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Continuous Genetic Algorithms as Intelligent Assistance for Resource Distribution in Logistic Systems

Institute of Information Technology, Lodz University of Technology, 90-924 Łódź, Poland
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This paper is an extended version of conference paper: Lukasz Wieczorek, Przemyslaw Ignaciuk. “Intelligent Support for Resource Distribution in Logistic Networks Using Continuous-Domain Genetic Algorithms”, 2018 IEEE Second International Conference on Data Stream Mining & Processing (DSMP), 2018.
Received: 14 November 2018 / Revised: 10 December 2018 / Accepted: 12 December 2018 / Published: 16 December 2018
(This article belongs to the Special Issue Data Stream Mining and Processing)
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Abstract

This paper addresses the problem of resource distribution control in logistic systems influenced by uncertain demand. The considered class of logistic topologies comprises two types of actors—controlled nodes and external sources—interconnected without any structural restrictions. In this paper, the application of continuous-domain genetic algorithms (GAs) is proposed in order to support the optimization process of resource reflow in the network channels. GAs allow one to perform simulation-based optimization and provide desirable operating conditions in the face of a priori unknown, time-varying demand. The effectiveness of inventory management process governed under an order-up-to policy involves two different objectives—holding costs and service level. Using the network analytical model with the inventory management policy implemented in a centralized way, GAs search a space of candidate solutions to find optimal policy parameters for a given topology. Numerical experiments confirm the analytical assumptions. View Full-Text
Keywords: supply chain; inventory control; optimization; artificial intelligence; evolutionary algorithms; uncertain demand supply chain; inventory control; optimization; artificial intelligence; evolutionary algorithms; uncertain demand
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Wieczorek, Ł.; Ignaciuk, P. Continuous Genetic Algorithms as Intelligent Assistance for Resource Distribution in Logistic Systems. Data 2018, 3, 68.

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