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The sixth edition provides expanded Discussion and Comments and References sections at the end of each chapter, creating a spotlight on practical applications of the theory presented in that chapter. New topics include rules for stochastic parallel machine scheduling and for stochastic online scheduling, models of flow shops with reentry, fixed parameter tractability, and new designs and implementations of scheduling systems. The main structure of the book as per previous edition consists of three parts. The first part focuses on deterministic scheduling and the related combinatorial problems. The second part covers probabilistic scheduling models; in this part it is assumed that processing times and other problem data are random and not known in advance. The third part deals with scheduling in practice; it covers heuristics that are popular with practitioners and discusses system design and implementation issues. All three parts of this new edition have been revamped and streamlined and the references have been made up-to-date. Theoreticians and practitioners alike will find this book of interest. Graduate students in operations management, operations research, industrial engineering, and computer science will find the book an accessible and invaluable resource. Scheduling - Theory, Algorithms, and Systems will serve as an essential reference for professionals working on scheduling problems in manufacturing, services, and other environments.Michael L. Pinedo is the Julius Schlesinger Professor of Operations Management in the Stern School of Business at New York University.

This book has resulted from the activities of IFAC TC 5.2 “Manufacturing Modelling for Management and Control”. The book offers an introduction and advanced techniques of scheduling applications to cloud manufacturing and Industry 4.0 systems for larger audience. This book uncovers fundamental principles and recent developments in the theory and application of scheduling methodology to cloud manufacturing and Industry 4.0.The purpose of this book is to present recent developments in scheduling in cloud manufacturing and Industry 4.0 and to systemize these developments in new taxonomies and methodological principles to shape this new research domain. This book addresses the needs of both researchers and practitioners to uncover the challenges and opportunities of scheduling techniques'applications to cloud manufacturing and Industry 4.0. For the first time, it comprehensively conceptualizes scheduling in cloud manufacturing and Industry 4.0 systems as a new research domain. The chapters of the book are written by the leading international experts and utilize methods of operations research, industrial engineering and computer science. Such a multi-disciplinary combination is unique and comprehensively deciphers major problem taxonomies, methodologies, and applications to scheduling in cloud manufacturing and Industry 4.0.

This book presents a number of efficient techniques for solving large-scale production scheduling and planning problems in process industries. The main content is supplemented by a wealth of illustrations, while case studies on large-scale industrial applications, ranging from continuous to semicontinuous and batch processes, round out the coverage.The book examines a variety of complex, real-world problems, and demonstrates solutions that are applicable to scenarios and countries around the world. Specifically, these case studies include:• the production planning of the bottling stage of a major brewery at the Cervecería Cuauhtémoc Moctezuma (Heineken Int) in Mexico;• the production scheduling for multi-stage semicontinuous processes at an ice-cream production facility of Unilever in the Netherlands;• the resource-constrained production planning for the yogurt production line at the KRI KRI dairy production facility in Greece; and• the production scheduling for large-scale, multi-stage batch processes at a pharmaceutical batch plant in Germany.In addition, the book includes industrial-inspired case studies of:• the simultaneous planning of production and logistics operations considering multi-site facilities for semicontinuous processes; and• the integrated planning of production and utility systems in process industries under uncertainty.Solving Large-scale Production Scheduling and Planning in the Process Industries offers a valuable reference guide for researchers and decision-makers alike, as it shows readers how to evaluate and improve existing installations, and how to design new ones. It is also well suited as a textbook for advanced courses on production scheduling and planning in industry, as it addresses the optimization of production and logistics operations in real-world process industries.

In scheduling theory, the models that have attracted considerable attention during the last two decades allow the processing times to be variable, i.e., to be subjected to various effects that make the actual processing time of a job dependent on its location in a schedule. The impact of these effects includes, but is not limited to, deterioration and learning. Under the first type of effect, the later a job is scheduled, the longer its actual processing time becomes. In the case of learning, delaying a job will result in shorter processing times. Scheduling with Time-Changing Effects and Rate-Modifying Activities covers and advances the state-of-the-art research in this area. The book focuses on single machine and parallel machine scheduling problems to minimize either the maximum completion time or the sum of completion times of all jobs, provided that the processing times are subject to various effects. Models that describe deterioration, learning and general non-monotone effects to be considered include positional, start-time dependent, cumulative and their combinations, which cover most of the traditionally used models. The authors also consider more enhanced models in which the decision-maker may insert certain Rate-Modifying Activities (RMA) on processing machines, such as for example, maintenance or rest periods. In any case, the processing times of jobs are not only dependent on effects mentioned above but also on the place of a job in a schedule relative to an RMA. For most of the enhanced models described in the book, polynomial-time algorithms are presented which are based on similar algorithmic ideas such as reduction to linear assignment problems (in a full form or in a reduced form), discrete convexity, and controlled generation of options.

