Solving maximum independent set by asynchronous distributed hopfield-type neural networks
نویسندگان
چکیده
We propose a heuristic for solving the maximum independent set problem for a set of processors in a network with arbitrary topology. We assume an asynchronous model of computation and we use modified Hopfield neural networks to find high quality solutions. We analyze the algorithm in terms of the number of rounds necessary to find admissible solutions both in the worst case (theoretical analysis) and in the average case (experimental Analysis). We show that our heuristic is better than the greedy one at 1% significance level. Mathematics Subject Classification. 68W15, 90C59, 05C69.
منابع مشابه
Hopfield Neural Network with Hysteresis for Maximum Cut Problem
A model of neurons with hysteresis (or hysteresis binary neurons) for the Hopfield neural networks is studied. We prove theoretically that the emergent collective properties of the original Hopfield neural networks also are present in the Hopfield neural networks with hysteresis binary neurons. As an example, the networks are also applied to the maximum cut problem and results of computer simul...
متن کاملApplication of Discrete Hopfield-type Neural Network for Max-Cut Problems
In this paper, we discuss the convergence property of the discrete Hopfield-type neural network (DHNN) running in asynchronous mode. Then a DHNN with negative diagonal weight matrix is designed to solve the Max-Cut problem, which can approach good solutions.
متن کاملNonpositive Hopfield Neural Network with Self-Feedback and its Application to Maximum Clique Problems
A clique of an undirected graph G (V, E) with a vertex set V and an edge set E is a subset of V such that all pairs of vertices are connected by an edge in E. The maximum clique problem (MCP) is to find a clique of maximum size of the graph G. Figure 1(b) shows a maximum clique of the graph Figure 1(a) with 10 vertices and 21 edges. It is one of the first problems which have been proven to be N...
متن کاملThe Minimum Cost Path Finding Algorithm Using a Hopfield Type Neural Network
Recently neural networks have been ploposed as new computational tools for solving constrained optimization problems. In this paper the minimum cost path fmding algorithm is proposed by using a Hopfield type neural network. In order to design a Hopfield type neural network, an energy function must be defmed at f i t . To achieve thii, the concept of a vector-represented network is used to descr...
متن کاملExtended Hopfield models for combinatorial optimization
The extended Hopfield neural network proposed by Abe et al. for solving combinatorial optimization problems with equality and/or inequality constraints has the drawback of being frequently stabilized in states with neurons of ambiguous classification as active or inactive. We introduce in the model a competitive activation mechanism and we derive a new expression of the penalty energy allowing ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- ITA
دوره 40 شماره
صفحات -
تاریخ انتشار 2006