A hybrid method of 2-TSP and novel learning-based GA for job sequencing and tool switching problem

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dc.contributor.authorAhmadi, Ehsan
dc.contributor.authorSuer, Gursel
dc.contributor.authorGoldengorin, Boris
dc.contributor.authorMosadegh, Hadi
dc.contributor.departmentInformation System and Decision Sciencesen_US
dc.contributor.programInformation System and Decision Sciencesen_US
dc.date.accessioned2021-01-07T13:54:52Z
dc.date.available2021-01-07T13:54:52Z
dc.date.issued2018-01-03
dc.description.abstractOne of the well-known problems in a single machine scheduling context is the Job Sequencing and Tool Switching Problem (SSP). The SSP is optimally sequencing a finite set of jobs and loading a restricted subset of tools to a magazine with the aim of minimizing the total number of tool switches. It has been proved in the literature that the SSP can be reduced to the Job Sequencing Problem (JSeP). In the JSeP, the number of tool switches from the currently processed job to the next job depends on the sequencing of all predecessors. In this paper, the JSeP is modeled as a Traveling Salesman Problem of Second Order(2-TSP).en_US
dc.description.urihttps://www.researchgate.net/profile/Boris_Goldengorin/publication/322228276_A_hybrid_method_of_2-TSP_and_novel_learning-based_GA_for_job_sequencing_and_tool_switching_problem/links/5ab3bdffa6fdcc1bc0c35053/A-hybrid-method-of-2-TSP-and-novel-learning-based-GA-for-job-sequencing-and-tool-switching-problem.pdfen_US
dc.format.extent214-229 ppen_US
dc.genrejournal articleen_US
dc.identifierdoi:10.13016/m2biuy-uexn
dc.identifier.citationAhmadi, E., Goldengorin, B., Süer, G. A., & Mosadegh, H. (2018). A hybrid method of 2-TSP and novel learning-based GA for job sequencing and tool switching problem. Applied Soft Computing, 65, 214-229. DOI: 10.1016/j.asoc.2017.12.04en_US
dc.identifier.uriDOI: 10.1016/j.asoc.2017.12.04
dc.identifier.urihttps://www.researchgate.net/profile/Boris_Goldengorin/publication/322228276_A_hybrid_method_of_2-TSP_and_novel_learning-based_GA_for_job_sequencing_and_tool_switching_problem/links/5ab3bdffa6fdcc1bc0c35053/A-hybrid-method-of-2-TSP-and-novel-learning-based-GA-for-job-sequencing-and-tool-switching-problem.pdf
dc.identifier.urihttp://hdl.handle.net/11603/20352
dc.language.isoen_USen_US
dc.publisherElsevieren_US
dc.relation.isAvailableAtUniversity of Baltimore
dc.rightsPublic Domain Mark 1.0*
dc.rights.urihttp://creativecommons.org/publicdomain/mark/1.0/*
dc.subjectCombinatorial optimizationen_US
dc.subjectJob Schedulingen_US
dc.subjectTool switchesen_US
dc.subjectGenetic algorithmen_US
dc.subjectQ-learningen_US
dc.subjectReinforcement learningen_US
dc.titleA hybrid method of 2-TSP and novel learning-based GA for job sequencing and tool switching problemen_US
dc.typeTexten_US

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