Abstract: A truck configuration satisfying a truck configuration problem is automatically determined. The truck configuration problem is transformed to a target function, outputting values indicative of configurations satisfying the truck configuration problem. Stochastic local search methods are applied on the target function to determine the truck configuration. Preprocessing may be performed to improve efficiency, performance or the like of the stochastic local search methods. The truck configuration problem may be obtained from several sources, which may be independent of one another.

Abstract: A method and system for generating an n-dimensional matrix presentation of at least part of an m-dimensional database including data records and a least one key dimension. Each key dimension includes data value fields. Each data value field has real data therein. A sorting sequence of fact numbers is calculated. The fact numbers are integers that identify the data records. Entry points for each dimension of the n-dimensional matrix presentation are calculated. Each entry point is calculated to be linked with a corresponding fact number of the sorting sequence. A cardinality of the n-dimensional matrix presentation is calculated in dependence on the calculated sorting sequence and the calculated corresponding entry points. The n-dimensional matrix presentation is generated based on the calculated cardinality and the calculated entry points.

Abstract: A computer program product and computer system for implementing a method that generates an n-dimensional matrix presentation of at least part of an m-dimensional database including data records and at least two key dimensions. Each key dimension includes data value fields. Each data value field has real data therein. A sorting sequence of fact numbers is calculated. The fact numbers identify the data records. Entry points for each dimension of the n-dimensional matrix presentation are calculated. Each entry point is calculated to be linked with a corresponding fact number of the sorting sequence. A cardinality of the n-dimensional matrix presentation is calculated in dependence on the calculated sorting sequence and the calculated corresponding entry points. The n-dimensional matrix presentation is generated based on the calculated cardinality and the calculated entry points.

Abstract: A method and system for generating an n-dimensional matrix presentation of at least part of an m-dimensional database including data records and a least one key dimension. Each key dimension includes data value fields. Each data value field has real data therein. A sorting sequence of fact numbers is calculated. The fact numbers are integers that identify the data records. Entry points for each dimension of the n-dimensional matrix presentation are calculated. Each entry point is calculated to be linked with a corresponding fact number of the sorting sequence. A cardinality of the n-dimensional matrix presentation is calculated in dependence on the calculated sorting sequence and the calculated corresponding entry points. The n-dimensional matrix presentation is generated based on the calculated cardinality and the calculated entry points.

Abstract: A computer program product and computer system for implementing a method that generates an n-dimensional matrix presentation of at least part of an m-dimensional database including data records and at least two key dimensions. Each key dimension includes data value fields. Each data value field has real data therein. A sorting sequence of fact numbers is calculated. The fact numbers identify the data records. Entry points for each dimension of the n-dimensional matrix presentation are calculated. Each entry point is calculated to be linked with a corresponding fact number of the sorting sequence. A cardinality of the n-dimensional matrix presentation is calculated in dependence on the calculated sorting sequence and the calculated corresponding entry points. The n-dimensional matrix presentation is generated based on the calculated cardinality and the calculated entry points.

Abstract: Disclosed are a method and system for generating user-defined pivot views of data records contained in a database where, as depicted in FIG. 2a, an underlying real facts table at first is extended by continuous index values (200) which provides a continuous numbering of the facts from ‘1’ to ‘x’ (x=20 in the present example). In the resulting pivot view shown in FIG. 2b, in each cell (210) the indices of those facts are presented which sales value has to be summed-up in the corresponding cell. The pivot view is generated by means of a sequence vector. The underlying sequence vector for the pivot view in FIG. 2b is depicted in FIG. 2c and consists of two columns (260, 270), the left column (260) containing continuous numbers from again ‘1’ to ‘x’ and the right column (270) containing the mentioned index values (275) depicted in FIG. 2a in an ordered arrangement that enables sequentially building-up the pivot view of FIG. 2b.

Abstract: Disclosed are a method and system for generating user-defined pivot views of data records contained in a database where, as depicted in FIG. 2a, an underlying real facts table at first is extended by continuous index values (200) which provides a continuous numbering of the facts from ‘1’ to ‘x’ (x=20 in the present example). In the resulting pivot view shown in FIG. 2b, in each cell (210) the indices of those facts are presented which sales value has to be summed-up in the corresponding cell. The pivot view is generated by means of a sequence vector. The underlying sequence vector for the pivot view in FIG. 2b is depicted in FIG. 2c and consists of two columns (260, 270), the left column (260) containing continuous numbers from again ‘1’ to ‘x’ and the right column (270) containing the mentioned index values (275) depicted in FIG. 2a in an ordered arrangement that enables sequentially building-up the pivot view of FIG. 2b.