Jens Kuhpfahl analyzes the job shop scheduling problem with minimizing the total weighted tardiness as objective. First, he provides a suitable graph representation based on a disjunctive graph formulation. Second, several key components of local search procedures are analyzed and enhanced. The resulting outputs of these investigations contribute to the development of a new solution procedure whose performance quality leads to superior computational results.

This new edition provides an up-to-date coverage of important theoretical models in the scheduling literature as well as significant scheduling problems that occur in the real world. It again includes supplementary material in the form of slide-shows from industry and movies that show implementations of scheduling systems.The main structure of the book as per previous edition consists of three parts. The first part focuses on deterministic scheduling and the related combinatorial problems. The second part covers probabilistic scheduling models; in this part it is assumed that processing times and other problem data are random and not known in advance. The third part deals with scheduling in practice; it covers heuristics that are popular with practitioners and discusses system design and implementation issues. All three parts of this new edition have been revamped and streamlined. The references have been made completely up-to-date. Theoreticians and practitioners alike will find this book of interest. Graduate students in operations management, operations research, industrial engineering, and computer science will find the book an accessible and invaluable resource. Scheduling - Theory, Algorithms, and Systems will serve as an essential reference for professionals working on scheduling problems in manufacturing, services, and other environments.

The book is devoted to the problem of manufacturing scheduling, which is the efficient allocation of jobs (orders) over machines (resources) in a manufacturing facility. It offers a comprehensive and integrated perspective on the different aspects required to design and implement systems to efficiently and effectively support manufacturing scheduling decisions. Obtaining economic and reliable schedules constitutes the core of excellence in customer service and efficiency in manufacturing operations. Therefore, scheduling forms an area of vital importance for competition in manufacturing companies. However, only a fraction of scheduling research has been translated into practice, due to several reasons. First, the inherent complexity of scheduling has led to an excessively fragmented field in which different sub problems and issues are treated in an independent manner as goals themselves, therefore lacking a unifying view of the scheduling problem. Furthermore, mathematical brilliance and elegance has sometimes taken preference over practical, general purpose, hands-on approaches when dealing with these problems. Moreover, the paucity of research on implementation issues in scheduling has restricted translation of valuable research insights into industry.'Manufacturing Scheduling Systems: An Integrated View on Models, Methods and Tools'presents the different elements constituting a scheduling system, along with an analysis the manufacturing context in which the scheduling system is to be developed. Examples and case studies from real implementations of scheduling systems are presented in order to drive the presentation of the theoretical insights. The book is intended for an ample readership including industrial engineering/operations post-graduate students and researchers, business managers, and readers seeking an introduction to the field.

The topic of this book is known as dynamic scheduling, and is used to refer to three dimensions of project management and scheduling: the construction of a baseline schedule and the analysis of a project schedule's risk as preparation of the project control phase during project progress. This dynamic scheduling point of view implicitly assumes that the usability of a project's baseline schedule is rather limited and only acts as a point of reference in the project life cycle. Consequently, a project schedule should especially be considered as nothing more than a predictive model that can be used for resource efficiency calculations, time and cost risk analyses, project tracking and performance measurement, and so on.In this book, the three dimensions of dynamic scheduling are highlighted in detail and are based on and inspired by a combination of academic research studies at Ghent University (www.ugent.be), in-company trainings at Vlerick Business School (www.vlerick.com) andconsultancy projects at OR-AS (www.or-as.be). First, the construction of a project baseline schedule is a central theme throughout the various chapters of the book, and is discussed from a complexity point of view with and without the presence of project resources. Second, the creation of an awareness of the weak parts in a baseline schedule is discussed at the end of the two baseline scheduling parts as schedule risk analysis techniques that can be applied on top of the baseline schedule. Third, the baseline schedule and its risk analyses can be used as guidelines during the project control step where actual deviations can be corrected within the margins of the project's time and cost reserves.The second edition of this book has seen corrections, additions and amendments in detail throughout the book. Moreover Chapter 15 on'Dynamic Scheduling with ProTrack'has been completely rewritten and extended with a section on'ProTrack as a research tool'.

