Flexible worker allocation in aircraft final assembly line using multi-objective evolutionary algorithms

Abstract

In a paced aircraft final assembly line, some disturbances can be collected timely on the basis of the Cyber-Physical production system (CPPS). In order to reduce the execution deviation, some workers need to switch among stations after a fixed period. Thus, a worker allocation problem with the multi-stage workstation is introduced firstly. Then an integer programming formulation is presented to formulate the problem with the objective of shortest workstation cycle and the workload balance of both stations and workers. Moreover, a modified non-dominated sorting genetic algorithm (NSGA-IV) is proposed to solve it, which trades off the convergence and the population diversity in the decision space. Finally, the NSGA-IV algorithm compares with five multi-objective evolutionary algorithms (MOEA) in a real-world case. Compared to manual allocation, the takt time of an aircraft final assembly line is reduced by 20.86% by using the NSGA-IV algorithm.