An efficient computational approach for solving type-2 intuitionistic fuzzy numbers based Transportation Problems

被引:38
作者
Ebrahimnejad, Ali [1 ]
Luis Verdegay, Jose [2 ]
机构
[1] Islamic Azad Univ, Dept Math, Qaemshahr Branch, POB 163, Qaemshahr, Iran
[2] Univ Granada, Dept Comp Sci & Artificial Intelligence, Granada 18014, Spain
关键词
Intuitionistic fuzzy transportation problem; Triangular intuitionistic fuzzy number; Accuracy function; LINEAR-PROGRAMMING APPROACH; MATRIX GAMES; SETS; OPTIMIZATION; MODELS;
D O I
10.1080/18756891.2016.1256576
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper is concerned with the solution procedure of a Transportation Problem in which costs are triangular intuitionistic fuzzy numbers (TIFN) and availabilities and demands are taken as exact numerical values. According to the existing solution approach, TIFN are first ordered by using an accuracy function defined on score functions for membership and non-membership functions of TIFN. Then this ordering is used to develop methods for finding an initial basic feasible solution and the optimal solution of intuitionistic fuzzy Transportation Problems in terms of triangular intuitionistic fuzzy numbers. This solution approach, in spite of its merits, requires a lot of fuzzy arithmetic operations, such as additions and subtractions of TIFN, as well as a lot of comparisons on TIFN. In this paper an efficient computational solution approach is proposed for solving intuitionistic fuzzy Transportation Problems based on classical transportation algorithms to overcome the shortcomings of the aforementioned solution approach. In the approach here presented, the comparison of triangular intuitionistic fuzzy costs is done once and all arithmetic operations are done on real numbers. Finally, for the sake of illustration, two intuitionistic fuzzy Transportation Problems are solved herein to demonstrate the usages and advantages of the proposed solution approach.
引用
收藏
页码:1154 / 1173
页数:20
相关论文
共 39 条
[1]  
Antony R.J.P., 2014, International Journal of Computing Algorithm, V03, P590
[2]   INTUITIONISTIC FUZZY-SETS [J].
ATANASSOV, KT .
FUZZY SETS AND SYSTEMS, 1986, 20 (01) :87-96
[3]  
Basirzadeh H., 2011, Appl. Math. Sci, V5, P1549
[4]   Image Thresholding Computation Using Atanassov's Intuitionistic Fuzzy Sets [J].
Bustince, H. ;
Barrenechea, E. ;
Pagola, M. ;
Orduna, R. .
JOURNAL OF ADVANCED COMPUTATIONAL INTELLIGENCE AND INTELLIGENT INFORMATICS, 2007, 11 (02) :187-194
[5]   Models and algorithms for the optimization of signal settings on urban networks with stochastic assignment models [J].
Cascetta, Ennio ;
Gallo, Mariano ;
Montella, Bruno .
ANNALS OF OPERATIONS RESEARCH, 2006, 144 (01) :301-328
[6]   An application of intuitionistic fuzzy sets in medical diagnosis [J].
De, SK ;
Biswas, R ;
Roy, AR .
FUZZY SETS AND SYSTEMS, 2001, 117 (02) :209-213
[7]  
Dinagar D. S., 2006, INT J ALGORITHMS COM, V2, P65
[8]   New method for solving Fuzzy transportation problems with LR flat fuzzy numbers [J].
Ebrahimnejad, Ali .
INFORMATION SCIENCES, 2016, 357 :108-124
[9]   Fuzzy linear programming approach for solving transportation problems with interval-valued trapezoidal fuzzy numbers [J].
Ebrahimnejad, Ali .
SADHANA-ACADEMY PROCEEDINGS IN ENGINEERING SCIENCES, 2016, 41 (03) :299-316
[10]   Note on "A fuzzy approach to transport optimization problem" [J].
Ebrahimnejad, Ali .
OPTIMIZATION AND ENGINEERING, 2016, 17 (04) :981-985