The Robust Weapon Target Assignment Problem

• Published in: Military operations research (Alexandria, Va.) Vol. 28; no. 1; pp. 27 - 54
• Main Authors: Park, Jungho, El-Amine, Hadi
• Format: Journal Article
• Language: English
• Published: Military Operations Research Society 01.01.2023
• Subjects: RESEARCH ARTICLE
• ISSN: 1082-5983; 2163-2758
• DOI: 10.5711/1082598328127

We study the weapon target assignment problem under target information uncertainty. We propose three stochastic/robust optimization models that are average case, worst case, and regret oriented. We show that the average-case and worst-case oriented models can be rewritten as equivalent deterministic ones that are relatively easy to solve. We then show that the regret-based approach yields a model that is less conservative but is substantially more computationally demanding to solve as it includes a number of constraints that grow exponentially in the problem size. To address this, we propose three Benders-like decomposition schemes that increase in sophistication and incorporate two linearization schemes to handle nonlinear constraints. To assess the performance of our numerical schemes, we conduct an extensive numerical study. Our results indicate that our proposed algorithms perform well and solve most problem instances in reasonable time.