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
Link To Document :
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