Improved MOEA/D for Dynamic Weapon-Target Assignment Problem

Ying Zhang, Rennong Yang, Jialiang Zuo,Xiaoning Jing

(Air Force Engineering University Aeronautics and Astronautics Engineering College, Xi¡¯an 710038, China)



Abstract:

Conducting reasonable weapon-target assignment (WTA) with near real time can bring the maximum awards with minimum costs which are especially significant in the modern war. A framework of dynamic WTA (DWTA) model based on a series of staged static WTA (SWTA) models is established where dynamic factors including time window of target and time window of weapon are considered in the staged SWTA model. Then, a hybrid algorithm for the staged SWTA named Decomposition-Based Dynamic Weapon-target Assignment (D-DWTA) is proposed which is based on the framework of multi-objective evolutionary algorithm based on decomposition (MOEA/D) with two major improvements: one is the coding based on constraint of resource to generate the feasible solutions, and the other is the tabu search strategy to speed up the convergence. Comparative experiments prove that the proposed algorithm is capable of obtaining a well-converged and well diversified set of solutions on a problem instance and meets the time demand in the battlefield environment.

Key words:  multi-objective optimization (MOP)  dynamic weapon-target assignment (DWTA)  multi-objective evolutionary algorithm based on decomposition (MOEA/D)  tabu search

DOI£º10.11916/j.issn.1005-9113.2015.06.017

Clc Number:TP391

Fund: