Multi-objective minmax robust combinatorial optimization with cardinality-constrained uncertainty

作者：Raith Andrea; Schmidt Marie; Schoebel Anita; Thom Lisa^*

来源：European Journal of Operational Research, 2018, 267(2): 628-642.

DOI：10.1016/j.ejor.2017.12.018

• Multiple objective programming
• Robust optimization
• Combinatorial optimization
• Multi-objective robust optimization
• Shortest path problem

In this paper, we develop two approaches to find minmax robust efficient solutions for multi-objective combinatorial optimization problems with cardinality-constrained uncertainty. First, we extend an existing algorithm for the single-objective problem to multi-objective optimization. We propose also an enhancement to accelerate the algorithm, even for the single-objective case, and we develop a faster version for special multi-objective instances. Second, we introduce a deterministic multi-objective problem with sum and bottleneck functions, which provides a superset of the robust efficient solutions. Based on this, we develop a label setting algorithm to solve the multi-objective uncertain shortest path problem. We compare both approaches on instances of the multi-objective uncertain shortest path problem originating from hazardous material transportation.

• 出版日期2018-6-1