Rapid methodological progress is now taking place in the USSR in the solution of the problems of developing both society and economy. A considerable proportion of the total methodological problems of the USSR economy are dealt with in the present monograph. This work is intended for economists, managers and specialists in methodology, sociology and applied mathematics, and it may also be useful to researchers into operations as well as to politicians, philosophers and wide circles of readers interested in the present and future problems of the USSR economy. Readers will find here, I hope, answers to many questions. At the same time this work can be used as a manual for students and post-graduate students investigating countries with centrally planned economies. For his monograph the author has used the material originally developed for a special course of lectures called "Macromodels of Planning". Some sections of the book correspond to the subjects of courses on "Mathematical Programming" and "Operations Research" as well as to the subjects of special courses on "Methods of Vector Optimization", "Stochastic Programming", "Parametric Programming" and "Decomposition Methods of Programming", read by the author from 1971 to 1976 to the graduates and post graduates of the department of applied mathematics and management processes at Leningrad University.
The problem of selection of alternatives or the problem of decision making in the modern world has become the most important class of problems constantly faced by business people, researchers, doctors and engineers. The fields that are almost entirely focused on conflicts, where applied mathematics is successfully used, are law, military science, many branches of economics, sociology, political science, and psychology. There are good grounds to believe that medicine and some branches of biology and ethics can also be included in this list. Modern applied mathematics can produce solutions to many tens of classes of conflicts differing by the composition and structure of the participants, specific features of the set of their objectives or interests, and various characteristics of the set of their actions, strategies, behaviors, controls, and decisions as applied to various principles of selection or notions of decision optimization. The current issues of social and economic systems involve the necessity to coordinate and jointly optimize various lines of development and activities of modern society. For this reason, the decision problems arising in investigation of such systems are versatile, which shows up not only in the multiplicity of participants, their interests and complexity of reciprocal effects, but also in the laborious development of social utility criteria for a variety of indices and versatile objectives. The efficient decision methods for such complex systems can be developed only the basis of specially developed mathematical tools. Contents: Social Choice Problems; Vector Optimization; Infinite-Valued Programming Problems; Stochastic Programming; Discrete Programming; Fundamentals of Decision Making; Multicriterion Optimization Problems; Decision Making Under Incomplete Information; Multicriterion Elements of Optimization Theory; Decision Models; Decision Models Under Fuzzy Information; The Applied Mathematical Model for Conflict Management. Readership: Undergraduates, graduate students, professionals and researchers in applied mathematics.
This monograph defines the notion of a ?system? by reference to those systems which exhibit goal-oriented behavior and utilize the notion of decision making and controls. Such systems allow for phenomenological description and fix the nature of causal transformations of input effects into output quantities. The study of consequences of the fact that the systems possess some properties constitutes the content of systems optimization methodology which goes beyond the scope of descriptive classification of systems.Chapter 1 deals with philosophical problems of systems methodology. An attempt is made to systematize and analyze the problems of scientific methodology as applied to systems modeling methodology which is viewed as the most general concept utilized in modern science.Chapter 2 focuses on problems of qualitative analysis in natural and social sciences. Attention is drawn to problems of measurement theory and quantitative analysis of systems.Approaches and methods of systems analysis and synthesis form the central portion of the book. Much study is given to the methods of systems decomposition, an integration using both discrete and continuous descriptions of objects, processes, and phenomena. Examples of complex goal-oriented systems are also provided.The remaining part of the book is largely centered around the methodology of multiobjective systems optimization.
This book is devoted to the problems of stochastic (or probabilistic) programming. The author took as his basis the specialized lectures which he delivered to the graduates from the economic cybernetics department of Leningrad University beginning in 1967. Since 1971 the author has delivered a specialized course on Stochastic Programming to the gradu ates from the faculty of applied mathematics/management processes at Leningrad University. The present monograph consists of seven chapters. In Chapter I, which is of an introductory character, consideration is given to the problems of uncertainty and probability, used for modelling complicated systems. Fundamental indications for the classification of stochastic pro gramming problems are given. Chapter II is devoted to the analysis of various models of chance-constrained stochastic programming problems. Examples of technological and applied economic problems of management with chance-constraints are given. In Chapter III two-stage stochastic programming problems are investigated, various models are given, and these models are qualitatively analyzed. In the conclusion of the chapter consideration is given to: the transport problem with random data, the problem of the determination of production volume, and the problem of planning the flights of aircraft as two-stage stochastic programming problems. Multi-stage stochastic programming problems are investigated in Chapter IV. The dependencies between prior and posterior decision rules and decision distributions are given. Dual problems are investigated.
