Scheduling part-time and mixed-skilled workers to maximize employee satisfaction

In this paper, part-time and mixed-skilled workers scheduling problem have been modeled in which workers' productivity is variable during a day. This paper considers fatigue as a significant human aspect in staff scheduling problem. Considering the effect of fatigue in staff scheduling problem is motivated by human operators who experience fatigue in carrying out tasks in various shifts. The model tries to maximize workers' satisfaction while regarding workers' availability, productivity, priority preference, seniority level, and number of workers required. To solve such an NP-hard problem, simulated annealing (SA) and variable neighborhood search (VNS) have been introduced. In order to improve the efficiency of proposed algorithms, "time of switching NSSs" is applied as a control parameter. To evaluate validity of the algorithms, efficient lower bound has been provided using a heuristic method. Comparison experiments show that our algorithms are capable of finding near-global optimum solution. Competitiveness of proposed algorithms has been evaluated through solutions of mathematical integer programming. The comparison results indicate that performance of VNS is better than performance of SA in terms of solution quality and computational time.