Multi‐Target Strike Path Planning Based on Improved Decomposition Evolutionary Algorithm

Abstract

This study proposes a path-finding model for multi-target strike planning. The model evaluates three elements, i.e., the target value, the aircraft’s threat tolerance, and the battlefield threat, and optimizes the striking path by constraining the balance between mission execution and the combat survival. In order to improve the speed of the Multi-Objective Evolutionary Algorithm Based on Decomposition (MOEA/D), we use the conjugate gradient method for optimization. A Gaussian perturbation is added to the search points to make their distribution closer to the population distribution. The simulation shows that the proposed method effectively chooses its target according to the target value and the aircraft’s acceptable threat value, completes the strike on high value targets, evades threats, and verifies the feasibility and effectiveness of the multi-objective optimization model.

An Approach to Air-to-Surface Mission Planner on 3D Environments for an Unmanned Combat Aerial Vehicle

“…For this reason, many studies have been conducted to perform missions using UCAVs. Through these efforts, several approaches are proposed to efficiently plan ASMs [1][2][3][4][5][6][7][8][9][10][11][12][13][14] in Table 1. Randal W Beard et al [1] proposed an ASM planning algorithm for multiple UCAVs.…”

“…Table 1. ASM Planner's characteristics of the literature [1][2][3][4][5][6][7][8][9][10][11][12][13][14].…”