{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,9]],"date-time":"2025-12-09T11:40:58Z","timestamp":1765280458495,"version":"3.38.0"},"reference-count":51,"publisher":"Tech Science Press","issue":"1","license":[{"start":{"date-parts":[[2024,10,20]],"date-time":"2024-10-20T00:00:00Z","timestamp":1729382400000},"content-version":"vor","delay-in-days":293,"URL":"https:\/\/doi.org\/10.32604\/TSP-CROSSMARKPOLICY"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["CMC"],"published-print":{"date-parts":[[2024]]},"DOI":"10.32604\/cmc.2024.055574","type":"journal-article","created":{"date-parts":[[2024,10,15]],"date-time":"2024-10-15T07:13:21Z","timestamp":1728976401000},"page":"1757-1787","update-policy":"https:\/\/doi.org\/10.32604\/tsp-crossmarkpolicy","source":"Crossref","is-referenced-by-count":1,"title":["A Discrete Multi-Objective Squirrel Search Algorithm for Energy-Efficient Distributed Heterogeneous Permutation Flowshop with Variable Processing Speed"],"prefix":"10.32604","volume":"81","author":[{"given":"Liang","family":"Zeng","sequence":"first","affiliation":[]},{"given":"Ziyang","family":"Ding","sequence":"additional","affiliation":[]},{"given":"Junyang","family":"Shi","sequence":"additional","affiliation":[]},{"given":"Shanshan","family":"Wang","sequence":"additional","affiliation":[]}],"member":"17807","published-online":{"date-parts":[[2024]]},"reference":[{"key":"ref1","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1002\/nav.3800010110","article-title":"Optimal two-and three-stage production schedules with setup times included","volume":"1","author":"Johnson","year":"1954","journal-title":"Nav. Res. Logist. Q."},{"key":"ref2","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1287\/moor.1.2.117","article-title":"The complexity of flowshop and jobshop scheduling","volume":"1","author":"Garey","year":"May 1976","journal-title":"Math. Oper. Res."},{"key":"ref3","first-page":"3031","article-title":"Flow-shop scheduling with transportation capacity and time consideration","volume":"70","author":"Wang","year":"2022","journal-title":"Comput. Mater. Contin."},{"key":"ref4","doi-asserted-by":"crossref","first-page":"364","DOI":"10.1016\/j.eswa.2005.04.009","article-title":"An adaptive genetic algorithm with dominated genes for distributed scheduling problems","volume":"29","author":"Chan","year":"2005","journal-title":"Expert Syst. Appl."},{"key":"ref5","doi-asserted-by":"crossref","first-page":"5235","DOI":"10.1080\/00207540903121065","article-title":"Distributed scheduling: A review of concepts and applications","volume":"48","author":"Toptal","year":"Sep. 2010","journal-title":"Int. J. Prod. Res."},{"key":"ref6","doi-asserted-by":"crossref","first-page":"754","DOI":"10.1016\/j.cor.2009.06.019","article-title":"The distributed permutation flowshop scheduling problem","volume":"37","author":"Naderi","year":"2010","journal-title":"Comput. Oper. Res."},{"key":"ref7","first-page":"497","article-title":"A hybrid genetic algorithm for the distributed permutation flowshop scheduling problem","volume":"4","author":"Gao","year":"2011","journal-title":"Int. J. Comput. Intell. Syst."},{"key":"ref8","doi-asserted-by":"crossref","first-page":"641","DOI":"10.1080\/00207543.2011.644819","article-title":"An efficient tabu search algorithm for the distributed permutation flowshop scheduling problem","volume":"51","author":"Gao","year":"2013","journal-title":"Int. J. Prod. Res."},{"key":"ref9","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1016\/j.asoc.2015.11.034","article-title":"Multi-objective adaptive large neighborhood search for distributed reentrant permutation flow shop scheduling","volume":"40","author":"Rifai","year":"2016","journal-title":"Appl. Soft Comput."},{"key":"ref10","doi-asserted-by":"crossref","first-page":"5029","DOI":"10.1080\/00207543.2013.790571","article-title":"Minimising makespan in distributed permutation flowshops using a modified iterated greedy algorithm","volume":"51","author":"Lin","year":"2013","journal-title":"Int. J. Prod. Res."