.png){kind=icon}
返回
Locating switches
.png){kind=icon}
PRE
AI
DOI：10.1016/j.eswa.2019.06.054.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
In this paper, a novel problem in transshipment networks has been proposed. The main aims of this paper are to introduce the problem and to give useful tools for solving it both in exact and approximate ways. In a transshipment network it is important to decide which are the best paths between each pair of nodes. Representing the network by a graph, the union of thesepaths is a delivery subgraph of the original graph which has all the nodes and some edges. Nodes in this subgraph which are adjacent to more than two nodes are called switches because when sending the flow between any pair of nodes, switches on the path must adequately direct it. Switches are facilities which direct flows among users. The installation of a switch involves the installation of adequate equipment and thus an allocation cost. Furthermore, traversing a switch also implies a service cost or allocation cost. The Switch Location Problem is defined as the problem of determining which is the delivery subgraph with the total lowest cost. Two of the three solutions approaches that we propose are decomposition algorithms based on articulation vertices, the exact and the math-heuristic ones. These two approaches could be embedded in expert systems for locating switches in transshipment networks. The results should help a decision maker to select the adequate approach depending on the shape and size of the network and also on the external time-limit. Our results show that the exact approach is a valuable tool if the network has less than 1000 nodes. Two upsides of our heuristics are that they do not require special networks and give good solutions, gap-wise. The impact of this paper is twofold: it highlights the difficulty of adequately locating switches and it emphasizes the benefit of decomposing algorithms. (C) 2019 Elsevier Ltd. All rights reserved.
Keyword:
Discrete location
Math-heuristic
Articulation vertex
Block-Cutpoint graph
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
7.5
论文数:
2.9W
被引数:
10.2W
机构
引用论文
A branch-and-cut algorithm for the minimum branch vertices spanning tree problem最小分支顶点生成树问题的分支-割算法
PREAI
分享收藏分享收藏Typhoons During the COVID-19 Pandemic in the Philippines: Impact of a Double Crises on Mental Health
OAAI
OAAI分享收藏A hybrid genetic algorithm for the degree-constrained minimum spanning tree problem.png)
SOFT COMPUTING
SOFT COMPUTINGIF2.5
PREAI
分享收藏A hybrid steady-state genetic algorithm for the min-degree constrained minimum spanning tree problem
PREAI
分享收藏
查看更多内容