Optimization of parallel machine scheduling problem with human resiliency engineering: A new hybrid meta-heuristics approach

This paper proposes a unique mixed integer programming model to solve non-identical parallel machines (NIPM) with sequence-dependent set-up times and human resiliency engineering. The presented mathematical model is formulated to consider human factors including Learning, Teamwork and Awareness. Moreover, processing time of jobs are assumed to be non-deterministic and dependent to their start time which leads to more precision and reality. The applicability of the proposed approach is demonstrated in a real world car accessories industrial unit. A hybrid metaheuristic method based on Genetic algorithm and simulated annealing is proposed to solve the problem. Parameter tuning is applied for adjustment of metaheuristic algorithm parameters. The superiority of the proposed hybrid metaheuristic method is evaluated by comparing the obtained results to GAMS, and two other hybrid metaheuristics. Moreover, it is shown that the hybrid approach provides better solutions than other hybrid approaches under uncertainty. This is the first study that presents a new hybrid approach for optimization of the stated problem by considering human resiliency.