},{"key":"ref11","doi-asserted-by":"crossref","first-page":"1344","DOI":"10.1109\/TASE.2018.2886303","article-title":"A pareto-based estimation of distribution algorithm for solving multiobjective distributed nowait flow-shop scheduling problem with sequence-dependent setup time","volume":"16","author":"Shao","year":"2019","journal-title":"IEEE Trans. Autom. Sci. Eng."},{"key":"ref12","doi-asserted-by":"crossref","DOI":"10.1016\/j.rcim.2021.102277","article-title":"A pareto-based collaborative multi-objective optimization algorithm for energy-efficient scheduling of distributed permutation flowshop with limited buffers","volume":"74","author":"Lu","year":"2022","journal-title":"Robot. Comput. Integr. Manuf."},{"key":"ref13","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2022.108471","article-title":"Jonrinaldi, an effective water wave optimization algorithm with problemspecific knowledge for the distributed assembly blocking flow-shop scheduling problem","volume":"243","author":"Zhao","year":"2022","journal-title":"Knowl.-Based Syst."},{"key":"ref14","doi-asserted-by":"crossref","first-page":"213","DOI":"10.1016\/j.omega.2018.03.004","article-title":"Iterated Greedy methods for the distributed permutation flowshop scheduling problem","volume":"83","author":"Ruiz","year":"2019","journal-title":"Omega"},{"key":"ref15","doi-asserted-by":"crossref","first-page":"239","DOI":"10.1016\/j.cie.2017.07.020","article-title":"A novel chemical reaction optimization for the distributed permutation flowshop scheduling problem with makespan criterion","volume":"111","author":"Bargaoui","year":"2017","journal-title":"Comput. Ind. Eng."},{"key":"ref16","doi-asserted-by":"crossref","first-page":"6922","DOI":"10.1080\/00207543.2019.1571687","article-title":"An improved artificial bee colony algorithm for addressing distributed flow shop with distance coefficient in a prefabricated system","volume":"57","author":"Li","year":"2019","journal-title":"Int. J. Prod. Res."},{"key":"ref17","doi-asserted-by":"crossref","first-page":"124","DOI":"10.1016\/j.swevo.2017.04.007","article-title":"A backtracking search hyper-heuristic for the distributed assembly flow-shop scheduling problem","volume":"36","author":"Lin","year":"2017","journal-title":"Swarm Evol. Comput."},{"key":"ref18","doi-asserted-by":"crossref","first-page":"866","DOI":"10.1016\/j.jclepro.2018.09.100","article-title":"Scheduling for sustainable manufacturing: A review","volume":"205","author":"Akbar","year":"2018","journal-title":"J. Clean.Prod."},{"key":"ref19","unstructured":"IEA, \u201cWorldwide trends in energy use and efficiency: Key insights from iea indicator analysis,\u201d 2008. Accessed: Aug. 11, 2024. [Online]. Available: http:\/\/sa.indiaenvironmentportal.org.in\/files\/Indicators_2008.pdf"},{"key":"ref20","doi-asserted-by":"crossref","first-page":"1805","DOI":"10.1109\/TSMC.2017.2788879","article-title":"A knowledge-based cooperative algorithm for energy-efficient scheduling of distributed flow-shop","volume":"50","author":"Wang","year":"2018","journal-title":"IEEE Trans. Syst., Man, Cybern.: Syst."},{"key":"ref21","doi-asserted-by":"crossref","DOI":"10.1016\/j.cie.2022.108126","article-title":"A cooperative memetic algorithm with feedback for the energy-aware distributed flow-shops with flexible assembly scheduling","volume":"168","author":"Wang","year":"2022","journal-title":"Comput. Ind. Eng."},{"key":"ref22","doi-asserted-by":"crossref","DOI":"10.1016\/j.asoc.2021.107526","article-title":"A green scheduling algorithm for the distributed flowshop problem","volume":"109","author":"Li","year":"2021","journal-title":"Appl. Soft Comput."},{"key":"ref23","doi-asserted-by":"crossref","first-page":"12675","DOI":"10.1109\/TCYB.2021.3086181","article-title":"A self-learning discrete jaya algorithm for multiobjective energy-efficient distributed no-idle flow-shop scheduling problem in heterogeneous factory system","volume":"52","author":"Zhao","year":"2022","journal-title":"IEEE Trans. Cybern."},{"key":"ref24","article-title":"Sustainable distributed permutation flow-shop scheduling model based on a triple bottom line concept","volume":"24","author":"Fathollahi-Fard","year":"2021","journal-title":"J. Ind. Inf. Integr."