Heuristic approaches for biobjective mixed 0-1 integer linear programming problems

被引:19
|
作者
Soylu, Banu [1 ]
机构
[1] Erciyes Univ, Dept Ind Engn, TR-38039 Kayseri, Turkey
关键词
Multiobjective programming; Biobjective mixed 0-1 integer linear programming; Variable neighborhood search; Local branching; VARIABLE NEIGHBORHOOD SEARCH; VECTOR MAXIMIZATION; PROPER EFFICIENCY; KNAPSACK-PROBLEM; BOUND ALGORITHM; LOCATION;
D O I
10.1016/j.ejor.2015.04.010
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
In this study, biobjective mixed 0-1 integer linear programming problems are considered and two heuristic approaches are presented to find the Pareto frontier of these problems. The first heuristic is a variant of the variable neighborhood search and explores the k-neighbors of a feasible solution (in terms of binary variables) to find the extreme supported Pareto points. The second heuristic is adapted from the local branching method, which is well-known in single objective mixed 0-1 integer linear programming. Finally, an algorithm is proposed to find Pareto segments of outcome line segments of these heuristics. A computational analysis is performed by using some test problems from the literature and the results are presented. (C) 2015 Elsevier B.V. All rights reserved.
引用
收藏
页码:690 / 703
页数:14
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