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

作     者：Wieczorek, Lukasz Ignaciuk, Przemyslaw 

作者机构：Lodz Univ Technol Inst Informat Technol PL-90924 Lodz Poland 

出 版 物：《DATA》 (Data)

年 卷 期：2018年第3卷第4期

页      面：68页

核心收录：

主　　题：supply chain inventory control optimization artificial intelligence evolutionary algorithms uncertain demand 

摘      要：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 actorscontrolled nodes and external sourcesinterconnected 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 objectivesholding 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.