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Solving discrete multi-objective optimization problems using modified augmented weighted Tchebychev scalarizations
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DOI：10.1016/j.ejor.2018.05.036.png)
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摘要
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In this paper we present the modified augmented weighted Tchebychev norm, which can be used to generate a complete efficient set of solutions to a discrete multi-objective optimization problem. We contribute a generating algorithm that will, without supervision, generate the entire non-dominated set for any number of objectives. To our knowledge, this is the first generating method for general discrete multi objective problems that uses a variant of the Tchebychev norm. In a computational study, our algorithm's running times are comparable to previously proposed algorithms. (C) 2018 Elsevier B.V. All rights reserved.
Keyword:
Multiple objective programming
Tchebychev norm
Computational optimization
Generating methods
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6
论文数:
2.2W
被引数:
6.4W
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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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