Comparison of the Effect of Various Types of Genetic Algorithm Operators on the Total Amount of Tardiness in Flow Shop Problem

Flow Shop Scheduling Problem (FSSP) with the objective of minimizing total amount of tardiness is an NP-hard problem and many articles has been written about it. In this context, great attention has been paide to metahuristic techniques such as genetic algorithm. Additionally determination of the paraemeters of the algorithms is an important subject in the research area that many researches have been allocated to it. The purpose of this paper is to investigate the effect of crossover and mutation operators of the genetic algorithm on the objective of minimizing total amount of tardiness in permutation FSSP in order to determine more suitable ones to be applied in the problem. The obtained numerical results indicate that in most cases among common crossover operators,using the one point and two point (first version) operators and among mutation operators,applying the adjacent exchange gives the best value for the mentioned problem.