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

机译:基于邻邻域的一个基于变量邻域的搜索方法,用于分发外包的位置清点路由问题

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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:这项工作提出了一种混合整数编程(MIP)配方,用于新的复杂NP-Hard Combinatial优化问题,该位置与分发外包的位置库存路由(Lirpdo)。由于其计算复杂性,仅通过精确的求解器来解决小问题实例。因此,呈现了用于解决大型LIRPDO实例的一般变量邻域搜索(GVNS)的成群质算法。所提出的方法已经在20个新的随机生成的Lirpdo实例中测试了来自文献的现有基准LiRP实例,以及30个新的大规模随机生成的Lirp实例。扩展数值分析说明了底层方法的效率,导致需要有限的计算工作的可接受的解决方案。 (c)2019 Elsevier Ltd.保留所有权利。

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