A hybrid metaheuristic algorithm to achieve sustainable production: involving employee characteristics in the job-shop matching problem

Sustainable production is proposed to guide manufacturers in achieving sustainable development goals. Although previous studies have developed diverse metaheuristics algorithms in finding the optimal method for balancing economic and environmental aspects, the social aspect is still omitted. In addressing this shortcoming, this study attempts to design a hybrid metaheuristic algorithm to balance economic performance with social expectations by matching the employees' characteristics with those of a job shop. This study contributes to (1) confirming the importance of considering the social aspect for strengthening the theoretical basis; (2) proposing a hybrid metaheuristic algorithm in matching employees' characteristics with the job shop; and (3) utilizing the optimal scenario leads the related firms in practicing sustainable production. The findings indicate that matching the employee-job-shop can fulfill the social expectation for generating positive effects on economic performance. If manufacturers insist on lowering labor costs, it may have a negative impact on production efficiency.