Although several monographs and edited volumes have discussed scheduling in general, most of these works survey the field by contributing a single chapter to production systems like flow shops. Flow Shop Scheduling: Theoretical Results, Algorithms, and Applications is solely dedicated to bringing together a huge body of knowledge on the subject, along distinct design features, in order to help scholars and practitioners easily identify problems of interest. This monograph has been organized into ten distinct flow shop systems and explores their connections. The chapters cover flow shop systems including two-machine, flexible, stochastic, and more. Outside of the traditional flow shops that require a job never revisits any stage, this book also examines the reentrant flow shop, in which a job may cycle back and be reprocessed at the same station or sequence of stations, multiple times.The authors have made the material accessible to a broad readership, using simplified notation and revealing unifying concepts. The results unique to flow shop research should provide the seed for research in other areas of scheduling and in optimization in general.

This book deals with the performance analysis of closed queueing networks with general processing times and finite buffer spaces. It offers a detailed introduction to the problem and a comprehensive literature review. Two approaches to the performance of closed queueing networks are presented. One is an approximate decomposition approach, while the second is the first exact approach for finite-capacity networks with general processing times. In this Markov chain approach, queueing networks are analyzed by modeling the entire system as one Markov chain. As this approach is exact, it is well-suited both as a reference quantity for approximate procedures and as extension to other queueing networks. Moreover, for the first time, the exact distribution of the time between processing starts is provided.

A project is a unique undertaking or endeavor to be accomplished that can be divided into individual subtasks or activities each of which requires time and scarce resources for its completion. Also there is a desired objective to be attained (for example, minimization of project duration or of variation of resource utilization, or maximization of net present value of the project). Moreover, there are given precedence relationships among activities prescrib­ ing the order in which activities must be carried out. Project scheduling, in its basic form, consists of finding start times for all activities such that pre­ scribed resource and precedence constraints are satisfied and an objective function is optimized. Since the concept of a project can be interpreted quite broadly, project scheduling problems arise in a great variety of practical situations. These in­ clude construction work, the development and introduction of new products, service systems, or software packages, strategic long-term planning in manu­ facturing and the service sector, emergency planning, and even the conduct­ ing of political campaigns. Recently, project scheduling has been successfully applied to production and operations management, e.g. make-to-order pro­ duction in manufacturing and batch production in process industries. Since the late 1950's, network-based planning methods for project sched­ uling problems have been developed, cf. Elmaghraby (1977) and Moder et al.

Besides scheduling problems for single and parallel machines and shop scheduling problems the book covers advanced models involving due-dates, sequence dependent change over times and batching. Also multiprocessor task scheduling and problems with multi-purpose machines are discussed. The methods used to solve these problems are polynomial algorithms, dynamic programming procedures, branch-and-bound algorithms and local search heuristics. Also complexity issues are addressed.

Besides scheduling problems for single and parallel machines and shop scheduling problems the book covers advanced models involving due-dates, sequence dependent changeover times and batching. Also multiprocessor task scheduling and problems with multipurpose machines are discussed. The method used to solve these problems are linear programming, dynamic programming, branch-and-bound algorithms, and local search heuristics. Complexity results for the different classes of deterministic scheduling problems are updated and summarized. Also the references are updated.

Continuous casting and hot strip milling are two successive production steps in the steel industry. In her thesis Imke Mattik develops model formulations to integrate the scheduling of continuous casters and hot strip mills. Aim is to reduce the waiting times of the pre-products, called slabs, between the production steps and at the same time to reduce the energy consumption. Along with two different model formulations extensive numerical tests and comparative analyses are provided.

​The book presents different models for the simultaneous optimization problem of capacity investment and work release rule parameterization. The overall costs are minimized either including backorder costs or considering a service level constraint. The available literature is extended with the integration of a distributed customer required lead time in addition to the actual demand distribution. Furthermore, an endogenous production lead time is introduced. Different models for make-to-order production systems with one or multiple serial processing stages are developed. Capacity investment is linked to the processing rates of the machines or to the number of the machines. Results are equations for service level, tardiness, and FGI lead time in such a production system. For special cases with M/M/1 and M/M/s queues explicit solutions of the optimization problems or optimality conditions concerning capacity investment and work release rule parameterization are provided.

