As employee cost rises,collaborative robots are increasingly utilized in assembly lines to either work alone or assist employees to complete the assembly tasks.Aiming at the man-robot cooperative assembly line balancing problem,a mixed integer programming model to optimize the cycle time was established.This formulated model was capable of solving the small-size instances optimally.Meanwhile,an enhanced artificial bee colony algorithm was developed to solve the large-size instances.The algorithm utilized two-layer encoding method of task permutation vector and robot assignment vector and one effective decoding procedure to achieve a feasible solution.The superior individuals in improved employed bee phase was preserved,and the performance of the new solution was developed in improved scout bee phase,thus the exploitation capacity of this algorithm was enhanced in local search phase.To evaluate the performance of the proposed method,it was compared with original artificial bee colony algorithm,late acceptance hill-climbing algorithm,simulated annealing algorithm,genetic algorithm,discrete particle swarm opti-mization algorithm and migrating birds optimization algorithm.The computational test demonstrated that the pro-posed method outperformed the compared methods and was capable of solving the man-robot cooperative assembly line balancing problem effectively.
assembly line balancingman-robot collaborationartificial bee colony algorithmintelligent optimization algorithm
万方数据
维普
