http://hdl.handle.net/10453/144 2013-05-23T00:42:01Z 2013-05-23T00:42:01Z Kulatunga Asela Skinner Bradley Liu Dikai Nguyen Hung http://hdl.handle.net/10453/12741 2013-05-07T01:09:43Z 2007-01-01T00:00:00Z

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.

2007-01-01T00:00:00Z Tsirlin Anatoly Kazakov Vladimir http://hdl.handle.net/10453/12740 2013-05-07T00:50:32Z 2003-01-01T00:00:00Z

Irreversibility factor and limiting performance of financial systems (thermodynamic approach) Tsirlin Anatoly; Kazakov Vladimir Oyibo, G

2003-01-01T00:00:00Z Filar Jerzy Kang Boda http://hdl.handle.net/10453/7817 2012-12-12T00:55:33Z 2006-01-01T00:00:00Z

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.

2006-01-01T00:00:00Z