نتایج جستجو برای: variance approach portfolio optimization problem is a quadratic programming model and
تعداد نتایج: 20885636 فیلتر نتایج به سال:
in this thesis, we consider a mathematical model of cancer with completely unknown parameters. we study the stability of critical points which are biologically admissible. then we consider a control on the system and introduce situations at which solutions are attracted to critical points and so the cancer disease has auto healing. the lyapunov stability method is used for estimating the un...
modern portfolio theory is based on harry markowitz's 1952 work on mean-variance portfolios. he stated that a rational investor should either maximize his expected return for a given level of risk, or minimize his risk for a given expected return. in this study the markowitz model with cardinality constraints was studied. we extend the standard model to include cardinality constraints that...
a semi-empirical mathematical model for predicting physical part of ignition delay period in the combustion of direct - injection diesel engines with swirl is developed . this model based on a single droplet evaporation model . the governing equations , namely , equations of droplet motion , heat and mass transfer were solved simultaneously using a rung-kutta step by step unmerical method . the...
with the increasing population and the need for more food, as well as with the development of science and technology, human approach to unnatural and often chemical inputs to increase agricultural production has been a great expansion and problems such as increased cancers, chronic diseases has created environmental pollution. implementation of organic organic is a solution to these problems . ...
over the past decades a number of approaches have been applied for forecasting mortality. in 1992, a new method for long-run forecast of the level and age pattern of mortality was published by lee and carter. this method was welcomed by many authors so it was extended through a wider class of generalized, parametric and nonlinear model. this model represents one of the most influential recent d...
in new management approaches, in the organizations with inflexible structure, existing of red tapes and interruptions caused by limitations and also non-compliance with environmental changes, create demotivation among staff. with regard to the influence of job motivational potential and its relationship to the type of organizational structure( enabling and dissuasive), the goal of this research...
QP is the optimization of a quadratic function subject to linear equality and inequality constraints. It arises in multiple objective decision making where the departure of the actual decisions from their corresponding ideal, or bliss, value can be evaluated using a weighted quadratic norm as a measure of deviation. The formulation of mean-variance optimization of uncertain systems also leads t...
The mean-variance (MV) portfolio is typically formulated as a quadratic programming (QP) problem that linearly combines the conflicting objectives of minimizing risk and maximizing expected return through aversion profile parameter. In this formulation, two are expressed in different units, an issue could definitely hamper obtaining more competitive set weights. For example, modification scale ...
This paper adopts the spread of fuzzy variable as a new criteria in practical risk management problems, and develops a novel fuzzy expectation-spread (E-S) model for portfolio optimization problem. Since the spread is defined by Lebesgue-Stieltjes (L-S) integral, its computation for general fuzzy variables is a challenge issue for research, and usually depends on approximation scheme and soft c...
In this paper, we study the problem of minimizing the ratio of two quadratic functions subject to a quadratic constraint. First we introduce a parametric equivalent of the problem. Then a bisection and a generalized Newton-based method algorithms are presented to solve it. In order to solve the quadratically constrained quadratic minimization problem within both algorithms, a semidefinite optim...
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