A new methodology for solving multi-objective stochastic optimization problems with independent objective functions

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Publication Details

Author list: Selcuklu S.B., Coit D.W., Felder F., Rodgers M., Wattanapongsakorn N.

Publisher: IEEE Computer Society

Publication year: 2014

Start page: 101

End page: 105

Number of pages: 5

ISBN: 9781479909865

ISSN: 2157-3611

eISSN: 2157-3611

URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84914127033&doi=10.1109%2fIEEM.2013.6962383&partnerID=40&md5=9901bb3e09d75694d9de3e9a7c8c2ec8

Languages: English-Great Britain (EN-GB)

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Abstract

For multi-objective optimization problems, a common solution methodology is to determine a Pareto optimal set. However, the Pareto optimal set only pertains to deterministic results. Our research aims to introduce Pareto Uncertainty Index which reflects the stochastic nature of the problem in the results. The proposed method is applied to a simplified Generation Expansion Planning problem to test the Pareto Uncertainty Index idea. ฉ 2013 IEEE.

Keywords

Generation Expansion Planning. Multi-objective optimization, Pareto optimality, Pareto Uncertainty Index (PUI)