A probabilistic approach to the stochastic job-shop scheduling problem

dc.contributor.authorShoval, S.
dc.contributor.authorEfatmaneshnik, M.
dc.contributor.conference15th Global Conference on Sustainable Manufacturing, GCSM 2017 (25 Sep 2017 - 27 Sep 2017 : Haifa, Israel)
dc.date.issued2018
dc.description.abstractUncertainty exists in almost any manufacturing process, and its effect may be detrimental to the manufacturing outcomes. In the Stochastic Job Shop Scheduling Problem (SJSSP), some of the process parameters are random variables, in particular the processing time. This paper considers another facet of the SJSSP, which is the probability for success (or failure) of a manufacturing job and its effect on other jobs. The paper presents a mathematical model for determining the expected manufacturing cost, and proposes heuristics for reducing that cost. The fundamental model is based on a single resource (e.g. a single machine) and a set of manufacturing jobs, each characterized by a cost and a probabilistic distribution for success. A failure causes either a re-work of the failed job, or restarting the entire process from the first job. Since the problem is NH Hard, a set of heuristics for scheduling the jobs is proposed, and simulation results validate these heuristics
dc.identifier.citationProcedia Manufacturing, 2018, vol.21, pp.533-540
dc.identifier.doi10.1016/j.promfg.2018.02.154
dc.identifier.issn2351-9789
dc.identifier.issn2351-9789
dc.identifier.urihttps://hdl.handle.net/11541.2/142997
dc.language.isoen
dc.publisherElsevier
dc.publisher.placeNetherlands
dc.rightsCopyright 2018 The author(s), published by Elsevier Under a Creative Commons License (https://creativecommons.org/licenses/by-nc-nd/4.0/)
dc.source.urihttps://doi.org/10.1016/j.promfg.2018.02.154
dc.subjectmanufacturing tolerance
dc.subjectoptimizing manufacturing cost
dc.subjectprobablishtic process model
dc.subjectstochastic job shop scheduling
dc.titleA probabilistic approach to the stochastic job-shop scheduling problem
dc.typeConference paper
pubs.publication-statusPublished
ror.mmsid9916416411501831

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