This book is a continuation of Scheduling in Computer and Manufacturing Sys­ tems 1, two editions of which have received kind acceptance of a wide readership. As the previous position, it is the result of a collaborative German-Polish project which has been partially supported by Committee for Scientific Research 2 and DFG. We appreciate this help. We decided to treat this work as a new book rather than the third edition of the previous one due to two important reasons. First of all, the contents has been changed significantly. This concerns not only corrections we have introduced following the suggestions made by many readers (we are very grateful to all of them!) and taking into account our own experience, but first of all this means that important new material has been added. In particular, in the introductory part the ideas of new local search heuristics, i. e. generally applicable global optimization strategies with a simple capability of learning (ejection chains, genetic algo­ rithms) have been presented. In the framework of parallel processor scheduling, topics of imprecise computations and lot size scheduling have been studied. Further on flow shop and job shop scheduling problems have been studied much more extensively, both from the viewpoint of exact algorithms as well as heuris­ tics.

A survey of the state of the art of deterministic resource-constrained project scheduling with time windows. General temporal constraints and several different types of limited resources are considered. A large variety of time-based, financial, and resource-based objectives - important in practice - are studied. A thorough structural analysis of the feasible region of project scheduling problems and a classification and detailed investigation of objective functions are performed, which can be exploited for developing efficient exact and heuristic solution methods. New interesting applications of project scheduling to production and operations management as well as investment projects are discussed in the second edition.

Scheduling is a resource allocation problem which exists in virtually every type of organization. Scheduling problems have produced roughly 40 years of research primarily within the OR community. This community has traditionally emphasized mathematical modeling techniques which seek exact solutions to well formulated optimization problems. While this approach produced important results, many contemporary scheduling problems are particularly difficult. Hence, over the last ten years operations researchers interested in scheduling have turned increasingly to more computer intensive and heuristic approaches. At roughly the same time, researchers in AI began to focus their methods on industrial and management science applications. The result of this confluence of fields has been a period of remarkable growth and excitement in scheduling research. Intelligent Scheduling Systems captures the results of a new wave of research at the forefront of scheduling research, of interest to researchers and practitioners alike. Presented are an array of the latest contemporary tools -- math modeling to tabu search to genetic algorithms -- that can assist in operational scheduling and solve difficult scheduling problems. The book presents the most recent research results from both operations research (OR) and artificial intelligence (AI) focusing their efforts on real scheduling problems.

The factory scheduling problem, that of allocating machines to competing jobs in manufacturing facilities to optimize or at least improve system performance, is encountered in many different manufacturing environments. Given the competitive pressures faced by many companies in today's rapidly changing global markets, improved factory scheduling should contribute to a flrm's success. However, even though an extensive body of research on scheduling models has been in existence for at least the last three decades, most of the techniques currently in use in industry are relatively simplistic, and have not made use of this body of knowledge. In this book we describe a systematic, long-term research effort aimed at developing effective scheduling algorithms for complex manufacturing facilities. We focus on a speciflc industrial context, that of semiconductor manufacturing, and try to combine knowledge of the physical production system with the methods and results of scheduling research to develop effective approximate solution procedures for these problems. The class of methods we suggest, decomposition methods, constitute a broad family of heuristic approaches to large, NP-hard scheduling problems which can be applied in other environments in addition to those studied in this book.

This new edition of the well established text Scheduling - Theory, Algorithms, and Systems provides an up-to-date coverage of important theoretical models in the scheduling literature as well as significant scheduling problems that occur in the real world. It again includes supplementary material in the form of slide-shows from industry and movies that show implementations of scheduling systems. The main structure of the book as per previous edition consists of three parts. The first part focuses on deterministic scheduling and the related combinatorial problems. The second part covers probabilistic scheduling models; in this part it is assumed that processing times and other problem data are random and not known in advance. The third part deals with scheduling in practice; it covers heuristics that are popular with practitioners and discusses system design and implementation issues. All three parts of this new edition have been revamped and streamlined. The references have been made completely up-to-date. Theoreticians and practitioners alike will find this book of interest. Graduate students in operations management, operations research, industrial engineering, and computer science will find the book an accessible and invaluable resource. Scheduling - Theory, Algorithms, and Systems will serve as an essential reference for professionals working on scheduling problems in manufacturing, services, and other environments. Reviews of third edition: This well-established text covers both the theory and practice of scheduling. The book begins with motivating examples and the penultimate chapter discusses some commercial scheduling systems and examples of their implementations.'(Mathematical Reviews, 2009)

