Lagrangian relaxation approach to the targeting problem

✍ Scribed by Ojeong Kwon; Donghan Kang; Kyungsik Lee; Sungsoo Park

• Publisher: John Wiley and Sons
• Year: 1999
• Tongue: English
• Weight: 116 KB
• Volume: 46
• Category: Article
• ISSN: 0894-069X
• DOI: 10.1002/(sici)1520-6750(199909)46:6<640::aid-nav3>3.0.co;2-q

✦ Synopsis

In this paper, we consider a new weapon-target allocation problem with the objective of minimizing the overall firing cost. The problem is formulated as a nonlinear integer programming model. We applied Lagrangian relaxation and a branch-and-bound method to the problem after transforming the nonlinear constraints into linear ones. An efficient primal heuristic is developed to find a feasible solution to the problem to facilitate the procedure. In the branch-and-bound method, three different branching rules are considered and the performances are evaluated. Computational results using randomly generated data are presented.