EFFICIENCY ANALYSIS OF THE HYBRID CAT SWARM OPTIMIZATION AND GENETIC ALGORITHM WITH SIMULATED ANNEALING IMPROVEMENT IN FLOW SHOP SCHEDULING

ABSTRACT: The article investigates a common production scheduling problem, namely the Flow Shop, with two hybrid metaheuristics. During the Flow Shop Scheduling, the numbers of jobs and machines are given in advance. Each job must go through each machine. The problem is to determine the job order such that the makespan is minimized. The two applied metaheuristic algorithms are Hybrid Cat Swarm Optimization and Hybrid Genetic Algorithm. The article hybridizes these two algorithms with the Simulated Annealing. The efficiency of the algorithms was validated on the Taillard benchmark dataset, where a few percent deviations from the best known values were observed.