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Hybridization of very large neighborhood search for ready-mixed concrete delivery problems

机译:大型邻域搜索的混合解决预拌混凝土的输送问题

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摘要

Companies in the concrete industry are facing the following scheduling problem on a daily basis: concrete produced at several plants has to be delivered at customers' construction sites using a heterogeneous fleet of vehicles in a timely, but cost-effective manner. The distribution of ready-mixed concrete (RMC) is a highly complex problem in logistics and combinatorial optimization.rnThis paper proposes two hybrid solution procedures for dealing with this problem. They ate based on a combination of an exact algorithm and a variable neighborhood search (VNS) approach. The VNS is used at first to generate feasible solutions and is trying to further improve them. The exact method is based on a mixed integer linear programming (MILP) formulation, which is solved (after an appropriated variable fixing phase) by using a general-purpose MILP solver. An approach based on very large neighborhood search (VLNS) determines which variables are supposed to be fixed. In a sense, the approaches follows a local branching scheme. The hybrid metaheuristics are compared with the pure VNS approach and the conclusion is that the new metaheuristics outperform the VNS if applied solely.
机译:混凝土行业的公司每天都面临以下调度问题:必须将多个工厂生产的混凝土使用异构的车队及时,但经济高效地运送到客户的建筑工地。预拌混凝土(RMC)的分配在物流和组合优化中是一个非常复杂的问题。本文提出了两种混合解决方案来处理此问题。他们基于精确算法和可变邻域搜索(VNS)方法的结合来用餐。首先使用VNS生成可行的解决方案,并正在尝试进一步改进它们。确切的方法基于混合整数线性规划(MILP)公式,该公式通过使用通用的MILP求解器进行求解(在适当的变量固定阶段之后)。基于超大型邻域搜索(VLNS)的方法确定哪些变量应该固定。从某种意义上说,这些方法遵循本地分支方案。将混合元启发式方法与纯VNS方法进行了比较,得出的结论是,如果单独使用,新的元启发式方法将优于VNS。

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