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The paper presents the idea of hedging portfolio selection and establishes the Mean- Absolute Deviation (MAD) optimization model for hedging portfolio selection problems. The MAD model uses absolute-deviation of returns of a hedging portfolio as measure of hedging risk. The MAD model can be converted into a linear programming model equivalently and the(More)
There are many applications related to linearly constrained quadratic programs subjected to upper and lower bounds. Lower bounds and upper bounds are treated as different constraints by common quadratic programming algorithms. These traditional treatments significantly increase the computation of quadratic programming problems. We employ pivoting algorithm(More)
The linear programming (simplified LP) problems in practice are always large scale. Large scale LP demands algorithms with high computing efficiency to satisfy practical needs. Pivoting algorithm for LP can cope with equality constraints, free variables, and constraints with upper and lower bounds efficiently. Especially during the course of computing, the(More)
Downside loss-averse preferences have seen resurgence in the portfolio management literature. Mean-lower semi absolute deviation (MLSAD) model is one of the most important mean-lower partial moment (MLPM) models. The MLSAD model is established and converted into a linear programming model. The pivoting algorithm for linear programming is presented to solve(More)
Portfolio optimization is an important branch to which optimization methods are applied. Transaction costs have significant influence on portfolio rebalancing in practice. The introduction of transaction costs into optimal rebalancing model significantly enlarges the size of optimization problem and need more efficient algorithms. We deduce the(More)
A framework of network collaborative manufacturing system is proposed in this paper, which is an integration of several functional systems and mainly consists of ISS, CMSS and LTS. It puts forward CMSS based on net manufacturing information, describes the destination of the system, the system structure, principal functions and working flow. With the system(More)
There are many applications related to parametric quadratic programming. The parametric quadratic programming problem causes much more computation than the common quadratic programming problem. We employ the parametric pivoting algorithm to improve the computing efficiency of the parametric quadratic programming problem. The algorithm can decrease(More)
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