},{"key":"ref25","doi-asserted-by":"crossref","DOI":"10.1016\/j.ress.2023.109143","article-title":"Integrated optimization of non-permutation flow shop scheduling and maintenance planning with variable processing speed","volume":"234","author":"Jiang","year":"2023","journal-title":"Reliab. Eng. Syst. Safety"},{"key":"ref26","doi-asserted-by":"crossref","first-page":"4805","DOI":"10.1007\/s40747-023-00984-x","article-title":"BRCE: bi-roles co-evolution for energy-efficient distributed heterogeneous permutation flow shop scheduling with flexible machine speed","volume":"9","author":"Huang","year":"2023","journal-title":"Complex Intelli. Syst"},{"key":"ref27","doi-asserted-by":"crossref","DOI":"10.1016\/j.swevo.2020.100716","article-title":"Energy-efficient distributed permutation flow shop scheduling problem using a multi-objective whale swarm algorithm","volume":"57","author":"Wang","year":"2020","journal-title":"Swarm Evol. Comput."},{"key":"ref28","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.ejor.2023.02.001","article-title":"A review and classification on distributed permutation flowshop scheduling problems","volume":"312","author":"Perez-Gonzalez","year":"2023","journal-title":"Eur. J. Oper. Res."},{"key":"ref29","doi-asserted-by":"crossref","first-page":"148","DOI":"10.1016\/j.swevo.2018.02.013","article-title":"A novel nature-inspired algorithm for optimization: Squirrel search algorithm","volume":"44","author":"Jain","year":"2019","journal-title":"Swarm Evol. Comput."},{"key":"ref30","doi-asserted-by":"crossref","DOI":"10.1155\/2019\/6291968","article-title":"An improved squirrel search algorithm for optimization","volume":"2019","author":"Zheng","year":"2019","journal-title":"Complexity"},{"key":"ref31","doi-asserted-by":"crossref","first-page":"118343","DOI":"10.1109\/ACCESS.2019.2936823","article-title":"An improved squirrel search algorithm for maximum likelihood DOA estimation and application for MEMS vector hydrophone array","volume":"7","author":"Wang","year":"2019","journal-title":"IEEE Access"},{"key":"ref32","doi-asserted-by":"crossref","first-page":"36019","DOI":"10.1109\/ACCESS.2021.3061058","article-title":"Advanced meta-heuristics, convolutional neural networks, and feature selectors for efficient COVID-19 X-ray chest image classification","volume":"9","author":"El-Kenawy","year":"2021","journal-title":"IEEE Access"},{"key":"ref33","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1007\/s12530-021-09366-5","article-title":"Multi-area economic environmental dispatch using multi-objective squirrel search algorithm","volume":"13","author":"Sakthivel","year":"2022","journal-title":"Evol. Syst."},{"key":"ref34","first-page":"1","article-title":"A FJSSP method based on dynamic multi-objective squirrel search algorithm","volume":"2021","author":"Wang","year":"2021","journal-title":"Int. J. Antennas Propag."},{"key":"ref35","doi-asserted-by":"crossref","first-page":"1815","DOI":"10.32604\/iasc.2022.021822","article-title":"Blockchain for securing healthcare data using squirrel search optimization algorithm","volume":"32","author":"Jaishankar","year":"2022","journal-title":"Intell. Autom. Soft Comput."},{"key":"ref36","doi-asserted-by":"crossref","first-page":"814","DOI":"10.1080\/15325008.2022.2141925","article-title":"Frequency control of a wind-diesel-generator hybrid system with squirrel search algorithm tuned robust cascade fractional order controller having disturbance observer integrated","volume":"50","author":"Guha","year":"2022","journal-title":"Elect. Power Compon. Syst."},{"key":"ref37","first-page":"6081","article-title":"Squirrel search optimization with deep convolutional neural network for human pose estimation","volume":"74","author":"Ishwarya","year":"2023","journal-title":"Comput. Mater. Contin."},{"key":"ref38","doi-asserted-by":"crossref","first-page":"13529","DOI":"10.1007\/s00521-023-08451-x","article-title":"Squirrel search algorithm applied to effective estimation of solar PV model parameters: A real-world practice","volume":"35","author":"Maden","year":"2023","journal-title":"Neural Comput. Appl."},{"key":"ref39","volume":"12689","author":"Wu","year":"2021","journal-title":"Advances in Swarm Intelligence."