THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

The Design and Analysis of Experiments

A unified view of metaheuristics This book provides a complete background on metaheuristics and shows readers how to design and implement efficient algorithms to solve complex optimization problems across a diverse range of applications, from networking and bioinformatics to engineering design, routing, and scheduling. It presents the main design questions for all families of metaheuristics and clearly illustrates how to implement the algorithms under a software framework to reuse both the design and code. Throughout the book, the key search components of metaheuristics are considered as a toolbox for: Designing efficient metaheuristics (e.g. local search, tabu search, simulated annealing, evolutionary algorithms, particle swarm optimization, scatter search, ant colonies, bee colonies, artificial immune systems) for optimization problems Designing efficient metaheuristics for multi-objective optimization problems Designing hybrid, parallel, and distributed metaheuristics Implementing metaheuristics on sequential and parallel machines Using many case studies and treating design and implementation independently, this book gives readers the skills necessary to solve large-scale optimization problems quickly and efficiently. It is a valuable reference for practicing engineers and researchers from diverse areas dealing with optimization or machine learning; and graduate students in computer science, operations research, control, engineering, business and management, and applied mathematics.

/pdf/metaheuristics-from-design-to-implementation-1vqdfv8nk9.pdf

Metaheuristics: From Design to Implementation

Praise for the Third Edition: "This is one of the best books available. Its excellent organizational structure allows quick reference to specific models and its clear presentation . . . solidifies the understanding of the concepts being presented."IIE Transactions on Operations EngineeringThoroughly revised and expanded to reflect the latest developments in the field, Fundamentals of Queueing Theory, Fourth Edition continues to present the basic statistical principles that are necessary to analyze the probabilistic nature of queues. Rather than presenting a narrow focus on the subject, this update illustrates the wide-reaching, fundamental concepts in queueing theory and its applications to diverse areas such as computer science, engineering, business, and operations research.This update takes a numerical approach to understanding and making probable estimations relating to queues, with a comprehensive outline of simple and more advanced queueing models. Newly featured topics of the Fourth Edition include:Retrial queuesApproximations for queueing networksNumerical inversion of transformsDetermining the appropriate number of servers to balance quality and cost of serviceEach chapter provides a self-contained presentation of key concepts and formulae, allowing readers to work with each section independently, while a summary table at the end of the book outlines the types of queues that have been discussed and their results. In addition, two new appendices have been added, discussing transforms and generating functions as well as the fundamentals of differential and difference equations. New examples are now included along with problems that incorporate QtsPlus software, which is freely available via the book's related Web site.With its accessible style and wealth of real-world examples, Fundamentals of Queueing Theory, Fourth Edition is an ideal book for courses on queueing theory at the upper-undergraduate and graduate levels. It is also a valuable resource for researchers and practitioners who analyze congestion in the fields of telecommunications, transportation, aviation, and management science.

Fundamentals of Queueing Theory

Facility location and supply chain management - A review

Introduction to stochastic programming

http://akturk.bilkent.edu.tr/ie573/aytug.pdf

Executing production schedules in the face of uncertainties: a review and some future directions

Although the national importance of the semiconductor industry is widely acknowledged, it is only recently that the production planning and scheduling problems encountered in this environment have begun to be addressed using industrial engineering and operations research.techniques. These problems have several features that make them difficult and challenging: random yields and rework, complex product flows, and rapidly changing products and technologies. Hence their solution will contribute considerably to die theory and practice of production planning and control. In a two-part project we present a review of research in this area to date, discuss the applicability of the various approaches and suggest directions for future research. In this paper, Part I, we describe the characteristics of the semiconductor manufacturing environment and review models related to performance evaluation and production planning. Part II will review research on shop-floor control in this industry to date.

A review of production planning and scheduling models in the semiconductor industry part i: system characteristics, performance evaluation and production planning

In this paper, we study the problem of scheduling semiconductor burn-in operations, where burn-in ovens are modeled as batch processing machines. A batch processing machine is one that can process up to B jobs simultaneously. The processing time of a batch is equal to the largest processing time among all jobs in the batch. We present efficient dynamic programming-based algorithms for minimizing a number of different performance measures on a single batch processing machine. We also present heuristics for a number of problems concerning parallel identical batch processing machines and we provide worst case error bounds.

Efficient algorithms for scheduling semiconductor burn-in operations

In the first part of this review [62] we described the characteristics of semiconductor manufacturing environments and reviewed research on system performance evaluation and production planning. In this paper we focus on shop-floor control problems. We classify research to date by the solution techniques used, and discuss the relative advantages and disadvantages of the various approaches. We discuss the relationship between shop-floor control and production planning and suggest future research directions.

A review of production planning and scheduling models in the semiconductor industry part ii: shop-floor control

The problem of scheduling jobs with non-identical capacity requirements or sizes on a single batch processing machine to minimize total completion time and makespan is studied. These problems are proven to be NP-hard and heuristics are developed for both, as well as a branch and bound algorithm for the total completion time problem. Computational experiments show that the heuristics are capable of rapidly obtaining near-optimal solutions.

Reha Uzsoy

Papers

Executing production schedules in the face of uncertainties: a review and some future directions

A review of production planning and scheduling models in the semiconductor industry part i: system characteristics, performance evaluation and production planning

Efficient algorithms for scheduling semiconductor burn-in operations

A review of production planning and scheduling models in the semiconductor industry part ii: shop-floor control

Scheduling a single batch processing machine with non-identical job sizes