Kai Zhou GaoPonnuthurai Nagaratnam SuganthanQuan Ke PanMehmet Fatih TasgetirenAli Sadollah2025-10-0620160950-705110.1016/j.knosys.2016.06.014http://dx.doi.org/10.1016/j.knosys.2016.06.014https://gcris.yasar.edu.tr/handle/123456789/7848This study addresses flexible job shop scheduling problem (FJSP) with two constraints namely fuzzy processing time and new job insertion. The uncertainty of processing time and new job insertion are two scheduling related characteristics in remanufacturing. Fuzzy processing time is used to describe the uncertainty in processing time. Rescheduling operator is executed when new job(s) is (are) inserted into the schedule currently being executed. A two-stage artificial bee colony (TABC) algorithm with several improvements is proposed to solve FJSP with fuzzy processing time and new job insertion constraints. Also several new solution generation methods and improvement strategies are proposed and compared with each other. The objective is to minimize maximum fuzzy completion time. Eight instances from remanufacturing are solved using the proposed TABC algorithm. The proposed improvement strategies are compared and discussed in detail. Two proposed ABC algorithms with the best performances are compared against seven existing algorithms over by five benchmark cases. The optimization results and comparisons show the competitiveness of the proposed TABC algorithm for solving FJSP. (C) 2016 Elsevier B.V. All rights reserved.EnglishArtificial bee colony, Flexible job shop scheduling, Fuzzy processing time, New job insertion, RemanufacturingPROCESSING TIME, GENETIC ALGORITHM, SEARCH, OPTIMIZATIONArticle