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A genetic algorithm-based heuristic for the dynamic integrated forward/reverse logistics network for 3PLs. (English) Zbl 1113.90028
Summary: Today’s competitive business environment has resulted in increasing cooperation among individual companies as members of a supply chain. Accordingly, third party logistics providers (3PLs) must operate supply chains for a number of different clients who want to improve their logistics operations for both forward and reverse flows. As a result of the dynamic environment in which these supply chains must operate, 3PLs must make a sequence of inter-related decisions over time. However, in the past, the design of distribution networks has been independently conducted with respect to forward and reverse flows. Thus, this paper presents a mixed integer nonlinear programming model for the design of a dynamic integrated distribution network to account for the integrated aspect of optimizing the forward and return network simultaneously. Since such network design problems belong to a class of NP hard problems, a genetic algorithm-based heuristic with associated numerical results is presented and tested in a set of problems by an exact algorithm. Finally, a solution of a network plan would help in the determination of various resource plans for capacities of material handling equipments and human resources.

90B10 Deterministic network models in operations research
90B06 Transportation, logistics and supply chain management
90C59 Approximation methods and heuristics in mathematical programming
Full Text: DOI
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