Optimization Research on Mixed-Model Multi-manned Assembly Line Balancing Problem of Type I

Owing to the incapability of the traditional approaches in solving the mixed-model multi-manned assembly line balancing problem of type I (MMALBP-I), a new mixed integer mathematical model is built to minimize the number of stations/workers and to balance the load between stations by introduce new variants and unequal constraints. What’s more, a modified chicken swarm optimization is also proposed. The algorithm adopts a priority-based coding and in decoding procedure, a worker which the assigned task can start earlier is being selected to reduce the sequence-dependent idle time, and the number of workers is decided by the designed station assignment rules to rude the mean station idle time. Moreover, in order to achieve more systematic and efficient search, the chicken swarm is divided into three groups according to the fitness values of the chickens themselves. The roosters generate new solution by a local search in different range of places based on the fitness value, the hens follow their group-mate roosters or other chickens to search a new solution based on the fitness value, the chicks move around their mother hens to update themselves. The proposed approaches are applied to solve the standard test instances. The results show that compared with the old model, the optimal results of eight more instances are found in the new mode in less time. The performance of the three evaluation indicators obtained using the proposed algorithm are improved by 10.74%, 16.05%, 44.89%, respectively, within the approximate time. Thus, above results verify the effectiveness and superiority of the proposed model and algorithm.