A quantum‐inspired cuckoo co‐evolutionary algorithm for no‐wait flow shop scheduling
Abstract No‐wait flow shop scheduling problems (NWFSPs) are widespread in practical applications. The authors propose a quantum‐inspired cuckoo co‐evolutionary algorithm for the NWFSP to minimize the makespan. There are three algorithm components: quantum solution construction, quantum population ev...
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Format: | Article |
Language: | English |
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Wiley
2021-06-01
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Series: | IET Collaborative Intelligent Manufacturing |
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Online Access: | https://doi.org/10.1049/cim2.12002 |
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author | Haihong Zhu Ning Luo Xiaoping Li |
author_facet | Haihong Zhu Ning Luo Xiaoping Li |
author_sort | Haihong Zhu |
collection | DOAJ |
description | Abstract No‐wait flow shop scheduling problems (NWFSPs) are widespread in practical applications. The authors propose a quantum‐inspired cuckoo co‐evolutionary algorithm for the NWFSP to minimize the makespan. There are three algorithm components: quantum solution construction, quantum population evolution, and an improved neighbourhood local search. They generate initial solutions, search solutions, and improve solution qualities, respectively. Parameters of the proposed algorithm are calibrated statistically. The proposal with calibrated parameters is compared with three existing algorithms on Reeves and Taillard benchmark instances with middle scales. Experimental results show that the proposal outperforms the compared algorithms. |
first_indexed | 2024-04-11T18:59:03Z |
format | Article |
id | doaj.art-ed157ed78d6b49a3bb861c55fefeda3f |
institution | Directory Open Access Journal |
issn | 2516-8398 |
language | English |
last_indexed | 2024-04-11T18:59:03Z |
publishDate | 2021-06-01 |
publisher | Wiley |
record_format | Article |
series | IET Collaborative Intelligent Manufacturing |
spelling | doaj.art-ed157ed78d6b49a3bb861c55fefeda3f2022-12-22T04:08:07ZengWileyIET Collaborative Intelligent Manufacturing2516-83982021-06-013210511810.1049/cim2.12002A quantum‐inspired cuckoo co‐evolutionary algorithm for no‐wait flow shop schedulingHaihong Zhu0Ning Luo1Xiaoping Li2School of Cyber Science and Engineering Southeast University Nanjing211189 ChinaInstitute of Software Chinese Academy of Sciences Beijing100190 ChinaSchool of Computer Science and Engineering Southeast University Nanjing211189 ChinaAbstract No‐wait flow shop scheduling problems (NWFSPs) are widespread in practical applications. The authors propose a quantum‐inspired cuckoo co‐evolutionary algorithm for the NWFSP to minimize the makespan. There are three algorithm components: quantum solution construction, quantum population evolution, and an improved neighbourhood local search. They generate initial solutions, search solutions, and improve solution qualities, respectively. Parameters of the proposed algorithm are calibrated statistically. The proposal with calibrated parameters is compared with three existing algorithms on Reeves and Taillard benchmark instances with middle scales. Experimental results show that the proposal outperforms the compared algorithms.https://doi.org/10.1049/cim2.12002evolutionary computationflow shop schedulingsearch problems |
spellingShingle | Haihong Zhu Ning Luo Xiaoping Li A quantum‐inspired cuckoo co‐evolutionary algorithm for no‐wait flow shop scheduling IET Collaborative Intelligent Manufacturing evolutionary computation flow shop scheduling search problems |
title | A quantum‐inspired cuckoo co‐evolutionary algorithm for no‐wait flow shop scheduling |
title_full | A quantum‐inspired cuckoo co‐evolutionary algorithm for no‐wait flow shop scheduling |
title_fullStr | A quantum‐inspired cuckoo co‐evolutionary algorithm for no‐wait flow shop scheduling |
title_full_unstemmed | A quantum‐inspired cuckoo co‐evolutionary algorithm for no‐wait flow shop scheduling |
title_short | A quantum‐inspired cuckoo co‐evolutionary algorithm for no‐wait flow shop scheduling |
title_sort | quantum inspired cuckoo co evolutionary algorithm for no wait flow shop scheduling |
topic | evolutionary computation flow shop scheduling search problems |
url | https://doi.org/10.1049/cim2.12002 |
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