A Competitive Memetic Algorithm for Carbon-Efficient Scheduling of Distributed Flow-Shop

Considering the energy conservation and emissions reduction, carbon-efficient scheduling becomes more and more important to the manufacturing industry. This paper addresses the multi-objective distributed permutation flow-shop scheduling problem (DPFSP) with makespan and total carbon emissions criteria (MODPFSP-Makespan-Carbon). Some properties to the problem are provided, and a competitive memetic algorithm (CMA) is proposed. In the CMA, some search operators compete with each other, and a local search procedure is embedded to enhance the exploitation. Meanwhile, the factory assignment adjustment is used for each job, and the speed adjustment is used to further improve the non-dominated solutions. To investigate the effect of parameter setting, full-factorial experiments are carried out. Moreover, numerical comparisons are given to demonstrate the effectiveness of the CMA.