A genetic algorithm-based heuristic for the dynamic integrated forward/reverse logistics network for 3PLs.

*(English)*Zbl 1113.90028Summary: 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.

##### MSC:

90B10 | Deterministic network models in operations research |

90B06 | Transportation, logistics and supply chain management |

90C59 | Approximation methods and heuristics in mathematical programming |

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\textit{H. J. Ko} and \textit{G. W. Evans}, Comput. Oper. Res. 34, No. 2, 346--366 (2007; Zbl 1113.90028)

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