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A general variable neighborhood search-based solution approach for the location-inventory-routing problem with distribution outsourcing

机译:基于一般变量邻域搜索的配送外包中位置库存路由问题的解决方法

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摘要

This work presents a Mixed Integer Programing (MIP) formulation for a new complex NP-hard combinatorial optimization problem, the Location Inventory Routing with Distribution Outsourcing (LIRPDO). Due to its computational complexity, only small problem instances can be solved by exact solvers. Therefore, a General Variable Neighborhood Search (GVNS)-based metaheuristic algorithm for solving large LIRPDO instances is presented. The proposed approach has been tested on 20 new randomly generated LIRPDO instances, 20 existing benchmark LIRP instances from the literature and 30 new large-scale random generated LIRP instances. An extended numerical analysis illustrates the efficiency of the underlying method, leading to acceptable solutions requiring limited computational effort. (C) 2019 Elsevier Ltd. All rights reserved.
机译:这项工作提出了一个新的复杂的NP硬组合优化问题,即带有分销外包的位置库存路由的混合整数编程(MIP)公式。由于其计算复杂性,精确的求解器只能解决小问题实例。因此,提出了一种基于通用可变邻域搜索(GVNS)的元启发式算法来求解大型LIRPDO实例。在20个新的随机生成的LIRPDO实例,文献中的20个现有基准LIRP实例以及30个新的大规模随机生成的LIRP实例上测试了该方法。扩展的数值分析说明了基础方法的效率,从而导致可接受的解决方案需要有限的计算工作。 (C)2019 Elsevier Ltd.保留所有权利。

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