Satisfaction-Driven Bi-Objective Multi-Skill Workforce Scheduling Problem

Abstract

with the global disappearance of the demographic dividend and the Industry 4.0, the workforce related to the manufacturing processes is increasingly important. Most existing works considering the workforce scheduling usually assume that the workers can be treated as specific machines and one machine is operated by one worker. However, in various practical manufacturing processes, the number workers available to run the machines is less than that of machines. Besides, worker's cooperation may be required to switch consecutive jobs on a machine, i.e., the setup tasks. Therefore, this paper investigates a satisfaction-driven bi-objective workforce scheduling problem, in which the workers process different skills to operate the available parallel machines. The workforce satisfaction and the number of on-time job (i.e., service level) are maximized simultaneously. For the problem, a bi-objective mixed integer programming (MIP) formulation is first proposed. To obtain the Pareto solutions, epsilon-constraint method is applied. A case study is conducted and analyzed to evaluate the applicability of the proposed model.