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 language | English |
|---|---|
| Pages (from-to) | 1201 - 1217 |
| Number of pages | 17 |
| Journal | RAIRO - Operations Research |
| Volume | 52 |
| Issue number | 4-5 |
| DOIs | |
| Publication status | Published - Oct 2018 |
| Externally published | Yes |
Bibliographical note
Copyright © and Moral Rights are retained by the author(s) and/ or other copyright owners. A copy can be downloaded for personal non-commercial research or study, without prior permission or charge. This item cannot be reproduced or quoted extensively from without first obtaining permission in writing from the copyright holder(s). The content must not be changed in any way or sold commercially in any format or medium without the formal permission of the copyright holders.Keywords
- Multi-objective decision-making
- stochastic programming
- mean–variance criterion
- fuzzy set based approach