Sap Se

Sap Ag

Nadine Gaertner

Benjamin Spieler

Holger Zendler

Markus Winkler

Oliver Frendo

Petra Meyer

Sven Liesecke

A computer-implemented method, a computer system and a computer program for controlling electric vehicle charging infrastructure that is used by a plurality of electric vehicles, wherein the infrastructure comprises a plurality of charging points. The method comprises receiving schedule information for the electric vehicles, the schedule information including, for each of the electric vehicles, at least one vehicle power characteristic. The method further comprises determining at least one power constraint for each of the electric vehicles based on the vehicle power characteristic. The method further comprises receiving an arrival indication for a respective one of the electric vehicles. The method further comprises assigning the respective electric vehicle to charge at one of the charging points for at least one time interval according to the respective power constraint.

Controlling electric vehicle charging infrastructure

A system, method, and computer program product for evaluating variant configuration using in-memory technology. Embodiments receive configuration data and a selection condition to be solved, bring Boolean selection condition expressions into disjunctive normal form (DNF) in memory, join concrete configuration values with the selection condition, and compare values. Embodiments aggregate the comparison results per AND-group with a minimum function, and aggregate those results per OR-group with a maximum function and output results of the selection condition for a concrete configuration. Embodiments may employ SQL Script statements. Embodiments may use conjunctive normal form (CNF) instead of DNF with corresponding aggregation ordering. Embodiments may extend the pure normal forms to enable calculations, string operations, evaluation of non-fixed-value literals, multi-valued literals, in-lists, and variant tables by translating and integrating them into the pattern of conjunctive and disjunctive aggregations. Parallelization and complexity-ordered branch evaluations are also provided.

Evaluation of variant configuration using in-memory technology

According to an example embodiment, a method may include accessing, by at least one processor from at least one non-transitory computer-readable memory device, a map and a hierarchy of places included in the map. The method may also include accessing, by the at least one processor from the at least one non-transitory computer-readable memory device, quantitative information associated with places in the hierarchy. The method may also include receiving a scaling input from a user. The method may also include determining, by the at least one processor, a level in the hierarchy at which to aggregate the quantitative information, based on the scaling input. The method may also include aggregating, by the at least one processor, the quantitative information for a plurality of the places at the determined level, the aggregating including independently aggregating the quantitative information associated with places below at least two of the plurality of places at the determined level. The method may also include generating, by the at least one processor, graphical data configured to display the map.

Aggregating based on hierarchy and scaling input

A plurality of digital resources are identified in a set of digital resources. An indication of a user selection of at least one criteria is received, the user selection received through a user interface. A degree of correlation is determined between each digital resource in the plurality and each of the criteria. Data is sent that is configured for use in presenting, in a window of the user interface, a plurality of graphical resource objects and at least one graphical attractor object, each graphical resource object representing a digital resource in the plurality of digital resources and each graphical attractor object representing one of the criteria. Each resource object is presented a distance from each attractor object, the distance based at least in part on the corresponding degree of correlation between the digital resource represented by the resource object and the criteria represented by the attractor object.

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Speyer, Germany

Nadine Gaertner