Improved Decomposition-Based Evolutionary Algorithm for Multi-objective Optimization Model of Dynamic Weapon-targetAssignment

doi:10.3969/j.issn.1000-1093.2015.08.022

Abstract

Abstract: A reasonable weapon-target assignment(WTA) scheme is developed to optimize the allocation of limited resources, which brings the maximum awards with minimum costs. A dynamic weapon-target assignment(DWTA) multi-objective optimization model is established, especially for the offensive operation with multi-weapon. The proposed model is composed of several stage static models. The parameters of each stage model are obtained from the battlefield in real time. An algorithm is elaborately studied to solve the stage model based on the hypothesis to deal with the dynamic model. According to the characteristic of the proposed model, an encoding mode is constructed to satisfy the resource constraints. An improved decomposition-based evolutionary algorithm is proposed by mixing of tabu search and crowding distance strategies. Comparative experiments prove that the proposed algorithm is feasible, fast and efficient.

Key words: ordnance science and technology, multi-objective optimization, dynamic weapon-target assignment, decomposition-based evolutionary algorithm, tabu search

CLC Number:

TP391

ZHANG Ying, YANG Ren-nong, ZUO Jia-liang, JING Xiao-ning, HE Gui-bo. Improved Decomposition-Based Evolutionary Algorithm for Multi-objective Optimization Model of Dynamic Weapon-targetAssignment[J]. Acta Armamentarii, 2015, 36(8): 1533-1540.

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