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

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

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.

Original languageEnglish (US)
Title of host publicationIEEE International Conference on Industrial Engineering and Engineering Management
PublisherIEEE Computer Society
Pages101-105
Number of pages5
ISBN (Electronic)9781479909865
DOIs
StatePublished - Nov 18 2014
Event2013 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2013 - Bangkok, Thailand
Duration: Dec 10 2013Dec 13 2013

Publication series

NameIEEE International Conference on Industrial Engineering and Engineering Management
ISSN (Print)2157-3611
ISSN (Electronic)2157-362X

Other

Other2013 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2013
Country/TerritoryThailand
CityBangkok
Period12/10/1312/13/13

All Science Journal Classification (ASJC) codes

  • Business, Management and Accounting (miscellaneous)
  • Industrial and Manufacturing Engineering
  • Safety, Risk, Reliability and Quality

Keywords

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

Fingerprint

Dive into the research topics of 'A new methodology for solving multi-objective stochastic optimization problems with independent objective functions'. Together they form a unique fingerprint.

Cite this