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dc.contributor.authorJiang, Zengqiang
dc.contributor.authorZuo, Le
dc.contributor.authorE, Mingcheng
dc.date.accessioned2014-07-30T08:32:26Z
dc.date.available2014-07-30T08:32:26Z
dc.date.issued2014-07
dc.identifier.citationJiang, Zengqiang; Zuo, Le; E, Mingcheng. Study on multi-objective flexible job-shop scheduling problem considering energy consumption. "Journal of Industrial Engineering and Management", Juliol 2014, vol. 7, núm. 3, p. 589-604.
dc.identifier.issn2013-0953
dc.identifier.urihttp://hdl.handle.net/2099/15005
dc.description.abstractPurpose: Build a multi-objective Flexible Job-shop Scheduling Problem(FJSP) optimization model, in which the makespan, processing cost, energy consumption and cost-weighted processing quality are considered, then Design a Modified Non-dominated Sorting Genetic Algorithm (NSGA-II) based on blood variation for above scheduling model. Design/methodology/approach: A multi-objective optimization theory based on Pareto optimal method is used in carrying out the optimization model. NSGA-II is used to solve the model. Findings: By analyzing the research status and insufficiency of multi-objective FJSP, Find that the difference in scheduling will also have an effect on energy consumption in machining process and environmental emissions. Therefore, job-shop scheduling requires not only guaranteeing the processing quality, time and cost, but also optimizing operation plan of machines and minimizing energy consumption. Originality/value: A multi-objective FJSP optimization model is put forward, in which the makespan, processing cost, energy consumption and cost-weighted processing quality are considered. According to above model, Blood-Variation-based NSGA-II (BVNSGA-II) is designed. In which, the chromosome mutation rate is determined after calculating the blood relationship between two cross chromosomes, crossover and mutation strategy of NSGA-II is optimized and the prematurity of population is overcome. Finally, the performance of the proposed model and algorithm is evaluated through a case study, and the results proved the efficiency and feasibility of the proposed model and algorithm.
dc.format.extent16 p.
dc.language.isoeng
dc.publisherOmniaScience
dc.rightsAttribution-NonCommercial 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Matemàtiques i estadística::Investigació operativa::Optimització
dc.subject.lcshMathematical optimization
dc.subject.lcshComputer algorithms
dc.subject.otherMulti-objective scheduling
dc.subject.otherFlexible job-shop scheduling
dc.subject.otherNSGA-II
dc.subject.otherEnergy consumption
dc.subject.otherBlood variation
dc.titleStudy on multi-objective flexible job-shop scheduling problem considering energy consumption
dc.typeArticle
dc.subject.lemacOptimització matemàtica
dc.subject.lemacAlgorismes genètics
dc.identifier.dlB-28744-2008
dc.description.peerreviewedPeer Reviewed
dc.rights.accessOpen Access
local.citation.authorJiang, Zengqiang; Zuo, Le; E, Mingcheng
local.citation.publicationNameJournal of Industrial Engineering and Management
local.citation.volume7
local.citation.number3
local.citation.startingPage589
local.citation.endingPage604


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Except where otherwise noted, content on this work is licensed under a Creative Commons license : Attribution-NonCommercial 3.0 Spain