeOptimization problemArtificial intelligenceMathematicsEngineering
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Publication Info
- Year
- 2002
- Type
- article
- Volume
- 6
- Issue
- 1
- Pages
- 42-57
- Citations
- 233
- Access
- Closed
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Cite This
Dragoljub Cvetković,
Ian C. Parmee
(2002).
Preferences and their application in evolutionary multiobjective optimization.
IEEE Transactions on Evolutionary Computation
, 6
(1)
, 42-57.
https://doi.org/10.1109/4235.985691
Identifiers
- DOI
- 10.1109/4235.985691