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Systems Optimization Methodology - Part II (System Optimization Methodology)

Kolbin, Vyacheslav V

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ضمانت فایل
پشتیبانی

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مشخصات کتاب

نویسنده
Kolbin, Vyacheslav V
سال انتشار
۱۹۹۹
فرمت
DJVU
زبان
انگلیسی
حجم فایل
۹٫۹ مگابایت

دربارهٔ کتاب

This monograph deals with theoretical fundamentals and numerical methods of optimizing nondetermined models of systems. The main body of this work is devoted to investigation and optimization of system models under incomplete information. Much consideration is given to one-, two- and multistage problems of stochastic programming, solution methods and problems of solution stability. Optimization problems with fuzzy variables and optimization problems in function spaces are investigated. Examples are given for implementation of specific models of optimization under incomplete information. The book is based on lectures given by the author since 1965 for undergraduates and postgraduates at St Petersburg State University This monograph deals with theoretical fundamentals and numerical methods of optimizing nondetermined models of systems. The main body of this work is devoted to investigation and optimization of system models under incomplete information. Much consideration is given to one-, two- and multistage problems of stochastic programming, solution methods and problems of solution stability. Optimization problems with fuzzy variables and optimization problems in function spaces are investigated. Examples are given for implementation of specific models of optimization under incomplete information.The book is based on lectures delivered by the author since 1965 for undergraduates and postgraduates at St. Petersburg (Leningrad) State University. This monograph deals with theoretical fundamentals and numerical methods of optimizing nondetermined models of systems. The main body of the work is devoted to investigation and optimization of system models under incomplete information. Covering the subject of systems optimization methodology, this work discusses areas including: philosophical problems of the methodology for systems modelling; decomposition and aggregation; and vector optimization. Nowadays the deterministic approach prevails in investigation and optimization for purposes of planning, designing and managing complex systems in economy, technology and defense.

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