Designing a reliable hierarchical military logistic network using an improved simplified swarm optimization. (July 2022)

• Record Type: Journal Article
• Authors: Lai, Chyh-Ming; Tseng, Ming-Lang
• Is Part Of: Computers & industrial engineering. Volume 169(2022)
• Publication Date: 2022-07
• Subjects: Reliable hierarchical facility location model -- Simplified swarm optimization -- System reliability -- Military logistic network design; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2022.108153
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: A novel reliable facility location problem is considered from the system reliability perspective. A new solution approach with a satisfactory solution quality and acceptable time is proposed. A location decision for a military logistic network is determined by solving integer programming. Statistical results indicate that the proposed method is better than its competitors. Abstract: This study presents a novel reliable hierarchical facility location model addressing a real-world military logistic network design problem, where facilities are subject to the risk of disruptions. It views the proposed model from a system reliability perspective. The reliability for a battalion is interpreted as the probability of required supplies delivered to its combat units via its primary and backup depots. In addition, this study seeks to design a military logistic network with stated reliability and pursues to minimize the total cost. An improved simplified swarm optimization (iSSO) with two novel mechanisms was developed to solve the proposed model due to the NP-hardness of the problem under consideration. The efficiency for solving small-scale problems via the comparison of results with CPLEX is investigated. Furthermore, the performance of the presented iSSO is compared with widely popular evolutionary algorithms on large-scale problems. Comprehensive analysis indicates that iSSO is highly competitive and performs well in terms of solution quality and convergence rate.