FUZZY MULTI-OBJECTIVE MULTI-INDEX TRANSPORTATION PROBLEM

Lohgaonkar M.H.¹*, Bajaj V.H.²*, Jadhav V.A.³, Patwari M.B.^4
1Department of Statistics, Dr. B. A. M. University, Aurangabad, MS
²Department of Statistics, Dr. B. A. M. University, Aurangabad, MS
³Departments of Statistics, Science College, Nanded, MS
⁴Department of Statistics, Dr. B. A. M. University, Aurangabad, MS
* Corresponding Author : vhbajaj@gmail.com

Received : -     Accepted : -     Published : 15-06-2010
Volume : 2     Issue : 1       Pages : 1 - 7
Adv Inform Min 2.1 (2010):1-7

Keywords : Transportation problem, multi-objective transportation problem, multi-index, linear membership function, non-linear membership function
Conflict of Interest : None declared

The aim of this paper is to present a fuzzy multi-objective multi-index transportation problem and develop multi-objective multi-index fuzzy programming model. This model cannot only satisfy more of the actual requirements of the integral system but is also more flexible than conventional transportation problems. Furthermore, it can offer more information to the decision maker (DM) for reference, and then it can raise the quality for decision-making. This paper, we use a special type of linear and non-linear membership functions to solve the multi-objective multi-index transportation problem. It gives an optimal compromise solution.

[1] Aneja V.P. and Nair K.P.K. (1979) Management Science, 25, 73-78.  
» CrossRef   » Google Scholar   » PubMed   » DOAJ   » CAS   » Scopus  

[2] Bellman R. E. and Zadeh L. A. (1970) Management science, 17, 141-164  
» CrossRef   » Google Scholar   » PubMed   » DOAJ   » CAS   » Scopus  

[3] Bit A. K., Biswal M.P. and Alam S. S. (1993) Industrial Engineering Journal XXII, No. 6, 8-12  
» CrossRef   » Google Scholar   » PubMed   » DOAJ   » CAS   » Scopus  

[4] Chanas S., Kolodzejczyk W. and Machaj A. (1984) Fuzzy set and systems, 13, 211-221.  
» CrossRef   » Google Scholar   » PubMed   » DOAJ   » CAS   » Scopus  

[5] Gwo-Hshiung Tzeng, Dusan Teodorovic and Ming-Jiu Hwang (1996) European Journal of Operations Research, 95, 62-72  
» CrossRef   » Google Scholar   » PubMed   » DOAJ   » CAS   » Scopus  

[6] Haley K. B. (1963) Operations Research 10, 448-463  
» CrossRef   » Google Scholar   » PubMed   » DOAJ   » CAS   » Scopus  

[7] Haley K. B. (1963) Operations Research 11, 369-379  
» CrossRef   » Google Scholar   » PubMed   » DOAJ   » CAS   » Scopus  

[8] Haley K. B. (1965) Operations Research 16, 471-474  
» CrossRef   » Google Scholar   » PubMed   » DOAJ   » CAS   » Scopus  

[9] Junginger W. (1993) European Journal of Operational Research 66, 353-371.  
» CrossRef   » Google Scholar   » PubMed   » DOAJ   » CAS   » Scopus  

[10] Oheigeartaigh M. (1982) fuzzy sets and systems, 8 , 235-243.  
» CrossRef   » Google Scholar   » PubMed   » DOAJ   » CAS   » Scopus  

[11] Prade H. (1980) Fuzzy sets. Theory and applications to policy analysis and information Systems. Plenum Press, new work, 155-170.  
» CrossRef   » Google Scholar   » PubMed   » DOAJ   » CAS   » Scopus  

[12] Rautman C.A. Reid R.A. and Ryder E.E. (1993) Operations Research 41, 459- 469  
» CrossRef   » Google Scholar   » PubMed   » DOAJ   » CAS   » Scopus  

[13] Verma Rakesh, Biswal M.P. and Biswas A. (1997) Fuzzy sets and systems 91, 37-43.  
» CrossRef   » Google Scholar   » PubMed   » DOAJ   » CAS   » Scopus  

[14] Waiel F. and Abd El- Wahed (2001) fuzzy sets and systems, 117, 26-33  
» CrossRef   » Google Scholar   » PubMed   » DOAJ   » CAS   » Scopus  

[15] Zimmermann H. J. (1978) fuzzy set and system 1, 45-55.  
» CrossRef   » Google Scholar   » PubMed   » DOAJ   » CAS   » Scopus