DocumentCode
2226814
Title
Solving multi-objective multi-stage weapon target assignment problem via adaptive NSGA-II and adaptive MOEA/D: A comparison study
Author
Li, Juan ; Chen, Jie ; Xin, Bin ; Dou, LiHua
Author_Institution
School of Automation, Beijing Institute of Technology, Key Laboratory of Complex System Intelligent Control and Decision, Beijing, P.R. China
fYear
2015
fDate
25-28 May 2015
Firstpage
3132
Lastpage
3139
Abstract
The weapon target assignment (WTA) problem is a fundamental problem arising in defense-related applications of operations research, and the multi-stage weapon target assignment (MWTA) problem is the basis of dynamic weapon target assignment (DWTA) problems which commonly exist in practice. The MWTA problem considered in this paper is formulated into a multi-objective constrained combinatorial optimization problem with two competing objectives. Apart from maximizing damage to hostile targets, this paper follows the principle of minimizing ammunition consumption under the consideration of resource constraints, feasibility constraints and fire transfer constraints. In order to tackle the two challenges, two types of multi-objective optimizers: NSGA-II (domination-based) and MOEA/D (decomposition-based) enhanced with an adaptive mechanism are adopted to achieve efficient problem solving. Then a comparison study between adaptive NSGA-II (ANSGA-II) and adaptive MOEA/D (AMOEA/D) on solving instances of three scales MWTA problems is done, and four performance metrics are used to evaluate each algorithm. Numerical results show that ANSGA-II outperforms AMOEA/D on solving multi-objective MWTA problems discussed in this paper, and the adaptive mechanism definitely enhances performances of both algorithms.
Keywords
Discrete wavelet transforms; Fires; Genetics; Optimization; Sociology; Statistics; Weapons; adaptive mechanism; combinatorial optimization; fire transfer constraints; multi-objective constrained optimization problem; multi-objective evolutionary algorithm based on decomposition (MOEA/D); multi-stage weapon target assignment (MWTA); non-dominated sorting genetic algorithm with elitist strategy (NSGA-II);
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation (CEC), 2015 IEEE Congress on
Conference_Location
Sendai, Japan
Type
conf
DOI
10.1109/CEC.2015.7257280
Filename
7257280
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