The vast territory from Asia to Eastern Europe that was part of or under the influence of the Soviet Union comprised cities, which have undergone profound changes in the last twenty years. The opening of borders combined with the affirmation of market dynamics, privatization and concentration of wealth, and the emergence of nationalist discourses have upset ways of life and value systems leaving deep marks on the urban landscape and organization of living space. These essays take an in-depth look at specific cases – Samarkand, Sarajevo, Berlin, Almaty, and others – to offer a complex picture of the transformations affecting the post-communist city.
This book is devoted to the problems of stochastic (or probabilistic) programming. The author took as his basis the specialized lectures which he delivered to the graduates from the economic cybernetics department of Leningrad University beginning in 1967. Since 1971 the author has delivered a specialized course on Stochastic Programming to the gradu ates from the faculty of applied mathematics/management processes at Leningrad University. The present monograph consists of seven chapters. In Chapter I, which is of an introductory character, consideration is given to the problems of uncertainty and probability, used for modelling complicated systems. Fundamental indications for the classification of stochastic pro gramming problems are given. Chapter II is devoted to the analysis of various models of chance-constrained stochastic programming problems. Examples of technological and applied economic problems of management with chance-constraints are given. In Chapter III two-stage stochastic programming problems are investigated, various models are given, and these models are qualitatively analyzed. In the conclusion of the chapter consideration is given to: the transport problem with random data, the problem of the determination of production volume, and the problem of planning the flights of aircraft as two-stage stochastic programming problems. Multi-stage stochastic programming problems are investigated in Chapter IV. The dependencies between prior and posterior decision rules and decision distributions are given. Dual problems are investigated.
Rapid methodological progress is now taking place in the USSR in the solution of the problems of developing both society and economy. A considerable proportion of the total methodological problems of the USSR economy are dealt with in the present monograph. This work is intended for economists, managers and specialists in methodology, sociology and applied mathematics, and it may also be useful to researchers into operations as well as to politicians, philosophers and wide circles of readers interested in the present and future problems of the USSR economy. Readers will find here, I hope, answers to many questions. At the same time this work can be used as a manual for students and post-graduate students investigating countries with centrally planned economies. For his monograph the author has used the material originally developed for a special course of lectures called "Macromodels of Planning". Some sections of the book correspond to the subjects of courses on "Mathematical Programming" and "Operations Research" as well as to the subjects of special courses on "Methods of Vector Optimization", "Stochastic Programming", "Parametric Programming" and "Decomposition Methods of Programming", read by the author from 1971 to 1976 to the graduates and post graduates of the department of applied mathematics and management processes at Leningrad University.
This monograph defines the notion of a ?system? by reference to those systems which exhibit goal-oriented behavior and utilize the notion of decision making and controls. Such systems allow for phenomenological description and fix the nature of causal transformations of input effects into output quantities. The study of consequences of the fact that the systems possess some properties constitutes the content of systems optimization methodology which goes beyond the scope of descriptive classification of systems.Chapter 1 deals with philosophical problems of systems methodology. An attempt is made to systematize and analyze the problems of scientific methodology as applied to systems modeling methodology which is viewed as the most general concept utilized in modern science.Chapter 2 focuses on problems of qualitative analysis in natural and social sciences. Attention is drawn to problems of measurement theory and quantitative analysis of systems.Approaches and methods of systems analysis and synthesis form the central portion of the book. Much study is given to the methods of systems decomposition, an integration using both discrete and continuous descriptions of objects, processes, and phenomena. Examples of complex goal-oriented systems are also provided.The remaining part of the book is largely centered around the methodology of multiobjective systems optimization.
The problem of selection of alternatives or the problem of decision making in the modern world has become the most important class of problems constantly faced by business people, researchers, doctors and engineers. The fields that are almost entirely focused on conflicts, where applied mathematics is successfully used, are law, military science, many branches of economics, sociology, political science, and psychology. There are good grounds to believe that medicine and some branches of biology and ethics can also be included in this list. Modern applied mathematics can produce solutions to many tens of classes of conflicts differing by the composition and structure of the participants, specific features of the set of their objectives or interests, and various characteristics of the set of their actions, strategies, behaviors, controls, and decisions as applied to various principles of selection or notions of decision optimization. The current issues of social and economic systems involve the necessity to coordinate and jointly optimize various lines of development and activities of modern society. For this reason, the decision problems arising in investigation of such systems are versatile, which shows up not only in the multiplicity of participants, their interests and complexity of reciprocal effects, but also in the laborious development of social utility criteria for a variety of indices and versatile objectives. The efficient decision methods for such complex systems can be developed only the basis of specially developed mathematical tools. Contents: Social Choice Problems; Vector Optimization; Infinite-Valued Programming Problems; Stochastic Programming; Discrete Programming; Fundamentals of Decision Making; Multicriterion Optimization Problems; Decision Making Under Incomplete Information; Multicriterion Elements of Optimization Theory; Decision Models; Decision Models Under Fuzzy Information; The Applied Mathematical Model for Conflict Management. Readership: Undergraduates, graduate students, professionals and researchers in applied mathematics.
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