Titlebook: Stochastic Modelling in Innovative Manufacturing; Proceedings, Cambrid Anthony H. Christer,Shunji Osaki,Lyn C. Thomas Conference proceeding

finite

Junji Koyanagi,Hajime Kawaiition of the problem solving robot and the position of the target robot coincide. In order to guarantee success in this task, the problem solver must be able to move faster than the target. Otherwise, the target could evade the problem solver indefinitely, even in a finite problem space, merely by a

Epidural-Space

Kodo Ito,Kazuyuki Teramoto,Toshio Nakagawa form, or function to its ancestors. It is, most obviously, smaller by several orders of mag­ nitude. Its form has changed from the carefully crafted one-of-a-kind in­ strument to the mass-produced microchip. But the change in its function is perhaps the most dramatic of all. Instead of being a computing engi978-1-4899-0481-2978-1-4899-0479-9

disrupt

modest

Rose Bakerrotection schemes to mitigate cascading blackouts will be examined. Also explored will be the use of: wide-area control strategies, new and emerging technologies and communications, software and hardware architectures, and state-of-the art Energy Management System (EMS) technologies as the keys to m

FIG

Games of Production Development in Manufacturing,ps researching. Each has to select a time to give up the competition. This model yields us a certain class of non-zero sum infinite games on some square. There are two patterns of information available to the players. We deal with three cases, that is, the noisy version, the silent version and the silent-noisy version.

占卜者

Software Reliability Growth Models for Discrete and Incomplete Testing,lusters..The likelihood functions for the models are derived, and the Empirical Bayes method used to fit the models to data on the testing of a number of software modules used to control a complex device. The model is used to predict how many faults are likely to remain in the software after testing is completed.

fluoroscopy

An Optimal Running Policy for Buffered Continuous Production Processes Subject to Random Breakdown,m of production processes (units) together with buffer storages between the units. The productive capacity of the units are subject to random breakdown and periodic maintenance. Branching and recycling of intermediate products and materials, as well as inter-dependence of operation between units, ar

exceed

On the Greedy Algorithm for Stochastic Optimization Problems,ed to element .. In this paper, we consider the case that .. are random costs which are ordered with respect to some stochastic ordering relation. We will show that the optimality of the greedy algorithm holds for a broad class of stochastic orders.

凝乳

Using Markov decision processes to optimize a nonlinear functional of the final distribution, with a strictly concave or strictly convex functional of the distribution of the final state. Reward structures such as these often arise when penalty factors are incorporated into the usual expected reward objective function. For convex problems there is a Markov deterministic policy which is optimal,

fetter