Influence of Crossover Probability on Performance of Genetic Algorithm in Scheduling of Parallel Machines - Raghavendra, B. V.; Pai , Dayananda K. (Techniques and Innovation in Engineering Research and Technology Vol. 5, 2023)
In this chapter, an investigation of the influence of Crossover Probability on Genetic Algorithm (GA) performance for the bi-criteria objective function to obtain the best solution in a reasonable time in scheduling of parallel machines is studied. A heuristic model for reducing the workload imbalance on the machines considering work-in-process material is developed. The simulation on a proposed genetic algorithm was carried out with a crossover probability of 0.4 to 0.95 (with a step of 0.05) and 0.97, and it was discovered that the results were converging for the crossover probability of 0.6 with a computing time of 3.41 seconds. The suggested algorithm assists the decision maker in analysing the objective function with the computational time.