Robust programming problems based on the mean-variance model including uncertainty factors

Takashi Hasuike, Hiroaki Ishii

Research output: Contribution to journalConference article

Abstract

This paper considers robust programming problems based on the mean-variance model including uncertainty sets and fuzzy factors. Since these problems are not well-defined problems due to fuzzy factors, it is hard to solve them directly. Therefore, introducing chance constraints, fuzzy goals and possibility measures, the proposed models are transformed into the deterministic equivalent problems. Furthermore, in order to solve these equivalent problems efficiently, the solution method is constructed introducing the mean-absolute deviation and doing the equivalent transformations.

Original languageEnglish
Pages (from-to)224-235
Number of pages12
JournalAIP Conference Proceedings
Volume1089
DOIs
Publication statusPublished - 2009 Apr 13
Externally publishedYes
EventInternational MultiConference of Engineers and Computer Scientists, IMECS 2008 - Hong Kong, China
Duration: 2008 Mar 192008 Mar 21

Keywords

  • Fuzzy optimization
  • Mean-variance model
  • Nonlinear programming
  • Robust optimization

ASJC Scopus subject areas

  • Physics and Astronomy(all)

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