Billions of dollars are tied up in the inventories of manufacturing companies which cause large (interest) costs. A small decrease of the inventory and/or production costs without reduction of the service level can increase the profit substantially. Especially in the case of scarce capacity, efficient production schedules are fundamental for short delivery time and on-time delivery which are important competitive priorities. To support decision makers by improving their manufacturing resource planning system with appropriate methods is one of the most of production planning. interesting challenges The following chapters contain new models and new solution strategies which may be helpful for decision makers and for further research in the areas of production planning and operations research. The main subject is on lotsizing and scheduling. The objectives and further characteristics of such problems can be inferred from practical need. Thus, before an outline is given, we consider the general objectives of lotsizing and scheduling and classify the most important characteristics of such problems in the following sections.

The financial results of any manufacturing company can be dramatically impacted by the repetitive decisions required to control a complex production network be it a network of machines in a factory; a network of factories in a company; or a network of companies in a supply chain. Decision Policies for Production Networks presents recent convergent research on developing policies for operating production networks including details of practical control and decision techniques which can be applied to improve the effectiveness and economic efficiency of production networks worldwide. Researchers and practitioners come together to explore a wide variety of approaches to a range of topics including:WIP and equipment management policies,Material release policies,Machine, factory, and supply chain network policies for delivery in the face of supply and demand variability, andConflicts between complex production network models and their controlling policies.Case studies and relevant mathematical techniques are included to support and explain techniques such as heuristics, global and hierarchical optimization, control theory and filtering approaches related to complex systems or traffic flows. Decision Policies for Production Networks acts as handbook for researchers and practitioners alike, providing findings and information which can be applied to develop methods and advance further research across production networks.

Constraint Programming is a problem-solving paradigm that establishes a clear distinction between two pivotal aspects of a problem: (1) a precise definition of the constraints that define the problem to be solved and (2) the algorithms and heuristics enabling the selection of decisions to solve the problem. It is because of these capabilities that Constraint Programming is increasingly being employed as a problem-solving tool to solve scheduling problems. Hence the development of Constraint-Based Scheduling as a field of study. The aim of this book is to provide an overview of the most widely used Constraint-Based Scheduling techniques. Following the principles of Constraint Programming, the book consists of three distinct parts: The first chapter introduces the basic principles of Constraint Programming and provides a model of the constraints that are the most often encountered in scheduling problems. Chapters 2, 3, 4, and 5 are focused on the propagation of resource constraints, which usually are responsible for the'hardness'of the scheduling problem. Chapters 6, 7, and 8 are dedicated to the resolution of several scheduling problems. These examples illustrate the use and the practical efficiency of the constraint propagation methods of the previous chapters. They also show that besides constraint propagation, the exploration of the search space must be carefully designed, taking into account specific properties of the considered problem (e.g., dominance relations, symmetries, possible use of decomposition rules). Chapter 9 mentions various extensions of the model and presents promising research directions.

Let us start with the description of the purpose of this book. First we should explain how we understand its tide. In general, scheduling problems can be understood very broadly as the problems of the allocation of resources over time to perform a set of tasks. By resources we understand arbitrary means tasks compete for. They can be of a very different nature, e.g. manpower, money, processors (machines), energy, tools. Also tasks can have a variety of interpretations starting from machining parts in manu­ facturing systems up to processing information in computer systems. The same is true for task characteristics, e. g. ready times, due dates, relative urgency weights, functions describing task processing in relation to allotted resources. Moreover, a structure of a set of tasks, reflecting precedence constraints among them, can be defined in different ways. In addition, different criteria which measure the quality of the performance of a set of tasks can be taken into account.

In some manufacturing systems significant setups are required to change production from one type of products to another. The setups render the manufacturing system inflexible as for reacting to changes in demand patterns, hence inventories must be maintained to guarantee an acceptable customer service. In this environment, production scheduling faces a number of problems, and this work deals with mathematical models to support the scheduling decisions. Some more background and motivation is given in the following sections, as well as in a case description in Section 1. 3. The synopsis in Section 1. 4 outlines the topics of the work. 1. 1 Motivation of the Planning Problem Consider the production of metal sheets in a rolling mill. If the width of the next type of sheets is greater than the width of the preceding type, then the roll needs a setup: during the rolling process the edges of a sheet cause grooves on the rolls'surface, thus, the surface must be polished if a greater width is run next. Sheets with a smaller width can be run directly, without a setup. Another example in which setups are sequence dependent is a line where cars are sprayed: if the color of the paint changes, the cleaning of the tools requires a setup depending on the sequence of the colors. Only a small setup may be needed for changing from a light to a dark color, but a thorough cleaning of the tools is 2 CHAPTER 1.

