Affiliations: [a] Department of Mathematics, South Tehran Branch, Islamic Azad University, Tehran, Iran
| [b] Department of Mathematics, Qaemshahr Branch, Islamic Azad University, Qaemshahr, Iran
| [c] Department of Mathematics, Science and Research Branch, Islamic Azad University, Tehran, Iran
Correspondence:
[*]
Corresponding author. A. Ebrahimnejad, Department of Mathematics, Qaemshahr Branch, Islamic Azad University,
Qaemshahr, Iran. E-mails: [email protected], [email protected].
Abstract: A transportation problem basically deals with the problem which aims to minimize the total transportation cost or maximize the total transportation profit of distributing a product from a number of sources or origins to a number of destinations. While, in general, most of the real life applications are modeled as a transportation problem (TP) with the multiple, conflicting and incommensurate objective functions. On the other hand, for some reason such as shortage of information, insufficient data or lack of evidence, the data of the mentioned problem are not always exact but can be fuzzy. This type of problem is called fuzzy multi-objective transportation problem (FMOTP). There are a few approaches to solve the FMOTPs. In this paper, a new fuzzy DEA based approach is developed to solve the Fully Fuzzy MOTPs (FFMOTPs) in which, in addition to parameters of the MOTPs, all of the variables are considered fuzzy. This approach considers each arc in a FFMOTP as a decision making unit which produces multiple fuzzy outputs using the multiple fuzzy inputs. Then, by using the concept of the common set of weights (CSW) in DEA, a unique fuzzy relative efficiency is defined for each arc. In the following, the unique fuzzy relative efficiency is considered as the only attribute for the arcs. In this way, a single objective fully fuzzy TP (FFTP) is obtained that can be solved using the existing standard algorithms for solving this kind of TPs. A numerical example is provided to illustrate the developed approach.
Keywords: Fuzzy multi-objective transportation problem, data envelopment analysis, fuzzy
arithmetic, common set of weights
