Effective ensembles of heuristics for scheduling flexible job shop problem with new job insertion
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Date
2015
Authors
Kai Zhou Gao
Ponnuthurai Nagaratnam Suganthan
Mehmet Fatih Tasgetiren
Quan Ke Pan
Qiang Qiang Sun
Journal Title
Journal ISSN
Volume Title
Publisher
PERGAMON-ELSEVIER SCIENCE LTD
Open Access Color
Green Open Access
Yes
OpenAIRE Downloads
OpenAIRE Views
Publicly Funded
No
Abstract
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 (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.
Description
Keywords
Flexible job shop scheduling, Ensemble, Heuristic, New job insertion, Multiple objectives, RANDOM MACHINE BREAKDOWNS, DISTRIBUTION ALGORITHM, GENETIC ALGORITHM, ROBUST, TIME
Fields of Science
0211 other engineering and technologies, 02 engineering and technology
Citation
WoS Q
Scopus Q

OpenCitations Citation Count
63
Source
Computers & Industrial Engineering
Volume
90
Issue
Start Page
107
End Page
117
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Citations
CrossRef : 19
Scopus : 76
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