In this paper, we propose a saturation binary neuron model and use it to construct a Hopfield-type neural network called saturation binary neural network to solve the bipartite sub-graph problem. A large number of instances have been simulated to verify the proposed algorithm, with the simulation result showing that our algorithm finds the solution quality is superior to the compared algorithms.

3 Minimum cost network flow problem 5 3.1 Transportation problem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 3.2 The maximum flow problem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 3.3 The shortest path problem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 3.4 The single source shortest paths . . . . . . . . . . . . . . . . ...

Important features of networks, e.g., length of shortest paths, centrality, are defined in a graph theoretical way. Bipartite graphs are frequently applied, not only in computer science (e.g. PetriNets), but in other sciences as well. They are used to represent various problems, for example, in medicine or in economy. The relations between customers and products can be represented by bipartite ...

The GeneWeaver bipartite data model provides an efficient means to evaluate shared molecular components from sets derived across diverse species, disease states and biological processes. In order to adapt this model for examining related molecular components and biological networks, such as pathway or gene network data, we have developed a means to leverage the bipartite data structure to extra...

We propose to determine fundamental circuits of two matroids induced by certain bipartite graphs derived from the network equations in order to detect and locate inconsistencies in large electrical networks. Our method is easy to implement, is very fast, and does not rely on a specific form of network equations. It has been implemented in an industrial circuit simulator and, despite its simplic...

We describe a stochastic network interdiction model for locating sensors that detect nuclear material. A nuclear material smuggler selects a path through a transportation network that maximizes the probability of avoiding detection. An interdictor installs sensors to minimize that maximum probability. We formulate this problem as a bi-level stochastic mixed-integer program, and then focus on a ...

Firstly we make a pretreatment to the original gene data, and analyze the information of sample gene graph by two steps. First step is removing the unrelated genes; Second step is use an extraction algorithm of label gene based on bipartite network structure to handle the candidate gene, and get gene interactive relationship network. Finally extracts some label gene form the gene interactive re...