A Genetic Algorithm for the Dual Resource Constrained Flexible Job Shop Scheduling Problem Considering Preparation Times

A mathematical model is developed for the dual resource constrained flexible job-shop scheduling problem (DRCFJSP), considering worker proficiency and preparation times of jobs on machines with the objective of minimizing the maximum completion time. The model incorporates variations in worker skills and proficiency levels. To address the problem’s complexity, a genetic algorithm (GA) is employed for solution generation. Finally, comparative experiments are conducted using simulation scenarios, validating that integrating the impact of worker proficiency on preparation times into the scheduling model significantly optimizes total production completion time.