Circuit partitioning using mean field annealing
Date
1995Source Title
Neurocomputing
Print ISSN
0925-2312
Electronic ISSN
1872-8286
Publisher
Elsevier
Volume
8
Issue
2
Pages
171 - 194
Language
English
Type
ArticleItem Usage Stats
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Abstract
Mean field annealing (MFA) algorithm, proposed for solving combinatorial optimization problems, combines the characteristics of neural networks and simulated annealing. Previous works on MFA resulted with successful mapping of the algorithm to some classic optimization problems such as traveling salesperson problem, scheduling problem, knapsack problem and graph partitioning problem. In this paper, MFA is formulated for the circuit partitioning problem using the so called net-cut model. Hence, the deficiencies of using the graph representation for electrical circuits are avoided. An efficient implementation scheme, which decreases the complexity of the proposed algorithm by asymptotical factors is also developed. Comparative performance analysis of the proposed algorithm with two wellknown heuristics, simulated annealing and Kernighan-Lin, indicates that MFA is a successful alternative heuristic for the circuit partitioning problem. © 1995.
Keywords
AlgorithmsCombinatorial Mathematics
Graph Theory
Heuristic Methods
Mathematical Models
Networks (Circuits)
Optimization
Performance
Simulated Annealing
Asymptotical Factors
Circuit Partitioning
Kernighan-Lin
Mean Field Annealing
Net-Cut Model
Neural networks
Article
Computer Model
Cost
Electric Activity
Mathematical Analysis
Mathematical Computing
Partition Coefficient
Priority Journal
Problem Solving
Theory