Identifying preferred solutions in multiobjective combinatorial optimization problems

Date

2019-01-01

Author

Lokman, Banu

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We develop an evolutionary algorithm for multiobjective combinatorial optimization problems. The algorithm aims at converging the preferred solutions of a decision-maker. We test the performance of the algorithm on the multiobjective knapsack and multiobjective spanning tree problems. We generate the true nondominated solutions using an exact algorithm and compare the results with those of the evolutionary algorithm. We observe that the evolutionary algorithm works well in approximating the solutions in the preferred regions.

Subject Keywords

Evolutionary Algorithm, Preferred Region, Nondominated Frontier, Multiobjective Combinatorial Optimization

URI

https://hdl.handle.net/11511/32559

Journal

TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES

DOI

https://doi.org/10.3906/elk-1807-18

Collections

Graduate School of Natural and Applied Sciences, Article

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Citation Formats

B. Lokman, “Identifying preferred solutions in multiobjective combinatorial optimization problems,” TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES, pp. 1970–1981, 2019, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/32559.