首页> 外文期刊>Informatica: An International Journal of Computing and Informatics >Minimum Flows in Parametric Dynamic Networks. The Static Approach
【24h】

Minimum Flows in Parametric Dynamic Networks. The Static Approach

机译:参数动态网络中的最小流动。静态方法

获取原文
           

摘要

The problems of flows in parametric networks extend the classical problems of optimal flow to some special kind of networks where capacities of certain arcs are not constants but depending on several parameters. Consequently, these problems consist of solving a range of ordinary (nonparametric) optimal flow problems for all the parameter values within certain sub-intervals of the parameter values. Although classical network flow models have been widely used as valuable tools for many applications [1], they fail to capture the essential property of the dynamic aspect of many real-life problems, such as traffic planning, production and distribution systems, communication systems, evacuation planning, etc. In all these cases, time is an essential component, either because the flows take time to pass from one location to another, or because the structure of the network changes over time. Accordingly, the dynamic flow models seem suited to catch and describe different real-life dynamic problems such as network-structure changing over time or timely decision-making, but, because of their complexity, these models have not been as thoroughly investigated as those of classical flows.This article presents and solves the problem of the minimum flows in a parametric dynamic network. The proposed approach consists in applying a parametric flow algorithm in the reduced expended network which is obtained by expanding the original dynamic network. A numerical example is also presented for a better understanding of the used approach. The problems of flows in parametric networks extend the classical problems of optimal flow to some special kind of networks where capacities of certain arcs are not constants but depending on several parameters. Consequently, these problems consist of solving a range of ordinary (nonparametric) optimal flow problems for all the parameter values within certain sub-intervals of the parameter values. Although classical network flow models have been widely used as valuable tools for many applications [1], they fail to capture the essential property of the dynamic aspect of many real-life problems, such as traffic planning, production and distribution systems, communication systems, evacuation planning, etc. In all these cases, time is an essential component, either because the flows take time to pass from one location to another, or because the structure of the network changes over time. Accordingly, the dynamic flow models seem suited to catch and describe different real-life dynamic problems such as network-structure changing over time or timely decision-making, but, because of their complexity, these models have not been as thoroughly investigated as those of classical flows.This article presents and solves the problem of the minimum flows in a parametric dynamic network. The proposed approach consists in applying a parametric flow algorithm in the reduced expended network which is obtained by expanding the original dynamic network. A numerical example is also presented for a better understanding of the used approach.
机译:参数网络中流动的问题将最佳流的经典问题扩展到某种特殊类型的网络,其中某些弧的容量不是常数,而是取决于几个参数。因此,这些问题由求解参数值的某些子间隔内的所有参数值的一系列普通(非参数)最佳流量问题。虽然经典网络流模型已被广泛用作许多应用的宝贵工具[1],但它们未能捕获许多现实问题的动态方面的基本属性,例如交通规划,生产和分配系统,通信系统,疏散计划等。在所有这些情况下,时间是一个基本组成部分,因为流量需要时间从一个位置传递到另一个位置,或者因为网络的结构随时间而变化。因此,动态流模型似乎适合捕获和描述不同的现实生命动态问题,例如网络结构改变时间或及时的决策,但是,由于他们的复杂性,这些模型并没有像那些一样彻底调查古典流动。这篇文章呈现并解决了参数动态网络中的最小流量的问题。所提出的方法包括在通过扩展原始动态网络获得的降低的消费网络中应用参数流算法。还提出了一个数字示例以更好地理解使用的方法。参数网络中流动的问题将最佳流的经典问题扩展到某种特殊类型的网络,其中某些弧的容量不是常数,而是取决于几个参数。因此,这些问题由求解参数值的某些子间隔内的所有参数值的一系列普通(非参数)最佳流量问题。虽然经典网络流模型已被广泛用作许多应用的宝贵工具[1],但它们未能捕获许多现实问题的动态方面的基本属性,例如交通规划,生产和分配系统,通信系统,疏散计划等。在所有这些情况下,时间是一个基本组成部分,因为流量需要时间从一个位置传递到另一个位置,或者因为网络的结构随时间而变化。因此,动态流模型似乎适合捕获和描述不同的现实生命动态问题,例如网络结构改变时间或及时的决策,但是,由于他们的复杂性,这些模型并没有像那些一样彻底调查古典流动。这篇文章呈现并解决了参数动态网络中的最小流量的问题。所提出的方法包括在通过扩展原始动态网络获得的降低的消费网络中应用参数流算法。还提出了一个数字示例以更好地理解使用的方法。

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