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Exact and Heuristic Methods for the Weapon Target Assignment Problem

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  • Ahuja, Ravindra
  • Kumar, Arvind
  • Jha, Krishna
  • Orlin, James
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    Abstract

    The Weapon Target Assignment (WTA) problem is a fundamental problem arising in defense-related applications of operations research. This problem consists of optimally assigning n weapons to m targets so that the total expected survival value of the targets after all the engagements is minimum. The WTA problem can be formulated as a nonlinear integer programming problem and is known to be NP-complete. There do not exist any exact methods for the WTA problem which can solve even small size problems (for example, with 20 weapons and 20 targets). Though several heuristic methods have been proposed to solve the WTA problem, due to the absence of exact methods, no estimates are available on the quality of solutions produced by such heuristics. In this paper, we suggest linear programming, integer programming, and network flow based lower bounding methods using which we obtain several branch and bound algorithms for the WTA problem. We also propose a network flow based construction heuristic and a very large-scale neighborhood (VLSN) search algorithm. We present computational results of our algorithms which indicate that we can solve moderately large size instances (up to 80 weapons and 80 targets) of the WTA problem optimally and obtain almost optimal solutions of fairly large instances (up to 200 weapons and 200 targets) within a few seconds.

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    File URL: http://hdl.handle.net/1721.1/7388
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    Bibliographic Info

    Paper provided by Massachusetts Institute of Technology (MIT), Sloan School of Management in its series Working papers with number 4464-03.

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    Date of creation: 10 Dec 2004
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    Handle: RePEc:mit:sloanp:7388

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    Web page: http://mitsloan.mit.edu/
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    Postal: MASSACHUSETTS INSTITUTE OF TECHNOLOGY (MIT), SLOAN SCHOOL OF MANAGEMENT, 50 MEMORIAL DRIVE CAMBRIDGE MASSACHUSETTS 02142 USA

    Related research

    Keywords: Weapon Target Assignment; WTA; very large-scale neighborhood search algorithm;

    This paper has been announced in the following NEP Reports:

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