Description
Book SynopsisThis 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.
This textbook also offers:
Easy to follow descriptions of how to apply a wide variety
Table of Contents
The Process of Multicriteria Decision Analysis. Problem Structuring. Making Decisions under Conditions of Certainty with a Small Number of Alternatives. Multi-Objective Mathematical Programming. Probability Review. Modeling Preferences over Risky/Uncertain Outcomes. Modeling Methodologies for Generating Probabilistic Outcomes: Decision Trees and Influence Diagrams. Determining Probabilistic Inputs for Decision Models. The Use of Simulation for Decision Models
