Quantitative Techniques for Decision Making in Construction

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Hong Kong University Press, Jun 1, 2004 - Technology & Engineering - 228 pages
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This is a text book as well as a reference book for decision making in construction. The book is written to serve undergraduates of construction-related programmes and postgraduate students undertaking construction management bridging courses. It contains mainly quantitative techniques used to assist decision making, including analytic hierarchy process (AHP), decision theories, conditional probabilities and the value of information, inventory modeling, dynamic programming, Monte-Carlo simulation, CYCLONE simulation modeling, information systems and process of decision making in construction. Plenty of real life examples are used to illustrate the theories, arguments and calculations. It is written in simple and easy to understand language. Readers will benefit from the book even by self studying because all the topics are described and developed in a logical and organized manner, from basic to complex. Moreover, the most up-to-date information on the development of AHP, simulation modelling, information systems and process of decision making are covered.
 

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Contents

PREFACE
1ANALYTIC HIERARCHY PROCESS I
2ANALYIC HIERARCHY PROCESS II
3DECISION THEORY USING EMV CRITERION
vii
4DECISION THEORY USING EUV CRITERION
v
5THE VALUE OF INFORMATION IN DECISION MODELS
xxi
6INVENTORY MODELLING I
xxix
7INVENTORY MODELLING II
xli
9SIMULATION I
14
10SIMULATION II
43
11INFORMATION SYSTEMS AND PROCESS OF DECISION MAKING
51
12PLANNING AND SCHEDULING DECISION
63
BIBLIOGRAPHY
81
Answers to Selected Exercise Questions
85
ABOUT THE AUTHORS
119
Copyright

8DYNAMIC PROGAMMING
lvii

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About the author (2004)

Dr S.L. Tang and Dr Ming Lu are faculty members in the Department of Civil and Structural Engineering of the Hong Kong Polytechnic University. Dr Irtishad U. Ahmad and Dr Syed M. Ahmed are faculty members in the Department of Construction Management of Florida International University in Miami. Ahmad is also the current Editor-in-Chief of the ASCE Journal of Management in Engineering.

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