Mass personalization-oriented integrated optimization of production task splitting and scheduling in a multi-stage flexible assembly shop

Aiming to produce personalized products at mass production efficiency, mass personalization has attained considerable interests in recent years. This paper considers an integrated task splitting and scheduling problem in the context of mass personalization, which converts customer requirements into a few production tasks at different levels and simultaneously optimizes the sizes as well as the scheduling sequence of the tasks. An in-tegrated optimization model for this problem is formulated to minimize makespan and two transfer strategies for the model are investigated. To solve the model, an improved whale optimization algorithm (IWOA) is proposed, where a first-whale search is designed to guide the search direction. Besides, an ocean current impact factor and differential evolution operators are combined in IWOA to enhance the search ability. Extensive computational experiments are performed to validate the proposed algorithm. Results show that compared with the comparison algorithms, IWOA can find the best solution and take relatively less time. Furthermore, statistical analysis proves that the results of multiple runs of IWOA are more concentrated, indicative of better stability of IWOA. Finally, a case study is presented in the paper to demonstrate the application of the proposed model and algorithm.

Automated summary

This paper investigates the problem of task splitting and scheduling in mass personalization, proposing an optimization model and an improved whale optimization algorithm (IWOA). Extensive experiments validate the effectiveness and stability of the algorithm.