Network flow optimization analyzes optimization problems on networks; hence, network optimization is reflected in many application fields including transportation, telecommunication, computer networking, financial planning, logistics and supply chain management, energy systems, etc. However, to date, most network optimization problems that have been studied are static network optimization problems. But real world networks are time-varying in essence, and therefore any flow within a network must take a certain amount of time to traverse an arc. Moreover, the parameters of real world networks may change over time. Problems such as how to plan and control the transmission of flow becomes very important, because waiting at a node, or traveling along a particular arc with different speed, may allow one to catch the best timing along the path; thus, achieving the objective and changing the decision making process. It should be noted that there are a host of decision making problems in practice that should be formulated as optimization models on time-varying networks. The express purpose of TIME-VARYING NETWORK OPTIMIZATION is to describe, in a unified and self-contained manner, a series of models, propositions, and algorithms developed in recent years on time-varying networks. References and discussions on relevant problems and studies that have appeared in the literature are integrated in the book. The book consists of eight chapters, in which the following problems are formulated and examined: (1) the shortest path problem, (2) minimum-spanning tree problem, (3) maximum flow problem, (4) minimum cost flow problem, (5)maximum capacity path problem, (6) quickest path problem, (7) multi-criteria problem, and (8) the generalized flow problem. The time-varying traveling salesman problem and the Chinese postman problem are presented in a chapter together with the time-varying generalized problem. While these topics will be described all within the framework of time-varying networks, our plan is to make each chapter relatively self-contained so that each can be read separately. The book will be useful for researchers, practitioners, graduate students and senior undergraduates, as a unified reference and textbook on time-varying network optimization. While the book describes the structure of the algorithms, the authors also have developed the software that implements the algorithms. This software can be made available for academic study purposes upon request.

This text describes a series of models, propositions, and algorithms developed in recent years on time-varying networks. References and discussions on relevant problems and studies that have appeared in the literature are integrated in the book. Its eight chapters consider problems including the shortest path problem, the minimum-spanning tree problem, the maximum flow problem, and many more. The time-varying traveling salesman problem and the Chinese postman problem are presented in a chapter together with the time-varying generalized problem. While these topics are examined within the framework of time-varying networks, each chapter is self-contained so that each can be read - and used - separately.

A major technological trend for large database systems has been the introduction of ever-larger mass storage systems. This allows computing centers and business data processing installations to maintain on line their program libraries, less frequently used data files, transaction logs and backup copies under unified system control. Tapes, disks and drums are classical examples of mass storage media. The more recent IBM 3851 Mass Storage Facility, part of the IBM 3850 Mass Storage System, represents a new direction in mass storage development, namely, it is two-dimensional. With the maturity of magnetic bubble technology, more sophisticated, massive, multi-trillion-bit storage systems are not far in the future. While large in capacity, mass storage systems have in general relatively long access times. Since record access probabilities are usually not uniform, various algorithms have been devised to position the records to decrease the average access time. The first two chapters of this book are devoted mainly to such algorithmic studies in linear and two-dimensional mass storage systems. In the third chapter, we view the bubble memory as more than a storage medium. In fact, we discuss different structures where routine operations, such as data rearrangement, sorting, searching, etc., can be done in the memory itself, freeing the CPU for more complicated tasks. The problems discussed in this book are combinatorial in nature.

This book constitutes the proceedings of the Second Annual International Conference on Computing and Combinatorics, COCOON '96, held in June 1996 in Hong Kong.
The 44 papers presented in the book in revised version were carefully selected from a total of 82 submissions. They describe state-of-the-art research results from various areas of theoretical computer science, combinatorics related to computing, and experimental analysis of algorithms; computational graph theory, computational geometry, and networking issues are particularly well-presented.