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A multi-start iterated local search with tabu list and path relinking for the two-echelon location-routing problem

机译:带有禁忌列表和路径重新链接的多级迭代本地搜索,用于解决两级位置路由问题

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The two-echelon location-routing problem (LRP-2E) is raised by the design of transportation networks with two types of trips: first-level trips serving from one main depot a set of satellite depots, to be located, and second-level trips supplying customers from these satellites. In the proposed multi-start iterated local search (MS-ILS), three greedy randomized heuristics are used cyclically to get initial solutions. Each ILS run alternates between two search spaces: LRP-2E solutions, and travelling salesman (TSP) tours covering the main depot and the customers. The number of iterations allotted to a run is reduced whenever a known solution (stored in a tabu list) is revisited. MS-ILS can be reinforced by a path-relinking procedure (PR), used internally for intensification, as post-optimization, or both. On two sets with 24 and 30 LRP-2E instances, MS-ILS outperforms on average two GRASP algorithms and adding PR brings a further improvement. Our metaheuristic also surpasses a tabu search on 30 instances for a more general problem with several main depots. It is still effective on a particular case, the capacitated location-routing problem (CLRP): In a comparison with four published metaheuristics, only one (LRGTS, Prins et al., 2007) does better.
机译:通过设计两种旅行类型的运输网络,提出了两级选址路由问题(LRP-2E):从一个主仓库服务的一级旅行和要定位的一组卫星仓库,以及第二级旅行通过这些卫星为客户提供服务的旅行。在提出的多起点迭代局部搜索(MS-ILS)中,循环使用三个贪婪随机启发式算法以获得初始解。每个ILS的运行都在两个搜索空间之间交替进行:LRP-2E解决方案和涵盖主要仓库和客户的旅行推销员(TSP)巡回演出。每当重新访问已知的解决方案(存储在禁忌列表中)时,分配给运行的迭代次数都会减少。 MS-ILS可以通过路径重新链接过程(PR)进行增强,该过程在内部用于增强,后优化或两者兼而有之。在两个分别具有24个和30个LRP-2E实例的集合上,MS-ILS平均优于两种GRASP算法,并且添加PR带来了进一步的改进。我们的元启发式方法还超过了针对30个实例的禁忌搜索,以解决几个主要仓库中更普遍的问题。在特定情况下,容量定位路由问题(CLRP)仍然有效:与四种已发布的元启发式方法进行比较,只有一种方法(LRGTS,Prins等,2007)效果更好。

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