TECHNICAL PAPERS
Jun 1, 2006

Contingency Planning in Project Selection Using Multiobjective Optimization and Chance Constraints

Publication: Journal of Infrastructure Systems
Volume 12, Issue 2

Abstract

We present a multiobjective optimization model for determining an efficient budget allocation for a portfolio of infrastructure projects. The model takes into account both the cost and the priority rank of each project while considering probabilistic constraints related to the available budget. A zero-one multiobjective optimization problem with chance constraints is developed and solved. This approach helps to more accurately take into account competing objectives such as cost and value of the funded projects, as well as budget risk to find a Pareto optimal set of project selection alternatives. We present numerical results based on infrastructure projects from a United States governmental agency in which we analyze the Pareto optimal set of solutions for this problem and test the working of the model with several cases that highlight budget contingencies needed in the face of random project costs.

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Information

Published In

Go to Journal of Infrastructure Systems
Journal of Infrastructure Systems
Volume 12Issue 2June 2006
Pages: 112 - 120

History

Received: May 25, 2004
Accepted: May 3, 2005
Published online: Jun 1, 2006
Published in print: Jun 2006

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Authors

Affiliations

Steven A. Gabriel, M.ASCE [email protected]
Assistant Professor, Project Management Program, Dept. Civil and Environmental Engineering and Applied Mathematics and Scientific Computation Program, Univ. of Maryland, College Park, MD 20742. (corresponding author). E-Mail: [email protected]
Javier F. Ordóñez [email protected]
Ph.D. Candidate, Project Management Program, Dept. of Civil and Environmental Engineering, Univ. of Maryland, College Park, MD 20742. E-Mail: [email protected]
José A. Faria [email protected]
Adjunct Professor, Project Management Program, Dept. of Civil and Environmental Engineering and The Institute for Systems Research, Univ. of Maryland, College Park, MD 20742. E-Mail: [email protected]

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