Iranian Journal of Information Science and Technology
Copyright © 2003 SHIRAZ REGIONAL LIBRARY OF SCIENCE AND TECHNOLOGY
Vol 1, No 1, ISSN 1726-8125, 2003
Computational
analysis of optimisation algorithms with artificial intelligence
A. Sadeghieh, Ph. DDepartment
of Industrial Engineering, University of Yazd, P. O. Box: 89195-741, YAZD, I. R. of Iran
Artificial intelligence is a way of making a computer
behave 'intelligently'. This can be accomplished by: studying how people think
when they are trying to make decisions and solve problems; breaking those
thought processes down into basic steps, and finally designing a computer
program that solves problems using those same steps. AI thereby
provides a simple, structured
approach to designing complex decision making programs. The goal of an AI
system is to analyse human behaviour in the fields of perception, comprehension
and decision making with the ultimate hope of reproducing the behaviour on a machine, namely a computer. One major category of AI
techniques is 'genetic algorithm'. Although it is recognised that the
performance of an evolutionary
system such as GA is affected by the parameters that are employed to implement
them, there is hardly any work known
to us that has shed much light on the
interdependencies and interactions between these parameters. Most
studies on the effects of these parameters on performance of GA-based systems
have focused on a parameter, at a
time, without considering the effect
of other parameters on that parameter and vice versa. Consequently, there is
hardly any theory about the interactions and interdependencies of these
parameters. This paper contributes towards correcting the situation mentioned
above by examining empirically the relationship between three parameters of GAs.
Keywords
- Linear Programming, Iterative
Methods, Genetic Algorithm, Transportation Problem, Integer Programming, Non-linear Programming,
Discrete Structures.