A combinatorial Benders decomposition algorithm for parallel machine scheduling with working-time restrictions

This paper addresses a parallel machine scheduling problem with restrictions on employees' workingtimes and break times. Tasks must be processed by employees nonpreemptively on unrelated parallel machines with different thresholds that specify for each employee the maximum total and consecutive working-time, and the minimum break time. The objective is to minimize the weighted sum of the makespan, the machine depreciation costs, and the labor costs. To solve this problem, a mixed integer linear programming model is formulated, and two different decomposition-based exact algorithms are implemented as well as a list scheduling (LS)-based heuristic method. Extensive computational experiments are performed on randomly generated instances, and the results demonstrate the efficiency of our proposed combinatorial Benders decomposition approach. (C) 2020 Elsevier B.V. All rights reserved.

Automated summary

This paper addresses a parallel machine scheduling problem considering restrictions on employees' working times and break times. The authors propose a mixed integer linear programming model, two decomposition-based exact algorithms, and a list scheduling-based heuristic method to solve the problem efficiently. Extensive computational experiments demonstrate the effectiveness of the proposed combinatorial Benders decomposition approach.