scholarly journals Interactive TOPSIS algorithms for solving multi-level non-linear multi-objective decision-making problems

Author(s):  
Ibrahim Baky
2004 ◽  
Vol 153 (1) ◽  
pp. 239-252 ◽  
Author(s):  
M.S. Osman ◽  
M.A. Abo-Sinna ◽  
A.H. Amer ◽  
O.E. Emam

2018 ◽  
Vol 13 (4) ◽  
pp. 7353-7370 ◽  
Author(s):  
MAHMOUD A ABO-SINNA ◽  
AZZA H AMER

TOPSIS (technique for order preference similarity to ideal solution) is considered one of the known classical multiple criteria decision making (MCDM) methods to solve bi-level non-linear fractional multi-objective decision making (BL-NFMODM) problems, and in which the objective function at each level is considered nonlinear and maximization type fractional functions. The proposed approach presents the basic terminology of TOPSIS approach and the construction of membership function for the upper level decision variable vectors, the membership functions of the distance functions from the positive ideal solution (PIS) and of the distance functions from the negative ideal solution (NIS). Thereafter a fuzzy goal programming model is adopted to obtain compromise optimal solution of BL-NFMODM problems. The proposed approach avoids the decision deadlock situations in decision making process and possibility of rejecting the solution again and again by lower level decision makers. The presented TOPSIS technique for BL-NFMODM problems is a new fuzzy extension form of TOPSIS approach suggested by Baky and Abo-Sinna (2013) (Applied Mathematical Modelling, 37, 1004-1015, 2013) which dealt with bi -level multi-objective decision making (BL-MODM) problems. Also, an algorithm is presented of the new fuzzy TOPSIS approach for solving BL-NFMODM problems. Finally, an illustrative numerical example is given to demonstrate the approach.


The motivation behind this paper is to propose method to obtain compromized solution of Non-Linear fractional Optimization Model. In this paper, Multi-level multi-objective fully quadratic fractional optimization model (ML-MOFQFOM) is studied in which various objective functions are involved, generally have conflicting nature. FGP approach is being used to solve ML-MOFQFOM involving triangular fuzzy numbers. This paper deals with the ML-MOFQFOM in which fuzzy model converted into deterministic form through the help of  -cuts where  is the combined choice of all objective functions. An algorithm and examples are also presented to validate the proposed method.


OPSEARCH ◽  
2001 ◽  
Vol 38 (5) ◽  
pp. 484-495 ◽  
Author(s):  
Mahmoud A. Abo-Sinna

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