http://hdl.handle.net/10453/144 Fri, 24 May 2013 13:37:31 GMT 2013-05-24T13:37:31Z http://hdl.handle.net/10453/12741 Distributed simultaneous task allocation and motion coordination of autonomous vehicles using a parallel computing cluster Kulatunga Asela; Skinner Bradley; Liu Dikai; Nguyen Hung Tzyh-Jong Tarn, Shan-Ben Chen, Changjiu Zhou Task allocation and motion coordination are the main factors that should be consi-dered in the coordination of multiple autonomous vehicles in material handling systems. Presently, these factors are handled in different stages, leading to a reduction in optimality and efficiency of the overall coordination. However, if these issues are solved simultaneously we can gain near optimal results. But, the simultaneous approach contains additional algorithmic complexities which increase computation time in the simulation environment. This work aims to reduce the computation time by adopting a parallel and distributed computation strategy for Simultaneous Task Allocation and Motion Coordination (STAMC). In the simulation experiments, each cluster node executes the motion coordination algorithm for each autonomous vehicle. This arrangement enables parallel computation of the expensive STAMC algorithm. Parallel and distributed computation is performed directly within the interpretive MATLAB environment. Results show the parallel and distributed approach provides sub-linear speedup compared to a single centralised computing node. Mon, 01 Jan 2007 00:00:00 GMT http://hdl.handle.net/10453/12741 2007-01-01T00:00:00Z http://hdl.handle.net/10453/12740 Irreversibility factor and limiting performance of financial systems (thermodynamic approach) Tsirlin Anatoly; Kazakov Vladimir Oyibo, G Wed, 01 Jan 2003 00:00:00 GMT http://hdl.handle.net/10453/12740 2003-01-01T00:00:00Z http://hdl.handle.net/10453/12402 Some recent developments in the theory of Lie group symmetries for PDEs Craddock Mark; Konstandatos Otto; Lennox Kelly Baswell AR Lie group symmetry methods provide a powerful tool for the analysis of PDEs. Over the last thirty years, considerable progress has been made in the development of this field. In this article, we provide a brief introduction to the method developed by Lie for the systematic computation of symmetries, then move on to a survey of some of the more recent developments. Our focus is on the use of Lie symmetry methods to construct fundamental solutions of partial differential equations of parabolic type. We will show how recent work has uncovered an intriguing connection between Lie symmetry analysis and the theory of integral transforms. Fundamental solutions of families of PDEs which arise in various applications, can be obtained by exploiting this connection. The major applications we give will be in financial mathematics. We will illustrate our results with the problem of pricing a so called zero coupon bond, as well as giving some applications to option pricing. We also discuss some results on group invariant solutions and show how an important PDE in nilpotent harmonic analysis can be studied via its group invariant solutions. Thu, 01 Jan 2009 00:00:00 GMT http://hdl.handle.net/10453/12402 2009-01-01T00:00:00Z http://hdl.handle.net/10453/7817 Two Types of Risk Filar Jerzy; Kang Boda Yan, H; Yin, G; Zhang, Q. The risk encountered in many environmental problems appears to exhibit special ¿two-sided¿ characteristics. For instance, in a given area and in a given period, farmers do not want to see too much or too little rainfall. They hope for rainfall that is in some given interval. We formulate and solve this problem with the help of a ¿two-sided loss function¿ that depends on the above range. Even in financial portfolio optimization a loss and a gain are ¿two sides of a coin¿, so it is desirable to deal with them in a manner that reflects an investor¿s relative concern. Consequently, in this paper, we define Type I risk: ¿the loss is too big¿ and Type II risk: ¿the gain is too small¿. Ideally, we would want to minimize the two risks simultaneously. However, this may be impossible and hence we try to balance these two kinds of risk. Namely, we tolerate certain amount of one risk when minimizing the other. The latter problem is formulated as a suitable optimization problem and illustrated with a numerical example. Sun, 01 Jan 2006 00:00:00 GMT http://hdl.handle.net/10453/7817 2006-01-01T00:00:00Z