An increasing interest to scheduling theory can be attributed to the high level of automation of all branches of human activity. The quality of modern production essentially depends on the planning decisions taken at different stages of a production process. Moreover, while the quality of these decisions is improving, the time and flexibility requirements for decision-making are becoming more important. All this stimulates scheduling research. Started as an independent discipline in the early fifties, it now has become an important branch of operations research. In the eighties, the largest Russian publishing house for scientific literature Nauka Publishers, Moscow, issued two books by a group of Byelorussian mathematicians: Scheduling Theory. Single-Stage Systems by V. S. Tanaev, V. S. Gordon and Y. M. Shafransky (1984) and Scheduling Theory. Multi-Stage Systems by V. S. Tanaev, Y. N. Sotskov and V. A. Strusevich (1989). Originally published in Russian, these two books cover two different major problem areas of scheduling theory and can be considered as a two-volume monograph that provides a systematic and comprehensive exposition of the subject. The authors are grateful to Kluwer Academic Publishers for creating the opportunity to publish the English translations of these two books. We are indebted to M. Hazewinkel, J. K. Lenstra, A. H. G. Rinnooy Kan, D. B. Shmoys and W. Szwarc for their supporting the idea of translating the books into English.

Production planning, inventory management, quality control, and maintenance policy are critical components of the manufacturing system. The effective integration of these four components gives a manufacturing operation the competitive edge in today's global market place. Integrated Models in Production Planning, Inventory, Quality, and Maintenance provides, in one volume, the latest developments in the integration of production, quality, and maintenance models. Prominent researchers, who are actively engaged in these areas, have contributed the topical chapters focused on the most recent issues in the area. In Part I, Ben-Daya and Rahim provide an overview of the literature dealing with integrated models for production, quality, and maintenance. Directions for future research are outlined. Part II contains six chapters (chapters 2 to 6) dealing with integrated models for production and maintenance. Part III deals with integrated production/inventory and quality models in chapters 7-11. Part IV focuses on quality and maintenance integrated models and contains two chapters. Part V deals with warranty, manufacturing, and quality and contains two chapters. Part VI addresses issues related to quality and contains three chapters (chapters 16-18).

Within a project human and non-human resources are pulled together in a tempo­ raray organization in order to achieve a predefined goal (d. [20], p. 187). That is, in contrast to manufacturing management, project management is directed to an end. One major function of project management is the scheduling of the project. Project scheduling is the time-based arrangement of the activities comprising the project subject to precedence-, time-and resource-constraints (d. [4], p. 170). In the 1950's the standard methods MPM (Metra Potential Method) and CPM (Cri­ tical Path Method) were developed. Given deterministic durations and precedence­ constraints the minimum project length, time windows for the start times and critical paths can be calculated. At the same time another group of researchers developed the Program Evaluation and Review Technique (PERT) (d. [19], [73] and [90]). In contrast to MPM and CPM, random variables describe the activity durations. Based on the optimistic, most likely and pessimistic estimations of the activity durations an assumed Beta­ distribution is derived in order to calculate the distribution of the project duration, the critical events, the distribution of earliest and latest occurence of an event, the distribution of the slack of the events and the probability of exceeding a date. By the time the estimates of the distributions have been improved (d. e.g. [52] and [56]). Nevertheless, there are some points of critique concerning the estimation of the resulting distributions and probabilities (d. e.g. [48], [49] and [50]).

Time-dependent scheduling involves problems in which the processing times of jobs depend on when those jobs are started. This book is a comprehensive study of complexity results and optimal and suboptimal algorithms concerning time-dependent scheduling in single-, parallel- and dedicated-machine environments. In addition to complexity issues and exact or heuristic algorithms which are typically presented in scheduling books, the author also includes more advanced topics such as matrix methods in time-dependent scheduling, and time-dependent scheduling with two criteria. The reader should be familiar with basic notions of calculus, discrete mathematics and combinatorial optimization theory, while the book offers introductory material on NP-complete problems, and the basics of scheduling theory. The author includes numerous examples, figures and tables, he presents different classes of algorithms using pseudocode, and he completes the book with an extensive bibliography, and author, symbol and subject indexes. The book is suitable for researchers working on scheduling, problem complexity, optimization, heuristics and local search algorithms.

