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On modeling genetic algorithms for functions of unitation

Content Provider	IEEE Xplore Digital Library
Author	Srinivas, M. Patnaik, L.M.
Copyright Year	1996
Abstract	We discuss a novel model for analyzing the working of Genetic Algorithms (GAs), when the objective function is a function of unitation. The model is exact (not approximate), and is valid for infinite populations. Functions of unitation depend only on the number of 1's in any string. Hence, we only need to model the variations in the distribution of strings with respect to the number of 1's in the strings. We introduce the notion of a Binomial Distributed Population (BDP) as the building block of our model, and we show that the effect of uniform crossover on BDPs is to generate two other BDPs. We demonstrate that a population with any general distribution may be decomposed into several BDPs. We also show that a general multipoint crossover may be considered as a composition of several uniform crossovers. Based on these results, the effects of mutation and crossover on the distribution of strings have been characterized, and the model has been defined. GASIM-a Genetic Algorithm Simulator for functions of unitation-has been implemented based on the model, and the exactness of the results obtained from GASIM has been verified using actual Genetic Algorithm runs. The time complexity of the GA simulator derived from the model is O(l/sup 3/) (where l is the string length), a significant improvement over previous models with exponential time complexities.
Starting Page	809
Ending Page	821
Page Count	13
File Size	1784583
File Format	PDF
ISSN	10834419
Volume Number	26
Issue Number	6
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1996-12-01
Publisher Place	U.S.A.
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Genetic algorithms Genetic mutations Algorithm design and analysis Robustness Sampling methods Encoding Microprocessors Laboratories
Content Type	Text
Resource Type	Article
Subject	Control and Systems Engineering Information Systems Electrical and Electronic Engineering Human-Computer Interaction Computer Science Applications Software

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