Browsing by Author "Gao, Kai Zhou"

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Citation - WoS: 84
Citation - Scopus: 97
An effective discrete harmony search algorithm for flexible job shop scheduling problem with fuzzy processing time
(Taylor and Francis Ltd., 2015) Kaizhou Gao; Ponnuthurai Nagaratnam Suganthan; Quanke Pan; M. Fatih Tasgetiren; Suganthan, Ponnuthurai Nagaratnam; Tasgetiren, Mehmet Fatih; Gao, Kai Zhou; Pan, Quan Ke
This study addresses flexible job shop scheduling problem (FJSP) with fuzzy processing time. The fuzzy or uncertainty of processing time is one of seven characteristics in remanufacturing. A discrete harmony search (DHS) algorithm is proposed for FJSP with fuzzy processing time. The objective is to minimise maximum fuzzy completion time. A simple and effective heuristic rule is proposed to initialise harmony population. Extensive computational experiments are carried out using five benchmark cases with eight instances from remanufacturing. The proposed heuristic rule is evaluated using five benchmark cases. The proposed DHS algorithm is compared to six metaheuristics. The results and comparisons show the effectiveness and efficiency of DHS for solving FJSP with fuzzy processing time. © 2021 Elsevier B.V. All rights reserved.
Citation - WoS: 132
Citation - Scopus: 151
Artificial bee colony algorithm for scheduling and rescheduling fuzzy flexible job shop problem with new job insertion
(Elsevier B.V., 2016) Kaizhou Gao; Ponnuthurai Nagaratnam Suganthan; Quanke Pan; M. Fatih Tasgetiren; Ali Sadollah; Suganthan, Ponnuthurai Nagaratnam; Tasgetiren, Mehmet Fatih; Sadollah, Ali; Gao, Kai Zhou; Pan, Quan Ke
This 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. © 2017 Elsevier B.V. All rights reserved.
Citation - WoS: 64
Citation - Scopus: 76
Effective ensembles of heuristics for scheduling flexible job shop problem with new job insertion
(Elsevier Ltd, 2015) Kaizhou Gao; Ponnuthurai Nagaratnam Suganthan; M. Fatih Tasgetiren; Quanke Pan; Qiangqiang Sun; Suganthan, Ponnuthurai Nagaratnam; Tasgetiren, Mehmet Fatih; Sun, Qiang Qiang; Gao, Kai Zhou; Pan, Quan Ke
This 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 (Tworkload). 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. © 2015 Elsevier B.V. All rights reserved.