Optimal resource allocation with practical statistical applications and theory
A UNIQUE ENGINEERING AND STATISTICAL APPROACH TO OPTIMAL RESOURCE ALLOCATION Optimal Resource Allocation: With Practical Statistical Applications and Theory features the application of probabilistic and statistical methods used in reliability engineering during the different phases of life cycles of...
| Autor principal: | |
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| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Hoboken, N.J. :
Wiley
2013.
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| Edición: | 1st edition |
| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009627671706719 |
Tabla de Contenidos:
- Cover; Title page; Copyright page; Dedication; Contents; Preface; CHAPTER 1: Basic Mathematical Redundancy Models; 1.1 Types of Models; 1.2 Non-repairable Redundant Group with Active Redundant Units; 1.3 Non-repairable Redundant Group with Standby Redundant Units; 1.4 Repairable Redundant Group with Active Redundant Units; 1.5 Repairable Redundant Group with Standby Redundant Units; 1.6 Multi-level Systems and System Performance Estimation; 1.7 Brief Review of Other Types of Redundancy; 1.7.1 Two-Pole Structures; 1.7.2 Multi-Pole Networks; 1.7.3 Branching Structures
- 1.7.4 Functional Redundancy1.8 Time Redundancy; 1.9 Some Additional Optimization Problems; 1.9.1 Dynamic Redundancy; Chronological Bibliography of Main Monographs on Reliability Theory (with topics on Optimization); CHAPTER 2: Formulation of Optimal Redundancy Problems; 2.1 Problem Description; 2.2 Formulation of the Optimal Redundancy Problem with a Single Restriction; 2.3 Formulation of Optimal Redundancy Problems with Multiple Constraints; 2.3.1 Direct Optimal Redundancy Problem; 2.3.2 Inverse Optimal Redundancy Problem; 2.4 Formulation of Multi-Criteria Optimal Redundancy Problems
- 2.4.1 Direct Multi-Criteria Optimal Redundancy Problem2.4.2 Inverse Multi-Criteria Optimal Redundancy Problem; Chronological Bibliography; CHAPTER 3: Method of Lagrange Multipliers; Chronological Bibliography; CHAPTER 4: Steepest Descent Method; 4.1 The Main Idea of SDM; 4.2 Description of the Algorithm; 4.3 The Stopping Rule; 4.5 Approximate Solution; Chronological Bibliography; CHAPTER 5: Dynamic Programming; 5.1 Bellman's Algorithm; 5.2 Kettelle's Algorithm; 5.2.1 General Description of the Method; 5.2.2 Numerical Example; 5.2.3 Solving the Direct and Inverse Problems of Optimal Redundancy
- Chronological BibliographyCHAPTER 6: Universal Generating Functions; 6.1 Generating Function; 6.2 Universal GF (U-function); Chronological Bibliography; CHAPTER 7: Genetic Algorithms; 7.1 Introduction; 7.1.1 Initialization; 7.1.2 Selection; 7.1.3 Reproduction; 7.1.4 Termination; 7.2 Structure of Steady-State Genetic Algorithms; 7.3 Related Techniques; Chronological Bibliography; CHAPTER 8: Monte Carlo Simulation; 8.1 Introductory Remarks; 8.2 Formulation of Optimal Redundancy Problems in Statistical Terms; 8.3 Algorithm for Trajectory Generation; 8.4 Description of the Idea of the Solution
- 8.5 Inverse Optimization Problem8.5.1 System Successful Operation versus System Cost; 8.5.2 System Average Time to Failure versus System Cost; 8.6 Direct Optimization Problem; 8.6.1 System Cost versus Successful Operation; 8.6.2 System Cost versus Average Time to Failure; Chronological Bibliography; CHAPTER 9: Comments on Calculation Methods; 9.1 Comparison of Methods; 9.2 Sensitivity Analysis of Optimal Redundancy Solutions; CHAPTER 10: Optimal Redundancy with Several Limiting Factors; 10.1 Method of "Weighing Costs"; 10.2 Method of Generalized Generating Functions
- Chronological Bibliography
