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An Adaptive Large Neighborhood Search Algorithm for the Resource-constrained Project Scheduling Problem

机译:资源受限项目调度问题的自适应大邻域搜索算法

摘要

We present an application of an Adaptive Large Neighborhood Search (ALNS) algorithm to the Resource-constrained Project Scheduling Problem (RCPSP). The ALNS framework was first proposed by Pisinger and Røpke [19] and can be described as a large neighborhood search algorithm with an adaptive layer, where a set of destroy/repair neighborhoods compete to modify the current solution in each iteration of the algorithm. Experiments are performed on the wellknown J30, J60 and J120 benchmark instances, which show that the proposed algorithm is competitive and confirms the strength of the ALNS framework previously reported for different variants of the Vehicle Routing Problem.
机译:我们提出一种自适应大邻域搜索(ALNS)算法在资源受限的项目计划问题(RCPSP)中的应用。 ALNS框架最初是由Pisinger和Røpke[19]提出的,可以描述为具有自适应层的大型邻域搜索算法,其中,一组破坏/修复邻域在算法的每次迭代中竞争修改当前解决方案。在著名的J30,J60和J120基准实例上进行了实验,这些实验表明所提出的算法具有竞争力,并确认了先前针对车辆路径问题的不同变型报告的ALNS框架的强度。

著录项

  • 作者

    Muller Laurent Flindt;

  • 作者单位
  • 年度 2009
  • 总页数
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类

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