Akış Tipi Çizelgeleme Problemlerinin Genetik Algoritma Yardımı ile Çözümünde Uygun Çaprazlama Operatörünün Belirlenmesi

Abstract

In this study crossover operators of Genetic Algorithms are tested for flowshop scheduling problems which are in NP-hard class and the most effective operator is determined. Six crossover operators are tested on different scaled flowshop scheduling problems with long processing times. Problems are examined in two categories: 2 machine and multi machine problems. In 2-machine problems six different scaled problems were used which are produced randomly. For multi-machine problems seven different scaled reference problems were used which are produced by J. Carlier. The most effective crossover operators are determined for both categories according to the results of 2050 experiments.