Title :
Varying quality function in genetic algorithms and the cutting problem
Author :
Petridis, V. ; Kazarlis, S.
Author_Institution :
Dept. of Electr. Eng., Thessaloniki Univ., Greece
Abstract :
In this paper, an implementation of a genetic algorithm (GA) is presented, using a quality function that is not unaltered but changes according to the search evolution. This means that the GA `sees´ a continuously changing search space, throughout one run. The example chosen to test the effect of a varying quality function is the cutting problem. Simulation results show that the dynamic quality function performs much better than its static counterpart
Keywords :
genetic algorithms; optimisation; search problems; continuously changing search space; cutting problem; dynamic quality function; genetic algorithms; search evolution; simulation results; Area measurement; Genetic algorithms; Genetic mutations; Needles; Shape measurement; Space exploration; Testing; Traveling salesman problems; Waste materials;
Conference_Titel :
Evolutionary Computation, 1994. IEEE World Congress on Computational Intelligence., Proceedings of the First IEEE Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-1899-4
DOI :
10.1109/ICEC.1994.350022
