An interactive genetic algorithm applied to the multiobjective knapsack problem

Date

2001-01-01

Author

Pamuk, S
Köksalan, Mustafa Murat

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Multiobjective combinatorial problems are commonly encountered in practice and would benefit from the development of metaheuristics where the search effort is interactively guided towards the solutions favored by the decision maker. The present study introduces such an Interactive Genetic Algorithm designed for a general multiobjective combinatorial framework and discusses its behavior in simulations on the Multiobjective Knapsack Problem. The evolution strategies being employed reflect the multiobjective nature of the problem. The fitness of individuals in the population is estimated on the basis of preference information elicited from the decision maker, and continuously updated as the algorithm progresses. The presented results indicate that the algorithm performs well when simulated against decision makers with different underlying utility functions.

Subject Keywords

Multiobjective combinatorial optimization, Genetic algorithm, Knapsack

URI

https://hdl.handle.net/11511/54560

Journal

MULTIPLE CRITERIA DECISION MAKING IN THE NEW MILLENNIUM

Collections

Department of Industrial Engineering, Article

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Citation Formats

S. Pamuk and M. M. Köksalan, “An interactive genetic algorithm applied to the multiobjective knapsack problem,” MULTIPLE CRITERIA DECISION MAKING IN THE NEW MILLENNIUM, pp. 265–272, 2001, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/54560.