A Multi-Objective Cellular Memetic Optimization Algorithm for Green Scheduling in Flexible Job Shops

In the last 30 years, a flexible job shop scheduling problem (FJSP) has been extensively explored. Production efficiency is widely utilized objective. With rise in environmental awareness, green objectives (e.g., energy consumption) have received lot of attention. Nevertheless, consumption little Furthermore, controllable processing times (CPT) should be considered field scheduling, because they are closer to some real production. Therefore, this work investigates FJSP with CPT (i.e., FJSP-CPT) where asymmetrical conditions and symmetrical constraints increase difficulty solving. The FJSP-CPT minimize simultaneously maximum completion time makespan) total (TEC). First all, mathematical model multi-objective was formulated. To optimize problem, novel cellular memetic optimization algorithm (MOCMOA) presented. proposed MOMOA combined advantages structure for global exploration variable neighborhood search (VNS) local exploitation. At last, MOCMOA compared against other approaches by performing experiments. Numerical experiments reveal that presented superior its competitors 15 instances regarding three commonly used performance metrics.