Quantitative method for optimizing decision in project selection

The Indonesian economic and monetary condition recently has made changeover in many development policies including built environment. For example is the policy on selecting the built environmental project to be developed in the context of sustainable both environment and business. This research’s...

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Bibliographic Details
Main Authors: Utomo, Christiono, Murti, Farida
Format: Conference or Workshop Item
Language:English
Published: 2008
Subjects:
Online Access:http://eprints.usm.my/34684/
http://eprints.usm.my/34684/1/HBP24.pdf
Description
Summary:The Indonesian economic and monetary condition recently has made changeover in many development policies including built environment. For example is the policy on selecting the built environmental project to be developed in the context of sustainable both environment and business. This research’s report presents an approach to apply quantitative methods for optimizing decision in built environment project selection. The approach based on decision hierarchy that was obtained from 32 respondents in a survey study. It was completed with an implementation by a case study that is one of the biggest private construction projects in Indonesia to evaluate the application of that method. Model formulated and its implementation based on application of Analytic Hierarchy Process (AHP) method for multi criteria decision and Goal Programming (GP) method for multi objective decision and its optimization in a project selection. The result presents that complete design and permission; available funds; construction cost and probability to capital return are the most significant factors in decision. The implementation result demonstrates a process to select priorities each project to each decision and the optimization concludes that public park project, landfill sanitation project and supermarket project are selected and to be continued, but swimming pool is delayed and hospital is terminated. Follow up research is particularly required, primarily a study of decision support system and expert systems.