نتایج جستجو برای: multiple objective quadratic fractional programming

تعداد نتایج: 1644371  

Journal: :the modares journal of electrical engineering 2007
reza key pour mahmood reza haghifam hossin seifi

this paper presents a framework for long term transmission expansion planning in competitive, electricity markets. transmission lines and phase shifters are taken into account as expansion options. maximization of the network users' benefits, with satisfying security constraints are considered as the criterion for transmission expansion planning. the elements of the objective function are the...

Journal: :Optimization Methods and Software 2013
John E. Mitchell Stephen Braun

The inclusion of transaction costs is an essential element of any realistic portfolio optimization. In this paper, we consider an extension of the standard portfolio problem in which convex transaction costs are incurred to rebalance an investment portfolio. In particular, we consider linear, piecewise linear, and quadratic transaction costs. The Markowitz framework of mean-variance efficiency ...

Journal: :Expert Syst. Appl. 2011
Zhou-Jing Wang Kevin W. Li Jianhui Xu

9 This article proposes an approach to handle multi-attribute decision making (MADM) 10 problems under the interval-valued intuitionistic fuzzy environment, in which both 11 assessments of alternatives on attributes (hereafter, referred to as attribute values) and 12 attribute weights are provided as interval-valued intuitionistic fuzzy numbers (IVIFNs). 13 The notion of relative closeness is e...

2015
O. E. Emam Manal A. Abdel-Fattah H. A. Suleiman

This paper presents a bi level large scale multi objective quadratic programming problem (BLLSMOQPP) with fuzzy parameters in the objective functions problem. In the first phase convert the fuzzy parameters of the problem to equivalent crisp problem to make it easy in solving. In the second phase use Taylor series to convert the quadratic problem to linear problem to be easy for solving with th...

2013
Karthik Natarajan Dongjian Shi Kim-Chuan Toh

The Quadratic Convex Reformulation (QCR) method is used to solve quadratic unconstrained binary optimization problems. In this method, the semidefinite relaxation is used to reformulate it to a convex binary quadratic program which is solved using mixed integer quadratic programming solvers. We extend this method to random quadratic unconstrained binary optimization problems. We develop a Penal...

2014
E. A. Youness O. E. Emam M. S. Hafez

We present an algorithm to solve a bi-level multi-objective fractional integer programming problem involving fuzzy numbers in the right-hand side of the constraints. The suggested algorithm combine the method of Taylor series together with the Kuhn Tucker conditions to solve fuzzy bi-level multi-objective fractional integer programming problem (FBLMOFIPP) then Gomory cuts are added till the int...

2013
P. Pandian M. Jayalakshmi

A new method namely, denominator objective restriction method based on simplex method is proposed for solving linear fractional programming problems. Further, another method namely, decomposition-restriction method based on decomposition principle and the denominator objective restriction method is proposed for obtaining an optimal fuzzy solution to the fully fuzzy linear fractional programming...

Journal: :ژورنال بین المللی پژوهش عملیاتی 0
m. saraj s. sadeghi

this paper presents a fuzzy goal programming (fgp) methodology for solving bi-level quadratic programming (blqp) problems. in the fgp model formulation, firstly the objectives are transformed into fuzzy goals (membership functions) by means of assigning an aspiration level to each of them, and suitable membership function is defined for each objectives, and also the membership functions for vec...

Journal: :European Journal of Operational Research 2001
Ami Arbel Pekka J. Korhonen

We introduce in this paper a new starting mechanism for multiple-objective linear programming (MOLP) algorithms. This makes it possible to start an algorithm from any solution in objective space. The original problem is first augmented in such a way that a given starting solution is feasible. The augmentation is explicitly or implicitly controlled by one parameter during the search process, whi...

2013

In section 4.1 a new class of higher order (F,ρi, σj)type I functions are introduced for a vector minimization problem. Various known generalized invex functions such as type-I, second order type-I and second order (F,ρi,σj)-type I are particular cases of higher order (F, ρi, σj)-type I functions. This class of functions is used to establish higher order duality results for a nondifferentiable ...

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