Besides scheduling problems for single and parallel machines and shop scheduling problems the book covers advanced models involving due-dates, sequence dependent changeover times and batching. Also multiprocessor task scheduling and problems with multi-purpose machines are discussed. The methods used to solve these problems are linear programming, dynamic programming, branch-and-bound algorithms, and local search heuristics. Complexity results for different classes of deterministic scheduling problems are summerized.

Handbook of Production Scheduling concentrates on real-world production scheduling in factories and industrial settings. It includes industry case studies that use innovative techniques as well as academic research results that can be used to improve real-world production scheduling. Its purpose is to present scheduling principles, advanced tools, and examples of innovative scheduling systems to persons who could use this information to improve production scheduling in their own organization. The intended audience includes: production and plant managers, industrial engineers, operations research practitioners, advanced undergraduate/ graduate students and faculty studying and doing research in operations research and industrial engineering.

Scheduling and multicriteria optimisation theory have been subject, separately, to numerous studies. Since the last twenty years, multicriteria scheduling problems have been subject to a growing interest. However, a gap between multicriteria scheduling approaches and multicriteria optimisation field exits. This book is an attempt to collect the elementary of multicriteria optimisation theory and the basic models and algorithms of multicriteria scheduling. It is composed of numerous illustrations, algorithms and examples which may help the reader in understanding the presented concepts. This book covers general concepts such as Pareto optimality, complexity theory, and general method for multicriteria optimisation, as well as dedicated scheduling problems and algorithms: just-in-time scheduling, flexibility and robustness, single machine problems, parallel machine problems, shop problems, etc. The second edition contains revisions and new material.

Column Generation is an insightful overview of the state of the art in integer programming column generation and its many applications. The volume begins with'A Primer in Column Generation'which outlines the theory and ideas necessary to solve large-scale practical problems, illustrated with a variety of examples. Other chapters follow this introduction on'Shortest Path Problems with Resource Constraints,''Vehicle Routing Problem with Time Window,''Branch-and-Price Heuristics,''Cutting Stock Problems,'each dealing with methodological aspects of the field. Three chapters deal with transportation applications:'Large-scale Models in the Airline Industry,''Robust Inventory Ship Routing by Column Generation,'and'Ship Scheduling with Recurring Visits and Visit Separation Requirements.'Production is the focus of another three chapters:'Combining Column Generation and Lagrangian Relaxation,''Dantzig-Wolfe Decomposition for Job Shop Scheduling,'and'Applying Column Generation to Machine Scheduling.'The final chapter by François Vanderbeck,'Implementing Mixed Integer Column Generation,'reviews how to set-up the Dantzig-Wolfe reformulation, adapt standard MIP techniques to the column generation context (branching, preprocessing, primal heuristics), and deal with specific column generation issues (initialization, stabilization, column management strategies).

This book focuses on planning and scheduling applications. Planning and scheduling are forms of decision-making that play an important role in most manufacturing and services industries. The planning and scheduling functions in a company typically use analytical techniques and heuristic methods to allocate its limited resources to the activities that have to be done. The application areas considered in this book are divided into manufacturing applications and services applications. The book covers five areas in manufacturing: project scheduling, job shop scheduling, scheduling of flexible assembly systems, economic lot scheduling, and planning and scheduling in supply chains. It covers four areas in services: reservations and timetabling, tournament scheduling, planning and scheduling in transportation, and workforce scheduling. At the end of each chapter, a case study or a system implementation is described in detail. Numerous examples and exercises throughout the book illustrate the material presented. The fundamentals concerning the methodologies used in the application chapters are covered in the appendices.The book comes with extra material on http://extras.springer.com that contains various sets of PowerPoint slides. The extra material also contains several planning and scheduling systems that have been developed in academia as well as generic optimization software that has been developed in industry. This book is suitable for more advanced students in industrial engineering and operations research as well as graduate students in business. Michael Pinedo is the Julius Schlesinger Professor of Operations Management in the Stern School of Business at New York University. His research interests lie in the theoretical and applied aspects of planning and scheduling. He has written numerous papers on the theory of deterministic and stochastic scheduling and has also consulted extensively in industry. He has been actively involved in the development of several large industrial planning and scheduling systems.