Weapon-target Assignment with an Improved Multi-objective Particle Swarm Optimization Algorithm

doi:10.3969/j.issn.1000-1093.2016.11.017

Abstract

Abstract: Weapon-target assignment (WTA) with numerous variables in modern campaign is a typical non-deterministic polynomial (NP) complete problem. An optimization model based on improved multi-objective swarm optimization algorithm (MOPSO-II) is established to solve the objective functions of maximum damage probability and minimum ammunition consumption. Since “curse of dimensionality” occurs in the objective swarm optimization algorithm (PSO), the random variable decomposition strategy and cooperative co-evolution evolutionary frame are used for variable decomposition, and also all swarms are composited by using the non-dominated set algorithm in NSGA-II. The simulated results show that MOPSO-II is quicker and more effective than NSGA-II, and can give good WTA quickly, especially when the scale of WTA problem is large.

Key words: ordnance science and technology, multi-objective optimization, particle swarm optimization, firepower distribution, Pareto set, weapon-target assignment

CLC Number:

E920.8

XIA Wei， LIU Xin-xue， FAN Yang-tao， YUAN Feng-gang. Weapon-target Assignment with an Improved Multi-objective Particle Swarm Optimization Algorithm[J]. Acta Armamentarii, 2016, 37(11): 2085-2093.

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