...
首页> 外文期刊>Artificial intelligence >Filtering AtMostNValue with difference constraints: Application to the shift minimisation personnel task scheduling problem
【24h】

Filtering AtMostNValue with difference constraints: Application to the shift minimisation personnel task scheduling problem

机译:筛选具有差异约束的AtMostNValue:在最小化班次人员任务调度问题中的应用

获取原文
获取原文并翻译 | 示例
           

摘要

The problem of minimising the number of distinct values among a set of variables subject to difference constraints occurs in many real-life contexts. This is the case of the Shift Minimisation Personnel Task Scheduling Problem, introduced by Krishnamoorthy et al., which is used as a case study all along this paper. Constraint-Programming enables to formulate this problem easily, through several AllDif ferent constraints and a single AtMostNValue constraint. However, the independence of these constraints results in a poor lower bounding, hence a difficulty to prove optimality. This paper introduces a formalism to describe a family of propagators for AtMostNValue. In particular, we provide simple but significant improvement of the state-of-the-art AtMostNValue propagator of Bessiere et al., to filter the conjunction of an AtMostNValue constraint and disequalities. In addition, we provide an original search strategy which relies on constraint reification. Extensive experiments show that our contribution significantly improves a straightforward model, so that it competes with the best known approaches from Operational Research.
机译:在许多现实情况下,都会出现使受差异约束的一组变量中不同值的数量最小化的问题。这就是Krishnamoorthy等人提出的“班次最小化人员任务计划问题”,在本文中一直作为案例研究。约束编程通过几个AllDif相关约束和一个AtMostNValue约束,可以轻松地表达此问题。然而,这些约束的独立性导致较差的下界,因此难以证明最优性。本文介绍了一种形式主义,用于描述AtMostNValue的传播者系列。特别是,我们对Bessiere等人的最新的AtMostNValue传播器进行了简单但重要的改进,以过滤AtMostNValue约束和不等式的结合。另外,我们提供了一种依赖约束约束的原始搜索策略。大量的实验表明,我们的贡献大大改善了一个简单的模型,因此它可以与运筹学中最著名的方法竞争。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号