http://nova.newcastle.edu.au/vital/access/services/Feed ${session.getAttribute("locale")} 5 http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:12841 Because of the many important applications of quadratic programming, fast and efficient methods for solving quadratic programming problems are valued. Gotdfarb and Idnani (1983) describe one such method. Well known to be efficient and numerically stable, the Goldfarb and Idnani method suffers only from the restriction that in its original form it cannot be applied to problems which are positive semi-definite rather than positive definite. In this paper, we present a generalization of the Goldfarb and Idnani method to the positive semi-definite case and prove finite termination of the generalized algorithm. In our generalization, we preserve the spirit of the Goldfarb and Idnani method, and extend their numerically stable implementation in a natural way. 2013-05-02T01:41:26.677Z ]]> http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:12837 We consider networks in which two different commodities have to be transported across undirected arcs, subject to a shared capacity on the arcs. For each arc and commodity there is an associated non-linear cost that depends on the amount of the commodity transported across the arc. The aim is to minimize the sum of the costs over all arcs and commodities. Efficient algorithms for solving this problem for two types of objective functions will be presented: in the first the cost depends on the absolute value of the flow and in the second the cost is a quadratic function of the flow. Previous work on multi-commodity flow has concentrated on linear cost problems or tackled non-linear cost problems with Lagrangian relaxation methods and other more general techniques. The algorithms in this paper, on the other hand, provide a very efficient way of dealing with two types of non-linear two-commodity optimal flow problems. 2013-05-01T04:16:43.126Z ]]> http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:12836 This paper evaluates an algorithm for solving network flow optimization problems with quadratic cost functions. Strategies for fast implementation are discussed and the results of extensive numerical tests are given. The performance of the algorithm measured by CPU time is compared with that of the convex simplex method specialized for quadratic network programming. Performance of the two methods is analysed with respect to network size and density, and other parameters of interest. The algorithm is shown to perform significantly better on the majority of problems. We also show how the algorithm may be used to solve non-linear convex network optimization problems by the use of sequential quadratic programming. 2013-05-01T04:14:15.189Z ]]> http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:1031 We show how the discrete coefficient filter design problem can be solved with a moving horizon optimization approach. The computation time of this procedure is determined by the optimization horizon and does not grow exponentially with the filter length. ΣΔ design methods are a special case of the proposed procedure. 2013-03-17T23:52:02.342Z ]]> http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:422 We show how the discrete coefficient filter design problem can be solved with a moving horizon optimization approach. The computation time of this procedure is determined by the optimization horizon and does not grow exponentially with the filter length. ΣΔ design methods are a special case of the proposed procedure. 2013-03-17T23:51:43.365Z ]]> http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:8740 In this paper, nonlinear model predictive control is applied to an inverted pendulum apparatus. The sample interval for control calculations is 25 milli-seconds and the associated non-convex constrained optimisation problem involves 61-variables with 241-constraints. Despite this being a challenging problem, it was solved online using a standard sequential quadratic programming approach on a modest hardware platform. The efficacy of the control algorithm is validated via experimental results. 2013-03-14T05:34:18.178Z ]]> http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:1917 This paper examines the issue of the generation of optimal control policies where there are explicit constraints upon the control values and there is limited knowledge of the complex economic system. The paper develops a methodology where the constrained optimal control is based upon a separate model that predicts the policy targets for the economic system. The methodology as applied to a small calibrated macroeconomic model of Australia. 2010-04-27T06:58:06.065Z ]]> http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:1149 We consider the problem of approximating the global minimum of a general quadratic pro-gram (QP) with n variables subject to m ellipsoidal constraints. 2010-04-27T06:38:06.327Z ]]>