Fuzzy Engineering Economics with Applications 1st Edition by Cengiz Kahraman ISBN 3642089747 9783642089749 by Cengiz Kahraman 9783540708094, 354070809X instant download after payment.

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ISBN 10: 3642089747 
ISBN 13: 9783642089749
Author: Cengiz Kahraman

Fuzzy set approaches are suitable to use when the modeling of human knowledge is necessary and when human evaluations are needed. Fuzzy set theory is recognized as an important problem modeling and solution technique. It has been studied ext- sively over the past 40 years. Most of the early interest in fuzzy set theory pertained to representing uncertainty in human cognitive processes. Fuzzy set theory is now - plied to problems in engineering, business, medical and related health sciences, and the natural sciences. This book handles the fuzzy cases of classical engineering e- nomics topics. It contains 15 original research and application chapters including different topics of fuzzy engineering economics. When no probabilities are available for states of nature, decisions are given under uncertainty. Fuzzy sets are a good tool for the operation research analyst facing unc- tainty and subjectivity. The main purpose of the first chapter is to present the role and importance of fuzzy sets in the economic decision making problem with the literature review of the most recent advances.

Fuzzy Engineering Economics with Applications 1st Table of contents:

1. Fuzzy Sets in Engineering Economic Decision-Making
2. Introduction
3. Fuzzy Concepts in Engineering Economy
4. The Time Value of Money
5. Simple and Compound Interest Rates
6. Nominal and Effective Interest Rates
7. Continuous Compounding
8. Inflated Interest Rate
9. Interest Factors
10. Bibliography for Fuzzy Engineering Economic Analysis
11. Conclusions
12. References
13. Fuzzy Present Worth Analysis with Correlated and Uncorrelated Cash Flows
14. Introduction
15. Economic Concepts Review
16. Time Value of Money
17. Cash Flow
18. Equivalence Formulae
19. Techniques of Comparison
20. Arithmetic Operations over Fuzzy Numbers That Are Not Independent
21. Example of Financial Calculations
22. Comparing and Ordering Fuzzy Numbers
23. Independent Numbers
24. Dependent Fuzzy Numbers
25. Decision Issues
26. NPW Example 1
27. Fuzzy Case with Partial Correlation
28. NPW Example 2
29. References
30. Optimization with Fuzzy Present Worth Analysis and Applications
31. Introduction
32. Introductory Information - Crisp Present Value and Fuzzy Numbers
33. Crisp Present Value
34. Basic Definitions - Fuzzy Numbers
35. Fuzzy Present Value - Concept and Applications
36. Fuzzy Data
37. Calculation of Fuzzy Present Value and Fuzzy Net Present Value
38. Interpretation of Fuzzy Present Value and Fuzzy Net Present Value
39. Fuzzy and Probabilistic Approach to the Present Value
40. Fuzzy Net Present Value as Objective in Project Selection Problems
41. Applications to the Valuation of Projects with Future Options
42. Fuzzy Net Present Value as Objective in Optimization Problems from the Industry
43. Fuzzy Net Present Value as an Objective in Spatial Games
44. Fuzzy Classification Based on Net Present Value
45. Conclusions
46. References
47. Fuzzy Equivalent Annual-Worth Analysis and Applications
48. Introduction
49. Fuzzy Equivalent Uniform Annual Value Method
50. Ranking Methods
51. The First Ranking Method
52. The Second Ranking Method
53. Application
54. Analysis Period is Infinite
55. Conclusions
56. References
57. Case Studies Using Fuzzy Equivalent Annual Worth Analysis
58. Use of the A/P Factor
59. EAW Example 1
60. Crisp Case
61. Fuzzy Case
62. EAW Example 2
63. Crisp Case
64. Fuzzy Case
65. EAW Example 3
66. References
67. Fuzzy Rate of Return Analysis and Applications
68. Introduction
69. Crisp Internal Rate of Return
70. Fuzzy Internal Rate of Return
71. Conclusions
72. References
73. On the Fuzzy Internal Rate of Return
74. Introduction
75. A New Method for Solving of Interval Equations
76. Fuzzy IRR for the Crisp Interval Cash Flows-Basics
77. A Numerical Solution of the Non-linear Fuzzy Problem of $IRR$ Calculation
78. Possible Applications
79. Conclusion
80. References
81. Fuzzy Benefit/Cost Analysis and Applications
82. Introduction
83. Fuzzy Benefit/Cost Ratio Analysis
84. Discrete Compounding
85. Continuous Compounding
86. Ranking Methods
87. Applications
88. Application of Fuzzy B/C in Case of Continuous Compounding
89. Conclusions
90. References
91. Fuzzy Replacement Analysis
92. Introduction
93. Classical Replacement Analysis
94. Fuzzy EUAW
95. A Numerical Application: Operating System Selection with Fuzzy Replacement Analysis
96. Conclusion
97. References
98. Depreciation and Income Tax Considerations under Fuzziness
99. Introduction
100. Depreciation Methods
101. Straight Line (SL) Depreciation
102. Sum-of-Years Digits Depreciation
103. Declining Balance (DB)
104. Comparison of Depreciation Methods
105. Consideration of Depreciation and Tax under Fuzzy Case
