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Sequencing and Scheduling with Inaccurate Data
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Editors: Yuri N. Sotskov and Frank Werner (United Institute of Informatics Problems of the National Academy of Sciences of Belarus, Minsk, Belarus and others)
Book Description:
In many real-world applications, the problems with the data used for scheduling such as processing times, setup times, release dates or due dates is not exactly known before applying a specific solution algorithm which restricts practical aspects of scheduling theory. During the last decades, several approaches have been developed for sequencing and scheduling with inaccurate data, depending on whether the data is given as random numbers, fuzzy numbers or whether it is uncertain, i.e., it can take values from a given interval. This book considers the four major approaches for dealing with such problems: a stochastic approach, a fuzzy approach, a robust approach and a stability approach. Each of the four parts is devoted to one of these approaches. First, it contains a survey chapter on this subject, as well as between further chapters, presenting some recent research results in the particular area. The book provides the reader with a comprehensive and up-to-date introduction into scheduling with inaccurate data. The four survey chapters deal with scheduling with stochastic approaches, fuzzy job-shop scheduling, minmax regret scheduling problems and a stability approach to sequencing and scheduling under uncertainty. This book will be useful for applied mathematicians, students and PhD students dealing with scheduling theory, optimization and calendar planning. (Imprint: Nova)

Book Review

This book has been reviewed by Dr. Erwin Pesch, Faculty of Economics and Business Administration, University in Siegen. To read the review, click here.


Table of Contents:
Preface pp,vii-x

Part I: Stochastic Approach pp,1-2

Chapter 1: Scheduling with Stochastic Approaches
(Xiaoqiang Cai, Xianyi Wu, Lianmin Zhang and Xian Zhou, Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong and others)pp,3-46

Chapter 2: Uncertainty in Stochastic Scheduling
(Tjark Vredeveld, Maastricht University, The Netherlands)pp,47-60

Chapter 3: Stochastic Scheduling with General Distributed Activity Durations Using Markov Activity Networks and Phase-Type Distributions
(Marcello Urgo, Mechanical Engineering Department, Politecnico di Milano, Via La Masa, Milano, Italy)pp,61-72

Part II: Fuzzy Approach pp,73-74

Chapter 4: Fuzzy Job-Shop Scheduling
(Masatoshi Sakawa, Faculty of Engineering, Hiroshima University, Higashi-Hiroshima, Japan)pp,75-100

Chapter 5: Fuzzy Multi-Project Rough-Cut Capacity Planning
(Malek Masmoudi, Erwin Hans, Roel Leus and Alain Hait, LASPI, F-42334, IUT de Roanne, University of Lyon, University of Saint-Etienne, Roanne, France and others)pp,101-118

Chapter 6: Fuzzy Resource Constraint Project Scheduling Problem
(Malek Masmoudi and Alain Hait, University of Lyon, University of Saint-Etienne, LASPI, F-42334, IUT de Roanne, Roanne, France and others)pp,119-138

Chapter 7: A Fuzzy Tailored Nonlinear Fluctuation Smoothing Rule for Job Dispatching in a Semiconductor Manufacturing Factory
(Toly Chen, Department of Industrial Engineering and Systems Management, Feng Chia University, Taichung, Taiwan)pp,139-156

Part III: Robust Approach pp,157-158

Chapter 8: Minmax (Regret) Scheduling Problems
(Adam Kasperski and Pawel Zielinski, Institute of Industrial Engineering and Management, Wroclaw University of Technology, Wybrzeze Wyspianskiego, Wroclaw, Poland and others)pp,159-210

Chapter 9: Robust Assembly Line Balancing: State of the Art and New Research Perspectives
(Öncü Hazir and Alexandre Dolgui, TED Üniversitesi, Iktisadi ve Idari Bilimler Fakültesi, Ziya Gökalp Caddesi, Kolej, Cankaya, Ankara, Turkey and others)pp,211-224

Chapter 10: Dynamic Analysis of Supply Chain Robustness and Adaptation with the Help of Attainable Sets and Positional Optimization
(Dmitry Ivanov, Boris Sokolov, Inna Solovyeva and Semen Potryasaev, Berlin School of Economics and Law, Department of Business Administration. Berlin, Germany and others)pp,225-252

Chapter 11: A Bi-Criteria Approach to Scheduling in the Face of Uncertainty: Considering Robustness and Stability Simultaneously
(Selcuk Gören and Ihsan Sabuncuoglu, Department of Industrial Engineering, Abdullah Gül University, Kayseri, Turkey)pp,253-280

Part IV: Stability Approach pp,281-282

Chapter 12: A Stability Approach to Sequencing and Scheduling under Uncertainty
(Yuri N. Sotskov and Frank Werner, United Institute of Informatics Problems, Minsk, Belarus and others)pp,283-344

Chapter 13: Minimizing Total Flow Time under Uncertainty Using Optimality and Stability Boxes
(Yuri N. Sotskov and Natalia G. Egorova, United Institute of Informatics Problems, Minsk, Belarus)pp,345-376

Chapter 14: A Stability Approach to Two-Stage Scheduling Problems with Uncertain Processing Times
(Natalja M. Matsveichuk and Yuri N. Sotskov, United Institute of Informatics Problems, Minsk, Belarus)pp,377-408

Chapter 15: Accuracy and Stability Functions for a Problem of Minimization of a Linear Form on a Set of Substitutions
(Yury Nikulin, Department of Mathematics and Statistics, University of Turku, Turku, Finland)pp,409-426

Index pp,427-432

      Applied Statistical Science
   Binding: Hardcover
   Pub. Date: 2014 - 1st Quarter
   Pages: 442, 7x10 - (NBC-C)
   ISBN: 978-1-62948-677-2
   Status: AV
Status Code Description
AN Announcing
FM Formatting
PP Page Proofs
FP Final Production
EP Editorial Production
PR At Prepress
AP At Press
AV Available
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Sequencing and Scheduling with Inaccurate Data