Identifying preferred solutions in multiobjective combinatorial optimization problems

被引：0

作者：

Lokman, Banu ^{[1
]}

Koksalan, Murat ^{[2
]}

机构：

[1] Univ Portsmouth, Portsmouth Business Sch, Portsmouth, Hants, England

[2] Middle East Tech Univ, Dept Ind Engn, Fac Engn, Ankara, Turkey

来源：

TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES | 2019年 / 27卷 / 03期

关键词：

Evolutionary algorithm; preferred region; nondominated frontier; multiobjective combinatorial optimization; EVOLUTIONARY ALGORITHM; GENETIC ALGORITHM;

D O I：

10.3906/elk-1807-18

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：1970 / 1981

页数：12

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