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Continuous Genetic Algorithms in the Optimization of Logistic Networks: Applicability Assessment and Tuning

Institute of Information Technology, Lodz University of Technology, 215 Wólczańska St., 90-924 Łódź, Poland
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Appl. Sci. 2020, 10(21), 7851; https://doi.org/10.3390/app10217851
Received: 20 September 2020 / Revised: 23 October 2020 / Accepted: 3 November 2020 / Published: 5 November 2020
(This article belongs to the Section Computing and Artificial Intelligence)
Globalization opens up new perspectives for handling goods distribution in logistic networks. However, establishing an efficient inventory policy is challenging by virtue of the analytical and computational complexity. In this study, the goods distribution process that was governed by the order-up-to policy, implemented in either a distributed or centralized way, was investigated in the logistic systems with complex interconnection topologies. Uncertain demand may be imposed at any node, not just at conveniently chosen contact points, with a lost-sales assumption that introduces a non-linearity into the node dynamics. In order to adjust the policy parameters, the continuous genetic algorithm (CGA) was applied, with the fitness function incorporating both the operational costs and customer satisfaction level. This study investigated how to select the parameters of the popular inventory management policy when operating in the non-trivial networked structures. Moreover, precise guidelines for the CGA tuning in the considered class of problems were provided and evaluated in extensive numerical experiments. View Full-Text
Keywords: logistic networks; supply chain management; inventory control; optimization; genetic algorithms; time-delay systems logistic networks; supply chain management; inventory control; optimization; genetic algorithms; time-delay systems
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MDPI and ACS Style

Ignaciuk, P.; Wieczorek, Ł. Continuous Genetic Algorithms in the Optimization of Logistic Networks: Applicability Assessment and Tuning. Appl. Sci. 2020, 10, 7851. https://doi.org/10.3390/app10217851

AMA Style

Ignaciuk P, Wieczorek Ł. Continuous Genetic Algorithms in the Optimization of Logistic Networks: Applicability Assessment and Tuning. Applied Sciences. 2020; 10(21):7851. https://doi.org/10.3390/app10217851

Chicago/Turabian Style

Ignaciuk, Przemysław, and Łukasz Wieczorek. 2020. "Continuous Genetic Algorithms in the Optimization of Logistic Networks: Applicability Assessment and Tuning" Applied Sciences 10, no. 21: 7851. https://doi.org/10.3390/app10217851

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