},{"key":"ref40","doi-asserted-by":"crossref","first-page":"3101","DOI":"10.1109\/TCYB.2022.3151855","article-title":"Multiobjective flexible job-shop rescheduling with new job insertion and machine preventive maintenance","volume":"53","author":"An","year":"May 2023","journal-title":"IEEE Transact Cybern"},{"key":"ref41","doi-asserted-by":"crossref","first-page":"279","DOI":"10.1007\/BF00992698","article-title":"Technical note: Q-learning","volume":"8","author":"Watkins","year":"1992","journal-title":"Mach. Learn."},{"key":"ref42","doi-asserted-by":"crossref","first-page":"101118","DOI":"10.1109\/ACCESS.2020.2998324","article-title":"An improved squirrel search algorithm with reproductive behavior","volume":"8","author":"Zhang","year":"2020","journal-title":"IEEE Access"},{"key":"ref43","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2022.117380","article-title":"A reinforcement learning based RMOEA\/D for bi-objective fuzzy flexible job shop scheduling","volume":"203","author":"Li","year":"2022","journal-title":"Expert Syst. Appl."},{"key":"ref44","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1109\/TEVC.2005.851275","article-title":"A faster algorithm for calculating hypervolume","volume":"10","author":"While","year":"2006","journal-title":"IEEE Trans. Evol. Comput."},{"key":"ref45","doi-asserted-by":"crossref","first-page":"1692","DOI":"10.1109\/TII.2016.2614659","article-title":"Auxiliary hybrid PSO-BPNN-based transmission system loss estimation in generation scheduling","volume":"13","author":"Jethmalani","year":"2017","journal-title":"IEEE Trans. Ind. Inform."},{"key":"ref46","doi-asserted-by":"crossref","first-page":"182","DOI":"10.1109\/4235.996017","article-title":"A fast and elitist multiobjective genetic algorithm: Nsga-ii","volume":"6","author":"Deb","year":"2002","journal-title":"IEEE Trans. Evol. Comput."},{"key":"ref47","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1198\/004017002320256440","article-title":"Design of experiments using the taguchi approach: 16 steps to product and process improvement","volume":"44","author":"Van","year":"2002","journal-title":"Technometrics"},{"key":"ref48","doi-asserted-by":"crossref","first-page":"712","DOI":"10.1109\/TEVC.2007.892759","article-title":"MOEA\/D: A multiobjective evolutionary algorithm based on decomposition","volume":"11","author":"Zhang","year":"2007","journal-title":"IEEE Trans. Evol. Comput."},{"key":"ref49","volume":"103","author":"Zitzler","year":"2001","journal-title":"TIK Report"},{"key":"ref50","doi-asserted-by":"crossref","first-page":"924","DOI":"10.1109\/TEVC.2016.2549267","article-title":"Stochastic ranking algorithm for many-objective optimization based on multiple indicators","volume":"20","author":"Li","year":"2016","journal-title":"IEEE Trans. Evol. Comput."},{"key":"ref51","doi-asserted-by":"crossref","first-page":"6222","DOI":"10.1109\/TSMC.2022.3143657","article-title":"A two-stage evolutionary algorithm with balanced convergence and diversity for many-objective optimization","volume":"52","author":"Ming","year":"2022","journal-title":"IEEE Trans. Syst., Man, Cybern.: Syst."}],"container-title":["Computers, Materials &amp; Continua"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.techscience.com\/files\/cmc\/2024\/TSP_CMC-81-1\/TSP_CMC_55574\/TSP_CMC_55574.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,3,7]],"date-time":"2025-03-07T02:40:43Z","timestamp":1741315243000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.techscience.com\/cmc\/v81n1\/58345"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"references-count":51,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2024]]},"published-print":{"date-parts":[[2024]]}},"URL":"https:\/\/doi.org\/10.32604\/cmc.2024.055574","relation":{},"ISSN":["1546-2226"],"issn-type":[{"type":"electronic","value":"1546-2226"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"2024-07-01","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2024-09-12","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2024-10-15","order":2,"name":"published","label":"Published Online","group":{"name":"publication_history","label":"Publication History"}}]}}