RANDOM SEARCH IN OPTIMIZATION PROBLEMS FOR MULTIPARAMETER SYSTEMS,
FOREIGN TECHNOLOGY DIV WRIGHT-PATTERSON AFB OHIO
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It is only quite recently, roughly from the middle Fifties, that the theory of multiparameter automatic-optimization systems has appeared and received vigorous development. The outstanding characteristic of such systems is the search process, which ensures production of the information required to control the object. The first studies in this area were carried out, and the principal ideas were formulated by Professor A.A. Feldbaum in 1956. In recent years, two trends have developed in the field of automatic-optimization system theory they are characterized by different approaches to the nature of the search process. The first trend considers search as a fully regular process of information collection. Characteristic representatives of this trend are the very familiar Gauss-Seidel, gradient, steepest-descent, and other methods. The second trend originates with the Ashby Homeostat where the search process is random in nature, and the studies of A.G. Ivakhnenko, who demonstrated the importance of the randomness element for system selforganization. The present book is wholly concerned with the development of the latter trend, insofar as it applies to automatic optimization of multiparameter systems.
- Operations Research
- Manufacturing and Industrial Engineering and Control of Production Systems