Network Maximum Flow Algorithm And Applied Research

The maximum flow problem is a classic combinatorial optimization problem is an important part of operations research and computer science,and in science and engineering fields have a very wide range of applications.At the same time many practical applications of linear programming can also be converted into the largest network flow problem,so the network maximum flow problem is also closely linear programming problem and graph theory problem,opening up new ways of graph theory applications.Along with power,logistics and the rapid development of large-scale network communications and computer hardware,software,processing power and technology continues to enhance and widely used,the need for research network maximum flow problem has become increasingly urgent.In the largest study of network flow problem in the process,many scholars and researchers who have proposed to solve the maximum flow problem many new methods or ideas and improve existing algorithm appropriately,and gradually establish a maximum flow problem solving more perfect theoretical system,and we have made a series of relatively complete maximum flow problem solving ideas,methods and algorithms.In this paper,the concept of time and space is added to the balance of maximum flow algorithm for solving the network,the use of storage space in exchange for the time it takes to run.Specific binding process is as follows:traverse the entire network map and diagram of all the nodes to parameterize and stratified operation,in which the node parameterization including the current node in the state but also the most flowing stream flow values and have flowing flow value.If a network diagram can not be stratified operation,it indicates that the network diagram is not connected graph is the largest in circulation can not be solved.Create one for the nodes plans are additional parameter information network graph model based on the above operation.According to the above network graph model,a node-based parameter information and an adjacent node network parameter information to solve the maximum flow problem of two algorithms.The main idea of the two algorithms is that the added extra memory space to store node parameter information,through the parameter information of the current node to judge or compare,according to the judgment result,selecting the nodes of the optimal operation mode and according to the comparison results of the node and the adjacent node next step operation.The first algorithm is based on the node information of the maximum flow algorithm,this algorithm parameter information through the junction to judge,but take different actions based on the judgment result of the node different.The second algorithm is the maximum flow algorithm based on adjacent node information,in this algorithm on the more when the node and its adjacent node information to compare the current node depending on the result of comparison and its adjacent nodes point to take relevant action.Both algorithms are specific applications of the concept of time and space balance.