Bi-objective mean–variance method based on Chebyshev inequality bounds for multi-objective stochastic problems

Hannan Amoozad Mahdiraji, Seyed Hossein Razavi Hajiagha, Shide Sadat Hashemi, Edmundas Kazimieras Zavadskas

Research output: Contribution to journalArticle

3 Citations (Scopus)
6 Downloads (Pure)

Abstract

Multi-objective programming became more and more popular in real world decision making problems in recent decades. There is an underlying and fundamental uncertainty in almost all of these problems. Among different frameworks of dealing with uncertainty, probability and statistic-based schemes are well-known. In this paper, a method is developed to find some efficient solutions of a multi-objective stochastic programming problem. The method composed a process of transforming the stochastic multi-objective problem to a bi-objective equivalent using the concept of Chebyshev inequality bounds and then solving the obtained problem with a fuzzy set based approach. Application of the proposed method is examined on two numerical examples and the results are compared with different methods. These comparisons illustrated that the results are satisfying.

Original languageEnglish
Pages (from-to)1201 - 1217
Number of pages17
JournalRAIRO - Operations Research
Volume52
Issue number4-5
DOIs
Publication statusPublished - Oct 2018
Externally publishedYes

Bibliographical note

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Keywords

  • Multi-objective decision-making
  • stochastic programming
  • mean–variance criterion
  • fuzzy set based approach

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