Multiple criteria decision analysis for industrial engineering methodology and applications
This textbook presents methodologies and applications associated with multiple criteria decision analysis (MCDA), especially for those students with an interest in industrial engineering. With respect to methodology, the book covers (1) problem structuring methods; (2) methods for ranking multi-dime...
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| Format: | Book |
| Language: | English |
| Published: |
Boca Raton
CRC Press, Taylor & Francis Group
[2017]
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| Series: | Operations research series
12 |
| Subjects: | |
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| 008 | 221104 2017 flua bi 000 0 eng d | ||
| 020 | |a 9781498739825 | ||
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| 040 | |a UPNM |b eng |c UPNM |e rda | ||
| 090 | |a T 57 |b .E924 2017 | ||
| 100 | 1 | |a Evans, Gerald W. |c author | |
| 245 | 1 | 0 | |a Multiple criteria decision analysis for industrial engineering |b methodology and applications |c Gerald William Evans |
| 264 | 1 | |a Boca Raton |b CRC Press, Taylor & Francis Group |c [2017] | |
| 264 | 4 | |c ©2017 | |
| 300 | |a xiv, 800 pages |b illustrations |c 26 cm. | ||
| 336 | |a text |2 rdacontent | ||
| 337 | |a unmediated |2 rdamedia | ||
| 338 | |a volume |2 rdacarrier | ||
| 490 | 1 | |a Operations research series |v 12 | |
| 504 | |a Includes bibliographical references and index | ||
| 505 | 0 | |a Introduction -- Problem Structuring -- Making Decisions under Conditions of Certainty with a Small Number of Alternatives -- Goal Programming and Other Methodologies for Multiple Objective Optimization -- A Brief Review of Probability Theory -- Modeling Preferences over Risky/Uncertain Outcomes -- Modeling Methodologies for Generating Probabilistic Outcomes: Decision Trees and Influence Diagrams -- Determining Probabilistic Inputs for Decision Models -- Use of Simulation for Decision Models | |
| 520 | |a This textbook presents methodologies and applications associated with multiple criteria decision analysis (MCDA), especially for those students with an interest in industrial engineering. With respect to methodology, the book covers (1) problem structuring methods; (2) methods for ranking multi-dimensional deterministic outcomes including multiattribute value theory, the analytic hierarchy process, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), and outranking techniques; (3) goal programming,; (4) methods for describing preference structures over single and multi-dimensional probabilistic outcomes (e.g., utility functions); (5) decision trees and influence diagrams; (6) methods for determining input probability distributions for decision trees, influence diagrams, and general simulation models; and (7) the use of simulation modeling for decision analysis. | ||
| 592 | |a 32570 |b 5/12/16 |c RM337.69 |h Bookline | ||
| 650 | 0 | |a Industrial engineering | |
| 650 | 0 | |a Multiple criteria decision making | |
| 830 | 0 | |a Operations research series |v 12 | |
| 999 | |a vtls000057143 |c 102454 |d 102454 | ||