Research on flexible job shop scheduling with low-carbon technology based on quantum bacterial foraging optimization

Abstract In order to further reduce the carbon emission of manufacturing process in flexible job shop, a multi-objective integrated optimization model job-shop scheduling (FJSP) is proposed. A mathematics built this paper minimize makespan, total workload machines and emissions optimize method each machine characteristic, sequence allocation. Considering many parameters are interactional be optimized proposed model, quantum bacterial foraging designed code related parameters. On basis Kacem example through experimental simulation, performance was analysed with ANOVA, by comparing algorithms current separated planning scheduling, effect on reducing practical requirements FJSP verified.