Weapon-Target Assignment Problem by Multiobjective Evolutionary Algorithm Based on Decomposition

Xiaoyang Li,Yongchuan Tang,Jichuan Huang,Qian Pan,Deyun Zhou

doi:10.1155/2018/8623051

Abstract

The weapon-target assignment (WTA) problem is a key issue in Command & Control (C2). Asset-based multiobjective static WTA (MOSWTA) problem is known as one of the notable issues of WTA. Since this is an NP-complete problem, multiobjective evolutionary algorithms (MOEAs) can be used to solve it effectively. The multiobjective evolutionary algorithm based on decomposition (MOEA/D) is a practical and promising multiobjective optimization technique. However, MOEA/D is originally designed for continuous multiobjective optimization which loses its efficiency to discrete contexts. In this study, an improved MOEA/D is proposed to solve the asset-based MOSWTA problem. The defining characteristics of this problem are summarized and analyzed. According to these characteristics, an improved MOEA/D framework is introduced. A novel decomposition mechanism is designed. The mating restriction and selection operation are reformulated. Furthermore, a problem-specific population initialization method is presented to improve the efficiency of the proposed algorithm, and a novel nondominated solution-selection method is put forward to handle the constraints of Pareto front. Appropriate extensions of four MOEA variants are developed in comparison with the proposed algorithm on some generated scenarios. Extensive experiments demonstrate that the proposed method is effective and promising.

Highlights

Weapon-target assignment (WTA) problem is one of the most important problems in Command & Control (C2) [1]
The AG metric of multiobjective evolutionary algorithms (MOEAs)/D-WTA-r2 is better than multiobjective evolutionary algorithm based on decomposition (MOEA/D)-WTA in case 1, case 2, and case 4, the average time consumption (AT) metric of it is still worse than MOEA/D-WTA
The asset-based multiobjective static WTA (MOSWTA) problem is studied, which is a representative problem of multiobjective optimization weapon-target assignment (MOWTA)

Summary

Introduction

Weapon-target assignment (WTA) problem is one of the most important problems in Command & Control (C2) [1]. Li et al [32] introduced a modified Pareto ant colony optimization approach to solve the target-based multiobjective optimization static weapontarget assignment (MOSWTA) All these works have showed the advantage of solving MOWTA by using MOEA. In order to enhance the performance of MOEA/D in solving MOWTA, a novel framework of MOEA/D which is named as a multiobjective evolutionary algorithm based on decomposition for WTA (MOEA/D-WTA) is proposed, the contributions of this algorithm are described as follows:. In MOEA/D-WTA, a novel decomposition mechanism is designed to decompose the population into several subpopulations It decomposes the MOSWTA problem into M scalar optimization subproblems (M is the total number of weapons).

Problem Analysis

The Proposed Framework and Its Implementation

Subpopulation 4

Experimental Studies

Conclusions and Future Work