Scheduling: Theory, Algorithms, and Systems 4/e
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.
Discussion of the basic properties of scheduling models
Computational as well as theoretical exercises at the end of each chapter
Thorough examination of numerous applications
Investigation of the latest developments in the field
Discussion of future research developments
Covers deterministic models as well as stochastic models
Covers theoretical models as well as practical applications
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.
Table of Contents
Part I Deterministic Models
2 Deterministic Models: Preliminaries
3 Single Machine Models (Deterministic)
4 Advanced Single Machine Models (Deterministic)
5 Parallel Machine Models (Deterministic)
6 Flow Shops and Flexible Flow Shops (Deterministic)
7 Job Shops (Deterministic)
8 Open Shops (Deterministic)
Part II Stochastic Models
9 Stochastic Models: Preliminaries
10 Single Machine Models (Stochastic)
11 Single Machine Models with Release Dates (Stochastic)
12 Parallel Machine Models (Stochastic)
13 Flow Shops, Job Shops and Open Shops (Stochastic)
Part III Scheduling in Practice
14 General Purpose Procedures for Deterministic Scheduling
15 More Advanced General Purpose Procedures
16 Modeling and Solving Scheduling Problems in Practice
17 Design and Implementation of Scheduling Systems: Basic Concepts
18 Design and Implementation of Scheduling Systems: More Advanced Concepts
19 Examples of System Designs and Implementations
20 What Lies Ahead?
Michael L. Pinedo is the Julius Schlesinger Professor of Operations Managemein the Stern School of Business at New York University.