Belief linear programming

Authors:
Hatem Masri;Fouad Ben Abdelaziz
Affiliations:
Faculty of Economics, Management and Information Systems, University of Nizwa, P.O. Box 33, Nizwa, Oman;Engineering System Management Graduate Program, College of Engineering, American University of Sharjah, P.O. Box 26666, Sharjah, United Arab Emirates
Venue:
International Journal of Approximate Reasoning
Year:
2010

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Abstract

This paper proposes solution approaches to the belief linear programming (BLP). The BLP problem is an uncertain linear program where uncertainty is expressed by belief functions. The theory of belief function provides an uncertainty measure that takes into account the ignorance about the occurrence of single states of nature. This is the case of many decision situations as in medical diagnosis, mechanical design optimization and investigation problems. We extend stochastic programming approaches, namely the chance constrained approach and the recourse approach to obtain a certainty equivalent program. A generic solution strategy for the resulting certainty equivalent is presented.