NDLI: Static Segregative Genetic Algorithm for Optimizing Variable Ordering of ROBDDs

Content Provider	IEEE Xplore Digital Library
Author	Brudaru, O. Rotaru, C. Furdu, I.
Copyright Year	2011
Abstract	This paper presents a segregative genetic algorithm for optimizing the variable order in Reduced Ordered Binary Decision Diagrams. The main components are a basic genetic algorithm and two feature functions used to measure the similarity between chromosomes. Many copies of the basic genetic algorithm explore in parallel subpopulations induced in the search space by clustering in the feature space. A communication protocol preserves the similarity within each subpopulation during the evolution process. An associative tabu search memory is used to avoid reexploration of the search space. Extensive experimental evaluation proves the efficiency and stability of the segregative approach, which systematically produces better results than the basic genetic algorithm. The efficiency of the distributed implementation in terms of resource usage and many aspects regarding the communication protocol between different components are thoroughly described. The experiments used classical benchmarks known as very difficult and show that the segregative variant is better than the monopopulation algorithm and the approach using the island model.
Starting Page	222
Ending Page	229
File Size	378181
Page Count	8
File Format	PDF
ISBN	9781467302074
DOI	10.1109/SYNASC.2011.54
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-09-26
Publisher Place	Romania
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Heuristic algorithms Data structures Vectors Biological cells extensive exploration Genetic algorithms similarity preserving communication Boolean functions Clustering algorithms distributed implementation associative tabu search segregative genetic algorithm intensive exploitation
Content Type	Text
Resource Type	Article

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