Flexible job-shop rescheduling for new job insertion by using discrete Jaya algorithm
Rescheduling is a necessary procedure for a flexible job shop when newly arrived priority jobs must be inserted into an existing schedule. Instability measures the amount of change made to the existing schedule and is an important metrics to evaluate the quality of rescheduling solutions. This paper...
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sg-ntu-dr.10356-1399302020-08-21T00:58:18Z Flexible job-shop rescheduling for new job insertion by using discrete Jaya algorithm Gao, Kaizhou Yang, Fajun Zhou, MengChu Pan, Quanke Suganthan, Ponnuthurai Nagaratnam School of Electrical and Electronic Engineering Engineering::Electrical and electronic engineering Ensemble Instability Rescheduling is a necessary procedure for a flexible job shop when newly arrived priority jobs must be inserted into an existing schedule. Instability measures the amount of change made to the existing schedule and is an important metrics to evaluate the quality of rescheduling solutions. This paper focuses on a flexible job-shop rescheduling problem (FJRP) for new job insertion. First, it formulates FJRP for new job insertion arising from pump remanufacturing. This paper deals with bi-objective FJRPs to minimize: 1) instability and 2) one of the following indices: a) makespan; b) total flow time; c) machine workload; and d) total machine workload. Next, it discretizes a novel and simple metaheuristic, named Jaya, resulting in DJaya and improves it to solve FJRP. Two simple heuristics are employed to initialize high-quality solutions. Finally, it proposes five objective-oriented local search operators and four ensembles of them to improve the performance of DJaya. Finally, it performs experiments on seven real-life cases with different scales from pump remanufacturing and compares DJaya with some state-of-the-art algorithms. The results show that DJaya is effective and efficient for solving the concerned FJRPs. Accepted version This work was supported in part by the National Natural Science Foundation of China under Grant 61603169, Grant 61773192, and Grant 61503170, and in part by the Shandong Provincial Key Laboratory for Novel Distributed Computer Software Technology. 2020-05-22T08:58:08Z 2020-05-22T08:58:08Z 2018 Journal Article Gao, K., Yang, F., Zhou, M., Pan, Q., & Suganthan, P. N. (2019). Flexible job-shop rescheduling for new job insertion by using discrete Jaya algorithm. IEEE Transactions on Cybernetics, 49(5), 1944-1955. doi:10.1109/TCYB.2018.2817240 2168-2267 https://hdl.handle.net/10356/139930 10.1109/TCYB.2018.2817240 29993706 2-s2.0-85059046766 5 49 1944 1955 en IEEE Transactions on Cybernetics © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: https://doi.org/10.1109/TCYB.2018.2817240. application/pdf |
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Engineering::Electrical and electronic engineering Ensemble Instability Gao, Kaizhou Yang, Fajun Zhou, MengChu Pan, Quanke Suganthan, Ponnuthurai Nagaratnam Flexible job-shop rescheduling for new job insertion by using discrete Jaya algorithm |
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Rescheduling is a necessary procedure for a flexible job shop when newly arrived priority jobs must be inserted into an existing schedule. Instability measures the amount of change made to the existing schedule and is an important metrics to evaluate the quality of rescheduling solutions. This paper focuses on a flexible job-shop rescheduling problem (FJRP) for new job insertion. First, it formulates FJRP for new job insertion arising from pump remanufacturing. This paper deals with bi-objective FJRPs to minimize: 1) instability and 2) one of the following indices: a) makespan; b) total flow time; c) machine workload; and d) total machine workload. Next, it discretizes a novel and simple metaheuristic, named Jaya, resulting in DJaya and improves it to solve FJRP. Two simple heuristics are employed to initialize high-quality solutions. Finally, it proposes five objective-oriented local search operators and four ensembles of them to improve the performance of DJaya. Finally, it performs experiments on seven real-life cases with different scales from pump remanufacturing and compares DJaya with some state-of-the-art algorithms. The results show that DJaya is effective and efficient for solving the concerned FJRPs. |
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School of Electrical and Electronic Engineering |
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School of Electrical and Electronic Engineering Gao, Kaizhou Yang, Fajun Zhou, MengChu Pan, Quanke Suganthan, Ponnuthurai Nagaratnam |
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Article |
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Gao, Kaizhou Yang, Fajun Zhou, MengChu Pan, Quanke Suganthan, Ponnuthurai Nagaratnam |
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Gao, Kaizhou |
title |
Flexible job-shop rescheduling for new job insertion by using discrete Jaya algorithm |
title_short |
Flexible job-shop rescheduling for new job insertion by using discrete Jaya algorithm |
title_full |
Flexible job-shop rescheduling for new job insertion by using discrete Jaya algorithm |
title_fullStr |
Flexible job-shop rescheduling for new job insertion by using discrete Jaya algorithm |
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Flexible job-shop rescheduling for new job insertion by using discrete Jaya algorithm |
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flexible job-shop rescheduling for new job insertion by using discrete jaya algorithm |
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2020 |
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https://hdl.handle.net/10356/139930 |
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