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This article will discuss the effect of performance variables in achieving optimal solution in single machine scheduling problem. First of all, To determine whether genetic algorithm solution is optimal, optimal solution values for different job size will be obtained by mathematical model. In this model, Primary performance measure is Tmax, while secondary performance measure is the number of tardy jobs (nt) and total tardiness (TT) values. Genetic algorithm performance variables are crossover and mutation ratio, generation and population size. However other variables are job size, strategies of scheduling. We will utilize statistical methods to understand the effect of performance variables. Application study is to schedule the bottleneck machine for a company in the textile industry.
International Conference on Advanced Technologies, Computer Engineering and Science
ICATCES
Tugba Tunacan
S. Büşra ORTOĞLU