Solving the unrelated parallel machine scheduling problem with sequence-dependent setup times using a hybrid firefly algorithm

This study addresses the unrelated parallel machine scheduling problem with sequence-dependent setup times. A hybrid approach was developed, combining the firefly algorithm with the mutation, selection, and crossover operators of the genetic algorithm. Additionally, solution quality was enhanced using a variable neighborhood search algorithm. Test data were generated using a Python-based data production program, and the hybrid algorithm was implemented in MATLAB. For small data sets, solutions from a GAMS-coded mathematical model were compared to those from simulated annealing, genetic algorithm, and firefly algorithm for larger data sets. Results indicate the hybrid firefly algorithm is effective in solving the scheduling problem. The developed algorithm was applied to a real-life scenario using data from a factory in the Kayseri Organized Industrial Zone. When compared with the company's current situation, it was found to improve production by time saves planning efficiency by 12.77%.