Flexible Worker Allocation in Aircraft Final Assembly Line Using Multiobjective Evolutionary Algorithms

In a paced aircraft final assembly line, some disturbances can be collected timely on the basis of the cyber-physical production system. 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 multistage workstation is introduced first. 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 nondominated sorting genetic algorithm (NSGA-IV) is proposed to solve it, which tradeoff the convergence and the population diversity in the decision space. Finally, the NSGA-IV algorithm compares with five multiobjective evolutionary algorithms in a real-world case. Compared with manual allocation, the takt time of an aircraft final assembly line is reduced by 20.86% by using the NSGA-IV algorithm.