multiobjective nonlinear programming
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2019 ◽  
Vol 42 (9) ◽  
pp. 1941-1951 ◽  
Author(s):  
Mohammad Reza Sardashti Birjandi ◽  
Farhad Shahraki ◽  
Kiyanoosh Razzaghi

2018 ◽  
Vol 17 (03) ◽  
pp. 941-968 ◽  
Author(s):  
Yong-Jun Liu ◽  
Wei-Guo Zhang

Using the central value operator and the semi-dispersion measure of fuzzy number, this paper proposes the definitions of the lower and upper semi-variances. A general multiperiod fuzzy portfolio optimization model with return demand on the portfolio at each period is proposed with the objectives of maximizing both terminal wealth and the cumulative diversification degree of portfolios over the whole investment horizon, and minimizing terminal risk. A fuzzy multiobjective nonlinear programming technique is applied to convert the proposed model into a single-objective model. A genetic algorithm (GA) is given to solve it. Besides, a numerical example is given to illustrate the application of the proposed model and the effectiveness of the designed algorithm.


2013 ◽  
Vol 23 (3) ◽  
pp. 387-417
Author(s):  
I. Husain ◽  
Rumana Mattoo

In this paper, a pair of mixed type symmetric dual multiobjective variational problems containing support functions is formulated. This mixed formulation unifies two existing pairs Wolfe and Mond-Weir type symmetric dual multiobjective variational problems containing support functions. For this pair of mixed type nondifferentiable multiobjective variational problems, various duality theorems are established under convexity-concavity and pseudoconvexity-pseudoconcavity of certain combination of functionals appearing in the formulation. A self duality theorem under additional assumptions on the kernel functions that occur in the problems is validated. A pair of mixed type nondifferentiable multiobjective variational problem with natural boundary values is also formulated to investigate various duality theorems. It is also pointed that our duality theorems can be viewed as dynamic generalizations of the corresponding (static) symmetric and self duality of multiobjective nonlinear programming with support functions.


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