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Scheduling jobs on ...
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Pei, JunSchool of Management, Hefei University of Technology, Hefei, China; Center for Applied Optimization, Department of Industrial and Systems Engineering, University of Florida, Gainesville, USA
(author)
Scheduling jobs on a single serial-batching machine with dynamic job arrivals and multiple job types
- Article/chapterEnglish2016
Publisher, publication year, extent ...
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2015-02-15
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Springer Science and Business Media LLC,2016
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printrdacarrier
Numbers
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LIBRIS-ID:oai:DiVA.org:ltu-3472
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https://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-3472URI
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https://doi.org/10.1007/s10472-015-9449-7DOI
Supplementary language notes
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Language:English
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Summary in:English
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Subject category:ref swepub-contenttype
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Subject category:art swepub-publicationtype
Notes
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Validerad; 2016; Nivå 2; 20150218 (andbra)
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This paper investigates a scheduling model with certain co-existing features of serial-batching, dynamic job arrival, multi-types of job, and setup time. In this proposed model, the jobs of all types are first partitioned into serial batches, which are then processed on a single serial-batching machine with an independent constant setup time for each new batch. In order to solve this scheduling problem, we divide it into two phases based on job arrival times, and we also derive and prove certain constructive properties for these two phases. Relying on these properties, we develop a two-phase hybrid algorithm (TPHA). In addition, a valid lower bound of the problem is also derived. This is used to validate the quality of the proposed algorithm. Computational experiments, both with small- and large-scale problems, are performed in order to evaluate the performance of TPHA. The computational results indicate that TPHA outperforms seven other heuristic algorithms. For all test problems of different job sizes, the average gap percentage between the makespan, obtained using TPHA, and the lower bound does not exceed 5.41 %.
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Added entries (persons, corporate bodies, meetings, titles ...)
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Liu, XinbaoSchool of Management, Hefei University of Technology, Hefei, China; Key Laboratory of Process Optimization and Intelligent Decision-making of Ministry of Education, Hefei, China
(author)
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Fan, WenjuanSchool of Management, Hefei University of Technology, Hefei, China; Department of Computer Science, North Carolina State University, Raleigh, USA
(author)
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Pardalos, Panos M.Center for Applied Optimization, Department of Industrial and Systems Engineering, University of Florida, Gainesville, USA
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Migdalas, AthanasiosLuleå tekniska universitet,Industriell Ekonomi,Division of Transportation, Construction Management and Regional Planning, Department of Civil Engineering, Aristotle University of Thessaloniki, Thessaloniki, Greece(Swepub:ltu)athmig
(author)
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Yang, ShanlinSchool of Management, Hefei University of Technology, Hefei, China; Key Laboratory of Process Optimization and Intelligent Decision-making of Ministry of Education, Hefei, China
(author)
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School of Management, Hefei University of Technology, Hefei, China; Center for Applied Optimization, Department of Industrial and Systems Engineering, University of Florida, Gainesville, USASchool of Management, Hefei University of Technology, Hefei, China; Key Laboratory of Process Optimization and Intelligent Decision-making of Ministry of Education, Hefei, China
(creator_code:org_t)
Related titles
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In:Annals of Mathematics and Artificial Intelligence: Springer Science and Business Media LLC76:1-2, s. 215-2281012-24431573-7470
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