A fast and effective heuristic for smoothing workloads on assembly lines: algorithm design and experimental analysis

Workload smoothing on assembly lines, which aims to evenly assign tasks to stations, supports workforce planning and resource optimization. In this paper, we study smoothing assembly lines and develop a problem-specific heuristic to efficiently solve large-sized instances. To build solutions, the algorithm uses a number of well-known priority rules for task assignment in conjunction with a probabilistic decision-making procedure for closing workstations. We conduct an experimental design for selecting the best performing priority rules and for tuning the probabilistic decision-making procedure. The efficiency of our algorithm is tested and demonstrated through an extensive experimental study. (C) 2019 Elsevier Ltd. All rights reserved.