Optimal Resource Allocation: With Practical Statistical by Igor A. Ushakov

By Igor A. Ushakov

A detailed ENGINEERING AND STATISTICAL method of optimum source ALLOCATION

Optimal source Allocation: With useful Statistical functions and thought features the applying of probabilistic and statistical tools utilized in reliability engineering through the various levels of lifestyles cycles of technical systems.

Bridging the space among reliability engineering and utilized arithmetic, the publication outlines diversified techniques to optimum source allocation and diverse functions of versions and algorithms for fixing real-world difficulties. moreover, the elemental historical past on optimization thought and numerous illustrative numerical examples are supplied. The ebook additionally features:

  • An assessment of assorted methods to optimum source allocation, from classical Lagrange the right way to glossy algorithms according to rules of evolution in biology
  • Numerous routines and case experiences from numerous components, together with communications, transportation, power transmission, and counterterrorism protection
  • The utilized equipment of optimization with a number of tools of optimum redundancy challenge options in addition to the numerical examples and statistical equipment had to remedy the problems
  • Practical suggestions, evaluations, and judgments on real-world purposes of reliability conception and solves functional difficulties utilizing mathematical types and algorithms

Optimal source Allocation is a must have consultant for electric, mechanical, and reliability engineers facing engineering layout and optimum reliability difficulties. furthermore, the booklet is great for graduate and PhD-level classes in reliability idea and optimization.

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Extra resources for Optimal Resource Allocation: With Practical Statistical Applications and Theory

Sample text

John Wiley & Sons. R. 1997. Reliability in Engineering Design. John Wiley & Sons. A. 1999. Statistical Reliability Engineering. John Wiley & Sons. J. 2003. Optimal Reliability Modeling: Principles and Applications. John Wiley & Sons. Pham, H. 2003. Handbook of Reliability Engineering. Springer. -L. 2006. Optimal Reliability Design: Fundamentals and Applications. Cambridge University Press. , ed. 2006. Computational Intelligence in Reliability Engineering. Evolutionary Techniques in Reliability Analysis and Optimization.

For instance, in spare parts allocation problems, a redundant group might be a set of identical units located throughout the entire system in quite different places. 1 Modular system and “informal” redundant groups for this system. 2 FORMULATION OF THE OPTIMAL REDUNDANCY PROBLEM WITH A SINGLE RESTRICTION The simplest (and, practically, the most often encountered) optimal redundancy problem is optimization of an objective function under a single constraint. Usually, the following two objective functions are considered: the cost of the total set of redundant units, C(X), and the probability of a failure-free system operation, R(X), where as above X = (x1, x2 .

1983. Textbook on Reliability Engineering (in Bulgarian). VMEI. , ed. 1985. Handbook on Reliability (in Russian). Radio i Svyaz. A. 1986. Reliability of Power Systems (in Russian). Nauka. A. 1987. Application of Graph Theory for Reliability Analysis (in German). Verlag Technik. A. 1988. Application of Graph Theory for Reliability Analysis (in Russian). Radio i Svyaz. A. 1988. Application of Graph Theory for Reliability Analysis (in German). Springer, Munchen-Vien. A. 1989. Reliability of Power Systems, 2nd ed.

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