...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Applied Mathematical Modelling >Permutation-induced Acyclic Networks For The Job Shop Scheduling Problem
【24h】

Permutation-induced Acyclic Networks For The Job Shop Scheduling Problem

机译：作业车间调度问题的排列诱导非循环网络

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

In the literature of the combinatorial optimization problems, it is a commonplace to find more than one mathematical model for the same problem. The significance of a model may be measured in terms of the efficiency of the solution algorithms that can be built upon it. The purpose of this article is to present a new network model for the well known combinatorial optimization problem - the job shop scheduling problem. The new network model has similar structure as the disjunctive graph model except that it uses permutations of jobs as decision variables instead of the binary decision variables associated with the disjunctive arcs. To assess the significance of the new model, the performances of exact branch-and-bound algorithmic implementations that are based on both the new model and the disjunctive graph model are compared.
机译：在组合优化问题的文献中，为同一问题找到多个数学模型是很平常的事。可以根据可以建立在模型上的求解算法的效率来衡量模型的重要性。本文的目的是为众所周知的组合优化问题-车间调度问题提供一种新的网络模型。新网络模型的结构与分离图模型相似，不同之处在于它使用作业的排列作为决策变量，而不是与分离弧相关的二元决策变量。为了评估新模型的重要性，比较了基于新模型和析取图模型的精确分支定界算法实现的性能。

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