An adaptive BPSO algorithm for multi-skilled workers assignment problem in aircraft assembly lines

Abstract

Purpose – The purpose of this paper is to investigate the multi-skilled workers assignment problem in complex assembly systems such as aircraft assembly lines. An adaptive binary particle swarm optimization (A-BPSO) algorithm is proposed, which is used to balance the workload of both assembly stations and processes and to minimize the human cost. Design/methodology/approach – Firstly, a cycle time model considering the cooperation of multi-skilled workers is constructed. This model provides a quantitative description of the relationship between the cycle time and multi-skilled workers by means of revising the standard learning curve with the “Partition-And-Accumulate” method. Then, to improve the accuracy and stability of the current heuristic algorithms, an A-BPSO algorithm that suits for the discrete optimization problems is proposed to assign multi-skilled workers to assembly stations and processes based on modified sigmoid limiting function. Findings – The proposed method has been successfully applied to a practical case, and the result justifies its advantage as well as adaptability to both theory and engineering application. Originality/value – A novel cycle time model considering cooperation of multi-skilled workers is constructed so that the calculation results of cycle time are more accurate and closer to reality. An A-BPSO algorithm is proposed to improve the stability and convergence in dealing with the problems with higher dimensional search space. This research can be used by the project managers and dispatchers on assembly field.