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Heuristic approaches for biobjective mixed 0-1 integer linear programming problems
DOI:10.1016/j.ejor.2015.04.010.png)
摘要
En 中文
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.
Keyword:
Multiobjective programming
Biobjective mixed 0-1 integer linear programming
Variable neighborhood search
Local branching
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期刊
IF:
6
论文数:
2.2W
被引数:
6.4W
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引用论文
Multiple objective branch and bound for mixed 0-1 linear programming: Corrections and improvements for the biobjective case混合0-1线性规划的多目标分支和界限: 对双目标情况的修正和改进
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