Abstract
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
Original language | English |
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Pages (from-to) | 628-642 |
Number of pages | 15 |
Journal | European Journal of Operational Research |
Volume | 267 |
Issue number | 2 |
DOIs | |
Publication status | Published - 18 Dec 2017 |
Research programs
- RSM LIS