Six contributors from Japanese universities explore the basic theory and methodology of control and decision making in systems that either contain many variables or have some special characteristics such as multiple subsystems or control stations, a decentralized and/or hierarchical information stru

In its thousands of years of history, mathematics has made an extraordinary ca reer. It started from rules for bookkeeping and computation of areas to become the language of science. Its potential for decision support was fully recognized in the twentieth century only, vitally aided by the evolution of computing and communi cation technology. Mathematical optimization, in particular, has developed into a powerful machinery to help planners. Whether costs are to be reduced, profits to be maximized, or scarce resources to be used wisely, optimization methods are available to guide decision making. Opti mization is particularly strong if precise models of real phenomena and data of high quality are at hand - often yielding reliable automated control and decision proce dures. But what, if the models are soft and not all data are around? Can mathematics help as well? This book addresses such issues, e. g. , problems of the following type: - An elevator cannot know all transportation requests in advance. In which order should it serve the passengers? - Wing profiles of aircrafts influence the fuel consumption. Is it possible to con tinuously adapt the shape of a wing during the flight under rapidly changing conditions? - Robots are designed to accomplish specific tasks as efficiently as possible. But what if a robot navigates in an unknown environment? - Energy demand changes quickly and is not easily predictable over time. Some types of power plants can only react slowly.

This book is the record of papers presented at the Conference on Directions in Decentralized Control, Many-Person Optimization, and Large-Scale Systems held at the Colonial Hilton Inn, Wakefield, Massachusetts from September 1-3, 1975. Our motivation for organizing such a conference was two fold. Firstly, the last few years have seen a great deal of activity in the field of Large-Scale Systems Theory and it has been certainly one of the dominant themes of research in the disciplines of Systems and Control Theory. It therefore seemed appropriate to try and take stock of what had been accomplished and also try to "invent"l the future directions of research in this field. Secondly, the 6th World IFAC Conference was being held in Cambridge, Massachusetts the week earlier and it provided an ideal opportunity for taking advantage of the presence of a large number of specialists from all parts of the world to organize a small conference where a free exchange of ideas could take place. It is left to the readers of this volume to judge to what extent we have been successful in our above mentioned goals. There is no accepted definition of what constitutes a "large scale system" nor what large-scale system theory is. While this diversity does suggest that the field {whatever it may turn out to be} is in a state of flux, it does not necessarily imply chaos.

This book discusses key issues in the planning and operation of large-scale integrated energy systems (LSIES). It establishes individual-based models for LSIES and develops multi-objective optimization algorithms and multi-attribute decision making support systems, which are applied to the planning and optimal operation of LSIES. It is a valuable reference work for researchers, students and engineers who are interested in energy systems, operation research and decision theory.