106. Sum of Years Digits Depreciation
107. Straight Line (SL) Depreciation
108. Conclusions
109. References
110. Effects of Inflation under Fuzziness and Some Applications
111. Introduction
112. Relation between Inflation and Interest
113. Inflation Measurement
114. Impact of Inflation
115. Tax Consideration
116. Future Worth Calculations Adjusted for Inflation
117. Capital Recovery Calculations Adjusted for Inflation
118. Fuzzy Inflation-Adjusted Interest Rate
119. Fuzzy Inflation Rates and Present Worth Calculations
120. Fuzzy Inflation Rates and Future Worth Calculations
121. Fuzzy Inflation Rates and Capital Recovery Calculations
122. Some Applications
123. Conclusions
124. References
125. Fuzzy Sensitivity Analysis and Its Application
126. Introduction
127. Sensitivity Analysis of Differentiation of the Choquet Integral as an Aggregation Function in Data-M
128. Interval Limited Choquet Integral
129. Differentiation of the Choquet Integral
130. Sensitivity Analysis as an Aggregation Function in Data-Mining
131. Differentiation of t-Conorm Integral
132. Interval Limited t-Conorm Integral
133. Differentiation of t-Conorm Integral
134. Comparison with Differentiation of t-Conorm Integrals in Sensitivity Analysis of Aggregation Functio
135. Apply to Credit Risk Analysis
136. Long Term Debt Rating Model
137. Simulation Result
138. Sensitivity Analysis Using Differentiation of the Choquet Integral
139. Conclusions
140. References
141. A Probabilistic Approach to Fuzzy Engineering Economic Analysis
142. Introduction
143. Probability Density Function from Membership Function
144. Proportional Probability Distribution
145. Uniform Probability Distribution
146. The Mellin Transform
147. Mellin Transforms for Selected Probability Functions
148. Engineering Economy Applications
149. Present Worth of Fuzzy Cash Flow Project
150. Comparing Alternatives with Fuzzy Cash Flow
151. Fuzzy Multi-attribute Automobile Selection (Dubois et al. 1988)
152. Concluding Remarks
153. References
154. Investment Analyses Using Fuzzy Decision Trees
155. Introduction
156. Decision Trees
157. Fuzzy Decision Trees
158. A Numerical Example
159. Investment Analysis Using Fuzzy Decision Trees
160. Conclusions
161. References
162. Fuzzy Multiobjective Evaluation of Investments with Applications
163. Introduction
164. Tool Steel Material Selection Problem
165. Subsethood Measure for Linguistic Representation of Fuzzy Numbers
166. Common Representation of Different Types of Local Criteria
167. Probabilistic Method For Fuzzy Values Comparison
168. Aggregation of Local Criteria and Aggregating Modes
169. Multiple Criteria Investment Project Evaluation in the Fuzzy Setting
170. Local Criteria Building
171. Ranking of Local Criteria
172. Numerical Evaluation of the Comparing Investment Projects
173. Hierarchical Structure of Local Criteria
174. Conclusions
175. References
176. Using Fuzzy Multi-attribute Data Mining in Stock Market Analysis for Supporting Investment Decisions
177. Introduction
178. Preliminaries
179. Basic Concepts
180. FSQL: A Language for Flexible Queries
181. Fuzzy Functional Dependencies and Gradual Functional Dependencies
182. Applying FSQL to Obtain Fuzzy Extended Dependencies
183. Fuzzy Extended Dependencies with FSQL Operators
184. Obtaining Fuzzy Extended Dependencies from a Database by Using FSQL
185. Applying a Fuzzy Data Mining Process to Stock Market
186. Earning Sceneries Identification and Expert’s Theory Formulation
187. Expert’s Theory Validation through FEDs Using FSQL
188. Conclusions
189. References
190. Soft Decision Support Systems for Evaluating Real and Financial Investments
191. Introduction
192. The Basics of Fuzzy Sets and Fuzzy Numbers
193. Fuzzy Sets
194. Fuzzy Numbers
195. The Extension Principle
196. Normative Measures on Fuzzy Numbers
197. Soft Decision Support for Financial Investments
198. Utility Function for Ranking Portfolios
199. Possibility Theory in Portfolio Selection
200. A Possibilistic Approach to the Portfolio Selection Problem
201. Algorithm for Solving the Possibilistic Portfolio Selection Problem
202. Soft Decision Support for Strategic Investment Planning
203. Practical Background
204. Possibility Theory in Strategic Investment Planning
205. Fuzzy Net Present Value Analysis
206. Fuzzy Real Option Valuation
207. References
208. Pricing Options, Forwards and Futures Using Fuzzy Set Theory
209. Introduction
210. Pricing Options
211. Binomial Model
212. Black-Scholes Model
213. Pricing Forwards and Futures
214. Crisp Pricing Forwards/Futures
215. Fuzzy Pricing Forwards/Futures
216. Summary and Conclusions
217. References
218. Fuzzy Capital Rationing Models
219. Introduction
220. Uncertainty-Based Approaches to Capital Rationing Models
221. Stochastic and Robust Approaches to Capital Rationing Model
222. Fuzzy Capital Rationing Models
223. Conclusions
224. References
225. Future Directions in Fuzzy Engineering Economics

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Tags: Cengiz Kahraman, Engineering, Economics