An exploration of the shift work consideration in production scheduling

Scheduling problems predominantly assume that the same operators work fixed shifts during the day and night. Scheduling with a single-shift approach can result in infeasible or suboptimal production planning solutions when a multiple-shift system is implemented. This study introduces a new scheduling extension that incorporates shift work constraints. A new mathematical model based on the Permutation Flowshop Scheduling Problem is proposed, and the Iterated Greedy algorithm is adapted to solve it. The objective is to minimize the maximum completion time (makespan) and thereby improve the system performance while considering shift work constraints. Experiments reveal that the overall response time in 10-hour and 12-hour shifts is better than that of 8-hour shifts, despite the shorter overall active hours on the shop floor. Additional experiments confirm that the proposed Adjusted Iterated Greedy algorithm outperforms the Variable Neighbourhood Search algorithm in solving medium- and large-scale problems.