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Mathematical Problems in Engineering
Volume 2017, Article ID 9897153, 13 pages
https://doi.org/10.1155/2017/9897153
Research Article

MOQPSO-D/S for Air and Missile Defense WTA Problem under Uncertainty

School of Air and Missile Defense, Air Force Engineering University, Xi’an 710051, China

Correspondence should be addressed to Hao Xu; moc.361@oahuxdgk

Received 16 December 2016; Revised 5 November 2017; Accepted 12 November 2017; Published 14 December 2017

Academic Editor: Erik Cuevas

Copyright © 2017 Hao Xu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Aiming at the shortcomings of single objective optimization for solving weapon target assignment (WTA) and the existing multiobjective optimization based WTA method having problems being applied in air and missile defense combat under uncertainty, a fuzzy multiobjective programming based WTA method was proposed to enhance the adaptability of WTA decision to the changes of battlefield situation. Firstly, a multiobjective quantum-behaved particle swarm optimization with double/single-well (MOQPSO-D/S) algorithm was proposed by adopting the double/single-well based position update method, the hybrid random mutation method, and the two-stage based guider particles selection method. Secondly, a fuzzy multiobjective programming WTA model was constructed with consideration of air and missile defense combat’s characteristics. And, the uncertain WTA model was equivalently clarified based on the necessity degree principle of uncertainty theory. Thirdly, with particles encoding and illegal particles adjusting, the MOQPSO-D/S algorithm was adopted to solve the fuzzy multiobjective programming based WTA model. Finally, example simulation was conducted, and the result shows that the WTA model constructed is rational and MOQPSO-D/S algorithm is efficient.