DynLP essentially solves problems of the following form:
Maximize S = CX'
Subject to AX' 竕､ B
(or other variants of this), where:
窶｢ S denotes the 窶徭olution窶
窶｢ C is a row vector of 窶忤eights窶
窶｢ X is a row vector of 窶忻ariables窶
窶｢ A is a matrix
窶｢ B is a column vector
The matrix A and the vector B together defines the constraints of the problem. The goal is to determine the optimizing vector, X, and the corresponding solution value S.
By using DynLP events you can access all the elements of the LP problem. When specifying which element an event should be linked to, you use the 窶從ames窶 listed above, i.e., 窶彜窶, 窶廚窶, 窶弭窶, 窶廣窶, and 窶廝窶. To simplify the user interface, these are all considered to be 窶徼ables窶. You access a specific element in a table by specifying the row and the column numbers of this element. For the row vectors 窶廚窶 and 窶弭窶, the row number should always be 1. Similarly, for the column vector 窶廝窶, the column number should always be 1. Finally for the scalar 窶彜窶, both the row and the column numbers should be 1.
