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Multiple Criteria Decision Analysis for Industrial Engineering - Methodology and Applications (Hardcover)
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Multiple Criteria Decision Analysis for Industrial Engineering - Methodology and Applications (Hardcover)
Series: Operations Research Series
Expected to ship within 5 - 10 working days
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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. This textbook also
offers: * Easy to follow descriptions of how to apply a wide
variety of MCDA techniques * Specific examples involving multiple
objectives and/or uncertainty/risk of interest to industrial
engineers * A section on outranking techniques ; this group of
techniques, which is popular in Europe, is very rarely mentioned as
a methodology for MCDA in the United States * A chapter on
simulation as a useful tool for MCDA, including ranking &
selection procedures. Such material is rarely covered in courses in
decision analysis * Both material review questions and problems at
the end of each chapter . Solutions to the exercises are found in
the Solutions Manual which will be provided along with PowerPoint
slides for each chapter. The methodologies are demonstrated through
the use of applications of interest to industrial engineers,
including those involving product mix optimization, supplier
selection, distribution center location and transportation
planning, resource allocation and scheduling of a medical clinic,
staffing of a call center, quality control, project management,
production and inventory control,and so on. Specifically,
industrial engineering problems are structured as classical
problems in multiple criteria decision analysis, and the relevant
methodologies are demonstrated.
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