# A goal programming approach for multi-objective linear fractional programming problem with LR possibilistic variables

Author(s):
Hamiden Abd El- Wahed Khalifa ◽
Pavan Kumar
2020 ◽
Vol 14 (3) ◽
pp. 219-233
Author(s):
C. Veeramani ◽
S. Sharanya ◽

2017 ◽
Vol 51 (1) ◽
pp. 199-210 ◽
Author(s):
G. R. Jahanshahloo ◽
B. Talebian ◽

2012 ◽
Vol 2 (2) ◽
pp. 77-80
Author(s):
Durga Banerjee ◽
Surapati Pramanik

This paper deals with goal programming approach to chance constrained multi-objective linear fractional programming problem based on Taylorâ€™s series approximation. We consider the constraints with right hand parameters as the random variables of known mean and variance. The random variables are transformed into standard normal variables with zero mean and unit variance. We convert the chance constraints with known confidence level into equivalent deterministic constraints. The goals of linear fractional objective functions are determined by optimizing it subject to the equivalent deterministic system constraints. Then the fractional objective functions are transformed into equivalent linear functions at the optimal solution point by using first order Taylor polynomial series. In the solution process, we use three minsum goal programming models and identify the most compromise optimal solution by using Euclidean distance function.

2011 ◽
Vol 25 (11) ◽
pp. 34-40 ◽
Author(s):
Surapati Pramanik ◽
Partha Pratim Dey

2012 ◽
Vol 2 (2) ◽
pp. 77-80 ◽
Author(s):
Durga Banerjee ◽
Surapati Pramanik

This paper deals with goal programming approach to chance constrained multi-objective linear fractional programming problem based on Taylorâ€™s series approximation. We consider the constraints with right hand parameters as the random variables of known mean and variance. The random variables are transformed into standard normal variables with zero mean and unit variance. We convert the chance constraints with known confidence level into equivalent deterministic constraints. The goals of linear fractional objective functions are determined by optimizing it subject to the equivalent deterministic system constraints. Then the fractional objective functions are transformed into equivalent linear functions at the optimal solution point by using first order Taylor polynomial series. In the solution process, we use three minsum goal programming models and identify the most compromise optimal solution by using Euclidean distance function.

2014 ◽
Vol 48 (1) ◽
pp. 109-122 ◽
Author(s):
Muthukumar Sumathi

2020 ◽
Author(s):
Rizk M. Rizk-Allah ◽
Mahmoud A. Abo-Sinna

2014 ◽
Vol 5 (3) ◽
pp. 210
Author(s):
Ali Payan ◽
Abbas Ali Noora

Author(s):
Indrani Maiti ◽
Tarni Mandal ◽
Surapati Pramanik