Optimizing multi-objective uncertain multi-stage weapon target assignment problems with the risk measure CVaR

Juan Li*, Jie Chen, Bin Xin

*此作品的通讯作者

科研成果: 书/报告/会议事项章节会议稿件同行评审

3 引用 (Scopus)

摘要

This paper investigates the multi-objective uncertain multi-stage weapon target assignment (UMWTA) problem in which weapons' kill probabilities are considered to be uncertain from practical aspects. Here uncertainties are introduced by assuming that these probabilities depend on random parameters which are impacted by various factors. The multi-objective formulation of UMWTA problems covers the objectives of minimizing the risk of missing hostile targets measured by the conditional value-at-risk (CVaR) measure and minimizing the ammunition consumption. With the aim of determining referenced Pareto fronts, an approximated linear formulation of the UMWTA problem is put forward based on problem-specific characteristics. Two state-of-the-art decomposition-based multi-objective evolutionary algorithms (DMOEAs), i.e., MOEA/D-AWA and DMOEA -ϵC are used to solve the formulated problem. In view of the inefficiency of the standard comparison mechanism in DMOEAs, a hierarchical comparison strategy which takes into account Pareto dominance relationships and aggregated objective values simultaneously is proposed and embedded in MOEA/D-AWA and DMOEA-ϵC. MOEA/D-AWA and DMOEA-ϵC with the hierarchical comparison strategy are denoted as MOEA/D-AWA-H and DMOEA-ϵC-H, respectively. Numerical experiments have been performed on two sets of UMWTA instances. Experimental results confirm the effectiveness of the proposed hierarchical comparison strategy and demonstrate the superiority of DMOEA-ϵC-H over MOEA/D-AWA-H on the majority of test instances.

源语言英语
主期刊名2019 IEEE 15th International Conference on Control and Automation, ICCA 2019
出版商IEEE Computer Society
61-66
页数6
ISBN(电子版)9781728111643
DOI
出版状态已出版 - 7月 2019
活动15th IEEE International Conference on Control and Automation, ICCA 2019 - Edinburgh, 英国
期限: 16 7月 201919 7月 2019

出版系列

姓名IEEE International Conference on Control and Automation, ICCA
2019-July
ISSN(印刷版)1948-3449
ISSN(电子版)1948-3457

会议

会议15th IEEE International Conference on Control and Automation, ICCA 2019
国家/地区英国
Edinburgh
时期16/07/1919/07/19

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引用此

Li, J., Chen, J., & Xin, B. (2019). Optimizing multi-objective uncertain multi-stage weapon target assignment problems with the risk measure CVaR. 在 2019 IEEE 15th International Conference on Control and Automation, ICCA 2019 (页码 61-66). 文章 8899501 (IEEE International Conference on Control and Automation, ICCA; 卷 2019-July). IEEE Computer Society. https://doi.org/10.1109/ICCA.2019.8899501