Robert Boschgmbh

Sergei Chubanov

Daria Stepanova

A computer-implemented method of scheduling jobs of a manufacturing or logistics process using a priority function. The priority function is evaluated on multiple to be scheduled jobs to obtain multiple respective priority values. The priority function is defined to invoke a kernel function. The kernel function is defined to compare representations of two respective jobs. Evaluating the priority function on a selected job comprises evaluating the kernel function on representations of the selected job and one or more reference jobs. The schedule for the multiple jobs is determined based on the priority values and is then output to enable the multiple jobs to be carried out according to the schedule.

Scheduling jobs of a manufacturing or logistics process

A computer-implemented method of configuring a communication network. Devices of the network are configured to communicate according to scheduling parameters that indicate a timing of transmitting and/or receiving data over the communication network. To configure the network, the method uses a configuration procedure that is customizable by a set of customization parameters. For a current scheduling instance, representing multiple data streams to be scheduled, the configuration procedure is applied to determine current scheduling parameters, which are provided to the respective devices. Concurrently with the current customization parameters being used, the customization parameters are optimized with respect to a performance indicator of scheduling the current scheduling instance according to the customization parameters, with the updated customization being used to determine scheduling parameters for future scheduling instances with improved performance with respect to the performance indicator.

Configuring a communication network

A method for training a polyhedral classifier is described including obtaining training data in a data space, the training data including first data points associated with a first label and second data points associated with a second label, determining a pair of hyperplanes by determining an orientation of the pair of hyperplanes based on a minimization of a distance between the pair of hyperplanes such that the first data points lie between the hyperplanes in relation to a distance between the pair of hyperplanes such that both the first data points and the second data points lie between the hyperplanes and determining the position of the pair of hyperplanes such that the first data points lie between the pair of hyperplanes and the second data points are at least partially separated from the first data points by the pair of hyperplanes.

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Stuttgart, Germany

Sergei Chubanov