Abstract
Variable-size batching method has a higher possibility to obtain the most flexible scheduling schemes, which can be better applied to the manufacturing process. However, changing the sizes and number of sublots will not only increase the energy consumption of the manufacturing process, but also increase the search space of the scheduling schemes. A multi-objective optimization problem is formulated considering the makespan and total energy consumption simultaneously. Then, a two-stage multi-objective hybrid algorithm (HICSA) combining imperialist competitive algorithm (ICA) and simulated annealing algorithm (SAA) is proposed to solve this problem and improve the searching efficiency. The ICA and SAA are used to search for the suitable job sequences with optimal machine assignment and the optimal lot splitting schemes in the two stages, respectively. In order to improve the search efficiency, a novel mapping strategy that turns the discrete space into continuous space is applied. Extensive experiments are conducted and the computational results show that HICSA provides promising results for the problem.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call