Maximum Flow Distributing Algorithm under Restricted Capacity Condition at Transportation Network Sites
Zongping Li
Abstract
Zongping Li
Abstract
When the maximum flow distribution was carried out in a transportation network,the site under restricted capacity is usually to be divided into two sites.But in an enormous-complex transportation network,this method should make the network very large,in addition,the distributing maximum flow process will be more complicated.In this article,by analyzing the characteristics of these sites and based on the adjusting process of the add-flow-path,a distributing maximum flow algorithm is put forward in the paper.This optimization algorithm can solve the distributing maximum flow problem when more sites have the restricted capacity in an enormous-complex transportation network,and can be applied to the practical transportation problems.
OpenAlex reports 1 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
When the maximum flow distribution was carried out in a transportation network,the site under restricted capacity is usually to be divided into two sites.But in an enormous-complex transportation network,this method should make the network very large,in addition,the distributing maximum flow process will be more complicated.In this article,by analyzing the characteristics of these sites and based on the adjusting process of the add-flow-path,a distributing maximum flow algorithm is put forward in the paper.This optimization algorithm can solve the distributing maximum flow problem when more sites have the restricted capacity in an enormous-complex transportation network,and can be applied to the practical transportation problems.
Key concepts: Maximum flow problem, Flow network, Flow (mathematics), Process (computing), Path (computing), Minimum-cost flow problem, Out-of-kilter algorithm, Mathematical optimization