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A logical spreadsheet is a spreadsheet in which formulas take the form of logical constraints rather than function definitions.. In traditional spreadsheet systems, such as Excel, cells are partitioned into "directly specified" cells and "computed" cells and the formulas used to specify the values of computed cells are "functional", i.e. for every combination of values of the directly ...
Tables, plots, comments, and the MathLook notation display tool can be used to enrich TK Solver models. Models can be linked to other components with Microsoft Visual Basic and .NET tools, or they can be web-enabled using the RuleMaster product or linked with Excel spreadsheets using the Excel Toolkit product. There is also a DesignLink option ...
Curve fitting [1] [2] is the process of constructing a curve, or mathematical function, that has the best fit to a series of data points, [3] possibly subject to constraints. [ 4 ] [ 5 ] Curve fitting can involve either interpolation , [ 6 ] [ 7 ] where an exact fit to the data is required, or smoothing , [ 8 ] [ 9 ] in which a "smooth ...
Remove j from R. Let A P be A restricted to the variables included in P. Let s be vector of same length as x. Let s P denote the sub-vector with indexes from P, and let s R denote the sub-vector with indexes from R. Set s P = ((A P) T A P) −1 (A P) T y; Set s R to zero; While min(s P) ≤ 0: Let α = min x i / x i − s i for i in P ...
This can be used to implement a UNIQUE constraint (with equality predicate) or more complex constraints, like ensuring that no overlapping time ranges or no intersecting geometry objects would be stored in the table. An index supporting fast searching for records satisfying the predicate is required to police such a constraint. [1]
Such a constraint set is called a polyhedron or a polytope if it is bounded. Second-order cone programming (SOCP) is a convex program, and includes certain types of quadratic programs. Semidefinite programming (SDP) is a subfield of convex optimization where the underlying variables are semidefinite matrices .
The remaining constraints need to be grouped into independent submatrices such that if a variable has a non-zero coefficient within one submatrix, it will not have a non-zero coefficient in another submatrix. This description is visualized below: The D matrix represents the coupling constraints and each F i represents the independent submatrices.
The primal constraint graph or simply primal graph (also the Gaifman graph) of a constraint satisfaction problem is the graph whose nodes are the variables of the problem and an edge joins a pair of variables if the two variables occur together in a constraint. [1] The primal constraint graph is in fact the primal graph of the constraint ...