Mapping combinatorial optimization problems onto neural networks

Document Type

Article

Publication Date

1-1-1995

Abstract

Neural networks have been proposed as a model of computation for solving a wide variety of problems in fields as diverse as combinatorial optimization, vision, and pattern recognition. The ability to map and solve a number of interesting problems on neural networks motivates a proposal for using neural networks as a highly parallel model for general-purpose computing. We review this proposal, and show how to map a number of interesting combinatorial optimization problems from graph theory, VLSI placement, and operations research. © 1995.

Publication Source (Journal or Book title)

Information Sciences

First Page

239

Last Page

255

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