Operations Research began as a field with the mathematical scheduling of a massive projecta "logistically supplying Europe with military equipment and goods during the 2nd World War. Today project scheduling research continues to grow in the variety of its theoretical models, in its magnitude, and in its application. As the world becomes more interrelated and complex, the wider its research is applied to an increasing number of project scheduling problems.

The book surveys the current state-of-the-art in this realm of operations research with chapters written by the respective leading experts on each topic. It will cover the range of the key models in the field, including deterministic, probabilistic, single- and multi-mode, single- and multi-objective, and a general model on discrete-continuous resources. Recent solution algorithms are systematically examined. The book summarizes the current developments and theoretical achievements in the field. These new developments include project uncertainty and grid resource management.

PERSPECTIVES IN MODERN PROJECT SCHEDULING systematically presents this dynamically developing area in three parts. Part I discusses new models of the project management process that are being developed. They include an alternative to the well-known PERT technique, consideration of disturbances during the project realization, introduction of new constraints like due dates or setup times, as well as a general discussion on classification of resources.

Part II outlines and evaluates the new algorithms that have been developed to solve the strongly NP-hard resource constrained project scheduling efficiently with acceptable accuracy. New lowerbounds for the RCPSP are proposed, followed by smart justification technique and a series of Metaheuristics. Finally, a neural network approach is introduced.

Part III is devoted to new areas of applications of the project management models and the algorithms a" for example, pharmaceutical research, grid computing, factory pick-up of new cars, batch scheduling in process industries and make-to-order (project driven) manufacturing a" that have been developed to solve project scheduling problems in these application areas.

The book will be of interest to academics and students in project management and scheduling in Business Schools, Operations Research/Management Science, Computer Science & Engineering, Systems Analysis, and Applied Mathematics. In addition, decision makers, consultants and practitioners in industry, government and service organizations will also be interested in this book.

As the field of Supply Chain Management has matured, maintaining the precise flow of goods to maintain schedules (hence, minimizing inventories) on a just-in-time basis still remains as a major challenge. This problem or challenge has resulted in a fair amount of quantitative research in the area, producing an array of models and algorithms to help ensure the precise flow of components and final products into inventories to meet just-in-time requirements.

Just-in-Time Scheduling: Models and Algorithms for Real Time Operating Systems is the first expository treatment surveying the theoretical work on computer systems models and algorithms utilized in just-in-time scheduling. With the impact of globalization and supply chains on manufacturing, there are immense amounts of material flowing through supply chains at any given time worldwide. Therefore the scheduling of all the stages of material arriving at different geographical points at precise times is a highly significant problem. Moreover, the theoretical work in this area has larger ramifications for operational scheduling in many application areas. The scheduling models and algorithms presented and illustrated in the book will be done so in the context of extensive use of computer systems in a "real time context." The "just-in-time" and "real-time" theoretical work in the book will be of value and interest to many Engineers, Computer Scientists and Operations Research/Management Science researchers, students and practitioners. The book will survey and synthesize all the research in this topical area.

This book surveys the current state-of-the-art in operations research. The book summarizes the current developments and theoretical achievements in the field, including project uncertainty and grid resource management. It further covers the range of the key models in the field, including deterministic, probabilistic, single- and multi-mode, single- and multi-objective, and a general model on discrete-continuous resources.

As the field of Supply Chain Management has matured, maintaining the precise flow of goods to maintain schedules (hence, minimizing inventories) on a just-in-time basis still remains as a major challenge. This problem or challenge has resulted in a fair amount of quantitative research in the area, producing an array of models and algorithms to help ensure the precise flow of components and final products into inventories to meet just-in-time requirements.

Just-in-Time Scheduling: Models and Algorithms for Real Time Operating Systems is the first expository treatment surveying the theoretical work on computer systems models and algorithms utilized in just-in-time scheduling. With the impact of globalization and supply chains on manufacturing, there are immense amounts of material flowing through supply chains at any given time worldwide. Therefore the scheduling of all the stages of material arriving at different geographical points at precise times is a highly significant problem. Moreover, the theoretical work in this area has larger ramifications for operational scheduling in many application areas. The scheduling models and algorithms presented and illustrated in the book will be done so in the context of extensive use of computer systems in a "real time context." The "just-in-time" and "real-time" theoretical work in the book will be of value and interest to many Engineers, Computer Scientists and Operations Research/Management Science researchers, students and practitioners. The book will survey and synthesize all the research in this topical area.