Selecting a Portfolio of Solar Energy Projects Using Multiattribute Preference Theory

Kamal Golabi, Craig W. Kirkwood and Alan Sicherman
Additional contact information
Kamal Golabi: Woodward-Clyde Consultants
Craig W. Kirkwood: Woodward-Clyde Consultants
Alan Sicherman: Woodward-Clyde Consultants

Management Science, 1981, vol. 27, issue 2, 174-189

Abstract: This article reports a procedure developed to assist the U.S. Department of Energy in selecting a portfolio of solar energy applications experiments. The procedure has also been used in other government procurements and appears to be applicable in a variety of project funding processes. The technical quality of each proposed applications experiment was summarized through the use of multiple evaluation measures, or attributes. These were combined into a single index of the overall technical quality of an experiment through the use of a multiattribute utility function. Recently derived results in measurable value theory were applied to derive an index of the overall technical quality of a portfolio of experiments. Budgetary and programmatic issues were handled through the use of constraints. This approach allowed the portfolio selection problem to be formulated as an integer linear program. Details of the application are presented, including a discussion of the data requirements and assessment procedure used. The portfolio selection procedure was successfully applied, and variations of it have been successfully used in four other solar energy procurements.

Keywords: research and development: project selection; utility/preference: multiattribute; programming: integer; applications (search for similar items in EconPapers)
Date: 1981
References: Add references at CitEc
Citations: View citations in EconPapers (35)

Downloads: (external link)
http://dx.doi.org/10.1287/mnsc.27.2.174 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:27:y:1981:i:2:p:174-189

Access Statistics for this article

More articles in Management Science from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().