Kai Zhou GaoPonnuthurai Nagaratnam SuganthanMehmet Fatih TasgetirenQuan Ke PanQiang Qiang Sun2025-10-0620150360-835210.1016/j.cie.2015.09.005http://dx.doi.org/10.1016/j.cie.2015.09.005https://gcris.yasar.edu.tr/handle/123456789/7778This study investigates the flexible job shop scheduling problem (FJSP) with new job insertion. FJSP with new job insertion includes two phases: initializing schedules and rescheduling after each new job insertion. Initializing schedules is the standard FJSP problem while rescheduling is an FJSP with different job start time and different machine start time. The time to do rescheduling is the same as the time of new job insertion. Four ensembles of heuristics are proposed for scheduling FJSP with new job insertion. The objectives are to minimize maximum completion time (makespan) to minimize the average of earliness and tardiness (E/T) to minimize maximum machine workload (Mworkload) and total machine workload (Tworldoad). Extensive computational experiments are carried out on eight real instances from remanufacturing enterprise. The results and comparisons show the effectiveness of the proposed heuristics for solving FJSP with new job insertion. (C) 2015 Elsevier Ltd. All rights reserved.EnglishFlexible job shop scheduling, Ensemble, Heuristic, New job insertion, Multiple objectivesRANDOM MACHINE BREAKDOWNS, DISTRIBUTION ALGORITHM, GENETIC ALGORITHM, ROBUST, TIMEArticle