Journal of System Simulation ›› 2024, Vol. 36 ›› Issue (6): 1285-1297.doi: 10.16182/j.issn1004731x.joss.24-0116

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Dynamic Air Defense Resource Allocation Optimization Based on Improved Differential Evolution Algorithm

Luo Tianyu1(), Xing Lining2(), Wang Rui1, Wang Ling3, Shi Jianmai1, Sun Xin1   

  1. 1.College of Systems Engineering, National University of Defense Science and Technology, Changsha 410073, China
    2.College of Electronic Engineering, Xi'an University of Electronic Science and Technology, Xi'an 710071, China
    3.Department of Automation, Tsinghua University, Beijing 100084, China
  • Received:2024-01-30 Revised:2024-04-27 Online:2024-06-28 Published:2024-06-19
  • Contact: Xing Lining E-mail:luotianyu951005@163.com;lnxing@xidian.edu.cn

Abstract:

Based on the integrated performance of weapon equipments such as radars, launchers and missiles, a mixed-integer decision model that minimizes the total target intercept value and the probability of survival based on Target-Set, Resource-Set is developed. A new improved differential evolutionary algorithm has been introduced to solve the problem, and the initial solutions is generated by using the reverse learning strategies to ensure the quality of the initial populations. An inspiration rule for the fast repair and reconstruction is designed to work at multi-stage to improve the search capability of the algorithm. The simulation experiment results show the algorithm's superiority in search time and search accuracy, which can maintain the efficient combat capabilities and decision-making under the random influence of dynamic events.

Key words: air defense operations, dynamic air defense resource allocation, opposition-based learning, improved differential evolution algorithm

CLC Number: