چکیده:
Artificial intelligence is a way of making a computcr behave 'intelligently'. This can be accomplished by: studying how people think when they are trying to make decisions and solve problcms; breaking those thought processes down into basic steps, and finally designing a computer program that srilvcs problems using those same steps. Al thereby provides a simple. structured approach i,o designing complex dccision making programs. Thc goal of an AI system is to analyse human behaviour in the fields of perception, comprehension and decision making with the iiltiiiiate hope o1“ reproducing the behaviour on a machine, namely a computer. One major category of” AI tcchniques is 'genetic algorithm'. Although it is recognised that the performance ot” an evolutionary system such as GA is at'fected 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 or”GA-based systems have focused on a parameter, at a time, without considering the c1”fect of other parameters on that parameter and vice versa. Consequently, there in 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.
خلاصه ماشینی:
This paper contributes towards correcting the situation mentioned above by examining empirically the relationship between three parameters of GAs. Ab8lfiitCl - Keywords - Linear Programming, Iterative Methods, Genetic Algorithm, , Transportation Problem, Integer Programming.
A 1 or 0 in thc string may, in a Boolean scheme, correspond to whether some condition is true or false, or bits may be strung together to form binary words that will be translated cithcr directly or indircctly into continuous valucd variables, as shown in Figures 1 and 2 respectively.
The proportion of bits coming from tllc best parent is dclincd by the user-defined crossover rate in the range zero to one, where a '1 in thc random bit string indicates that in that position the child inherits the corresponding bit from parent-1, whilst a '0' causes inhuritancc front parent-2.
MUTATION OPERATOR Until now, reproduction and crossover effectively search and rccoiribinc thc existing Iranian Journal of Information Science & Technology.
RASIC PARAMETERS OF A GENETIC ALGORITHM "I"he basic parameters of a GA include population size, crossover and the mutation rates.
I’m is paper introduces the application of Genetic Algorithms to Iranian Journal nf" Int'ormatinn Science & technology, Vnlume I, Numbcr I January / June, 2003 thc Minimum Sost Nlow Problem and the Transportntion Problem.
Genetic algorithms require that the natural parameter set of the optimisation problem be coded as a tinitc length string.
Thc basic parameters of a genetic algorithm are thc population size, the crossover ratc and the mutation rate.