SimpleLPsolver 1.3.1a Details

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The Simple LP Solver can solve large size linear programming problems in an efficient way. The size of the problem theoratically depends on the memory allocated to the program by the computer; practically total array size could be max. 128M. The program provides Simplex and Revised Simplex solvers. If the all constraints are <=, the single phase technique is applied while Two Phased technique is automatically used for others; = and >=

Publisher Description

Window 10 CompatibleThe Simple LP Solver is a lightweight application that provides Simplex and Revised Simplex problem solvers with degeneration check for Primal and Dual problems. The software uses both single phase and two phase techniques depending on type of the constraints. If the all constraints are <=, the single phase technique is applied while Two Phase technique is automatically used for = and >= constraints. It has a simple graphical user interface with all menus and toolbar on the upper part and status-information bar on the lower part. There methods for problem loading are provided; the Input Table function allows entering the required input parameters (a maximum of 250 decision variables and 63,900 constraints) while Input from File function loads problems from comma separated text (CVS) files. On the other hand, the Load Table from File function loads problems from comma separated text (CVS) files to the Input Form. Save Table to File function writes problems from the Input Form to comma separated text (CVS) files. The delimiter for CVS can be selected. The Solver can check coefficent of decision variables and constraints if they are all zero. A constraint with all coefficients are zero is eliminated. Input can be checked for redundant constraints, if any, it is eliminated. The Solver also check the negative RHS values and converts them to positive by multiplying by -1 and changing the equality sign. The Simplex Solver converts minimization problems to maximization. On the other hand, the Revised Simplex Solver converts maximization problems to minimization. Depending on the selection, major steps of solving or just result are shown The size of the problem theoretically depends on the memory allocated to the program by the computer (typically maximum array size is 128M). Values can be integer and floating point numbers in the range of 2.3E-308 to 1.7E+308. The floating numbers have 15 digit precision although 2 decimal digits are displayed.

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