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000929934 019__ $$a1145556415
000929934 020__ $$a9789811535284$$q(electronic book)
000929934 020__ $$a9811535280$$q(electronic book)
000929934 020__ $$z9811535272
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000929934 035__ $$aSP(OCoLC)on1145292593
000929934 035__ $$aSP(OCoLC)1145292593$$z(OCoLC)1145556415
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000929934 050_4 $$aTS157.5
000929934 08204 $$a658.5/3$$223
000929934 1001_ $$aWang, Dujuan,$$eauthor.
000929934 24510 $$aRescheduling under disruptions in manufacturing systems :$$bmodels and algorithms /$$cDujuan Wang, Yunqiang Yin, Yaochu Jin.
000929934 264_1 $$aSingapore :$$bSpringer,$$c[2020]
000929934 264_4 $$c©2020
000929934 300__ $$a1 online resource.
000929934 336__ $$atext$$btxt$$2rdacontent
000929934 337__ $$acomputer$$bc$$2rdamedia
000929934 338__ $$aonline resource$$bcr$$2rdacarrier
000929934 4901_ $$aUncertainty and operations research
000929934 504__ $$aIncludes bibliographical references.
000929934 5050_ $$aChapter 1 Introduction -- Chapter 2 Rescheduling on identical parallel machines in the presence of machine breakdowns -- Chapter 3 Parallel-machine rescheduling with job rejection in the presence of job unavailability -- Chapter 4 Rescheduling with controllable processing times and job rejection in the presence of new arrival jobs and deterioration eect -- Chapter 5 Rescheduling with controllable processing times and preventive maintenance in the presence of new arrival jobs and deterioration eect -- Chapter 6 A knowledge-based evolutionary proactive scheduling approach in the presence of ma-chine breakdown and deterioration eect.
000929934 506__ $$aAccess limited to authorized users.
000929934 520__ $$aThis book provides an introduction to the models, methods, and results of some rescheduling problems in the presence of unexpected disruption events, including job unavailability, arrival of new jobs, and machine breakdown. The occurrence of these unexpected disruptions may cause a change in the planned schedule, which may render the originally feasible schedule infeasible. Rescheduling, which involves adjusting the original schedule to account for a disruption, is necessary in order to minimize the effects of the disruption on the performance of the system. This involves a trade-off between finding a cost-effective new schedule and avoiding excessive changes to the original schedule. This book views scheduling theory as practical theory, and it has made sure to emphasize the practical aspects of its topic coverage. Thus, this book considers some scenarios existing in most real-world environments, such as preventive machine maintenance, and deteriorating effect where the actual processing time of a job gets longer along with machines usage and age. To alleviate the effect of disruption events, some flexible strategies are adopted, including allocation extra resources to reduce job processing times or rejection the production of some jobs. For each considered scenario, depending on the model settings and on the disruption events, this book addresses the complexity, and the design of efficient exact or approximated algorithms. Especially when optimization methods and analytic tools fall short, this book stresses metaheuristics including improved elitist non-dominated sorting genetic algorithm and differential evolution algorithm. This book also provides extensive numerical studies to evaluate the performance of the proposed algorithms. The problem of rescheduling in the presence of unexpected disruption events is of great importance for the successful implementation of real-world scheduling systems. There is now an astounding body of knowledge in this field. This book is the first monograph on rescheduling. It aims at introducing the author's research achievements in rescheduling. It is written for researchers and Ph.D. students working in scheduling theory and other members of scientific community who are interested in recent scheduling models. Our goal is to enable the reader to know about some new achievements on this topic.
000929934 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed April 8, 2020).
000929934 650_0 $$aProduction scheduling.
000929934 650_0 $$aProduction scheduling$$xMathematical models.
000929934 7001_ $$aYin, Yunqiang,$$eauthor.
000929934 7001_ $$aJin, Yaochu,$$d1966-$$eauthor.
000929934 77608 $$iPrint version:$$z9811535272$$z9789811535277$$w(OCoLC)1138495379
000929934 830_0 $$aUncertainty and operations research.
000929934 852__ $$bebk
000929934 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-981-15-3528-4$$zOnline Access$$91397441.1
000929934 909CO $$ooai:library.usi.edu:929934$$pGLOBAL_SET
000929934 980__ $$aEBOOK
000929934 980__ $$aBIB
000929934 982__ $$aEbook
000929934 983__ $$aOnline
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