Dual Resource Constrained Flexible Job-shop Scheduling Considering Worker Proficiency

The indicators of labor and green production have a crucial impact on the production efficiency and green development of a workshop.In this article,a highdimensional and multi-objective Dual Resource-constrained Flexible Job shop Scheduling Problem(DRCFJSP)model is established,targeting completion time,total machine load,labor cost,and total energy consumption,while considering both machine flexibility and labor flexibility as factors affecting workshop production.An improved multi-objective spider monkey optimization algorithm(MOSMO)is proposed for solving the high-dimensional and multi-objective DRCFJSP problem.The optimization objectives of the model not only consider the commonly used completion time indicator for workshop scheduling but also involve relevant indicators of green production,such as machine load,workshop energy consumption,and labor cost.Process sequence constraints,machine processing constraints,and worker operation constraints are set in the scheduling model to better conform to the production rules.In terms of the algorithm,a three-layer encoding method is adopted to simultaneously arrange workers,machines,and jobs to generate population encoding.The population crossover and mutation methods are redesigned based on the characteristics of the three-layer encoding.Multiple initialization rules are used for machine selection and process sorting to improve the quality of the initial population.The greedy insertion decoding method is used to calculate processing time,fully utilizing the processing gaps of workers and machines.The method of fast nondominated sorting and reference point-based selection operator are introduced to filter the population,ensuring sufficient selection pressure during population evolution.Three improved methods for generating neighboring solutions are introduced to enhance the algorithm’s local search capability and optimize the optimal solution set in each iteration.Finally,20 test cases with worker flexibility added were constructed based on the classical examples of workshop scheduling problems,and MOSMO was compared with other advanced algorithms.The effectiveness of MOSMO in handling the DRCFJSP problem was verified by calculating the IGD value and HV value of the final solution set.MOSMO was applied to an actual workshop production case and compared with a single-objective algorithm to demonstrate its ability to handle practical problems.The comparison of the optimal solution sets using the Attribute Hierarchy Model and Grey Relation Analysis method helps decision-makers choose scheduling solutions.