Lot Streaming is a process of breaking a batch of jobs into smaller lots, and then processing these smaller lots in an overlapping fashion on the machines. This important concept can significantly improve the overall performance of a production process, and thereby make the operation of a manufacturing system lean. Flow Shop Lot Streaming Problems introduces the reader to this significant production process, presents various analysis techniques, and allows the reader to quickly become conversant with the state-of-the-art techniques in order to embark on new research directions. This text begins with an introduction to and a brief historical perspective of the lot streaming problem, and continues with generic mathematical models for this problem. Flow Shop Lot Streaming Problems presents systematic analysis, algorithms, key ideas and illustrative examples using 2-machine, 3-machine, and the general m-machine flow shop lot streaming problems.

From the Preface: This festschrift is devoted to recognize the career of a man who not only witnessed the growth of operations research from its inception, but also contributed significantly to this growth. Dr. Salah E. Elmaghraby received his doctorate degree from Cornell University in 1958, and since then, his scholarly contributions have enriched the fields of production planning and scheduling and project scheduling. This collection of papers is contributed in his honor by his students, colleagues, and acquaintances. It offers a tribute to the inspiration received from his work, and from his guidance and advice over the years, and recognizes the legacy of his many contributions. Dr. Elmaghraby is a pioneer in the area of project scheduling (in particular, project planning and control through network models, for which he coined the term 'activity networks'.) In his initial work in this area, he developed an algebra based on signal flow graphs and semi-Markov processes for analyzing generalized activity networks involving activities with probabilistic durations. This work led to the development of what was later known as the Graphical Evaluation and Review Technique (GERT), and GERT simulation models. He has made fundamental contributions in determining criticality indices for activities, in developing methodologies for project compression and time/cost analysis, and in the use of stochastic and chance-constrained programming and Petri Nets for the analysis of activity networks. This volume brings together fourteen contributions, which can be viewed under the following three main themes: operations research and its application in production planning; project scheduling, and production scheduling, inspired by, and in many cases based on, Dr. Elmaghraby's work in these areas. The first five chapters are devoted to the first theme, followed by four chapters each devoted to the other two, respectively. An additional chapter is devoted to the vulnerability of multimodal freight systems.

Stochastic scheduling is in the area of production scheduling. There is a dearth of work that analyzes the variability of schedules. In a stochastic environment, in which the processing time of a job is not known with certainty, a schedule is typically analyzed based on the expected value of a performance measure. This book addresses this problem and presents algorithms to determine the variability of a schedule under various machine configurations and objective functions. It is intended for graduate and advanced undergraduate students in manufacturing, operations management, applied mathematics, and computer science, and it is also a good reference book for practitioners. Computer software containing the algorithms is provided on an accompanying website for ease of student and user implementation.

This book discusses the process of "Lot Streaming" and how it can significantly improve the overall performance of a production process, and thereby, make the operation of a manufacturing system lean. It provides a complete introduction to the Flow Shop Lot Streaming Problem and provides a historical perspective. It further

presents algorithms for a variety of lot streaming problems with numerical illustrations for ease of understanding and implementation.