基于杀伤网评估的装备组合多目标优化

doi:10.12305/j.issn.1001-506X.2021.02.15

摘要/Abstract

摘要：

杀伤网作为众多新型作战理念中均有涉及的概念,将替代杀伤链成为新型作战方式下战斗力生成的主要模式。本文基于杀伤网的评估,对传统的装备组合问题进行多目标优化。首先,基于多层网络模型,构建杀伤网的网络化描述方法。其次,基于杀伤网的特点,构建3个评估指标:冗余性指标、风险性指标、敏捷性指标,并给出了3个评估指标的计算模型。然后,构建了基于杀伤网评估指标的装备组合规划模型,并给出了基于启发式算法的装备组合多目标优化方法。最后，进行示例研究,通过评估两种具有不同装备组成和网络结构的杀伤网,对比其优劣,然后针对第一种包含无人装备的杀伤网进行装备组合优化,分别验证了评估模型的合理性以及优化模型的有效性。

关键词: 杀伤网, 装备组合, 冗余性, 风险性, 敏捷性, 多目标优化

Abstract:

As a concept involved in many new combat concepts, the kill-web will replace the kill-chain as the main mode for generating combat effectiveness under the novel combat operations. In this paper, we make multiple-objective optimization for the problem of the traditional equipment portfolio based on the evaluation of kill-web. First, we construct the network description method of kill-web based on the multi-layer network model. Second, we constrult three evaluation criteria based on the characteristics of kill-web including redundancy indicator, risk indicator, and agility indicator, and propose the calculation model of three evaluation indicator. Then, we construct an equipment portfolio programming model based on the kill-web evaluation criteria and present a heuristic algorithm-based multi-objective optimization method of equipment portfolio. Finally, we carry out a case study to compare the advantages and disadvantages of two different kill-webs with different equipment composition and network structure, and then optimize the equipment portfolio based on the first kill-web including unmanned equipment to verify the rationality of the evaluation model and the effectiveness of the optimization model, respectively.

Key words: kill-web, equipment portfolio, redundancy, risk, agility, multi-objective optimization

中图分类号:

N945.15

夏博远, 杨克巍, 杨志伟, 张小可, 赵丹玲. 基于杀伤网评估的装备组合多目标优化[J]. 系统工程与电子技术, 2021, 43(2): 399-409.

Boyuan XIA, Kewei YANG, Zhiwei YANG, Xiaoke ZHANG, Danling ZHAO. Multi-objective optimization of equipment portfolio based on kill-web evaluation[J]. Systems Engineering and Electronics, 2021, 43(2): 399-409.

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