The GLPK package is part of the GNU Project released under the aegis of. GNU. Tables in the GNU MathProg Modeling Language” (doc/). PDF, Topic, Comment. doc/, GLPK reference manual, also covers the C language application programming interface (API). doc/, GNU MathProg . GLPK (GNU Linear Programming Kit) is intended for solving large-scale linear programming (LP), mixed integer programming (MIP), and other related problems .
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Add ‘number linear constraints. This amounts to adding a new column to the matrix. By default, the variable is both positive, real and the coefficient in the objective function is 0. Add number new variables. This amounts to adding new columns to the matrix.
By default, the variables are both positive, real and their coefficient in the objective function is 0. This method returns the current best upper resp. Has no meaning unless solve has been called before.
Each of them can be set to None if the variable is not bounded in the corresponding direction, and is a real value otherwise. Return the index th col name. A column corresponds to some non-basic variable specified by the parameter k as follows:. The basis factorization must exist. A pair indices, coeffs where indices lists the entries whose coefficient is nonzero, and to which coeffs associates their coefficient in the computed column of the current simplex tableau.
All these variables are basic by definition. A row corresponds to some basic variable specified by the parameter k as follows:. A pair indices, coeffs where indices lists the entries whose coefficient is nonzero, and to which coeffs associates their coefficient in the computed row of the current simplex tableau.
Elements in indices have the same sense as index k. All these variables are non-basic by definition. The dual value is the reduced cost of a variable.
Ubuntu – Package Search Results — glpk-doc
The reduced cost is the amount by which the objective coefficient of a non basic variable has to change to become a basic variable. Behaviour is undefined unless solve has been called before. If the simplex algorithm has not been used for solving just a 0.
Returns current status assigned to the structural variable associated with j-th column:. The dual value of a constraint is the shadow price of the constraint.
The shadow price is the amount by which the objective value will change if the constraints bounds change by one unit under the precondition that the basis remains the same.
If the simplex algorithm has not been used for solving 0. Returns current status assigned to the auxiliary variable associated with i-th row:. This assumes that the problem has been solved with the simplex method and a basis is available. Otherwise an exception will be raised. Test whether the given variable is nonbasic at lower bound. If no filename is given as an input the results of the sensitivity analysis are displayed on the screen.
RPM resource glpk-doc(x86-32)
If a filename is given they are written to a file. This method is only effective if an optimal solution has been found for the lp using the simplex algorithm. In all other cases an error message is printed. Each of them can be set to None if the constraint is not bounded in the corresponding direction, and is a real value otherwise.
Return the index th row name. If all variables are continuous, the algorithm reduces to solving the linear program by the simplex method. This method raises MIPSolverException exceptions when dod solution can not be computed for any reason none exists, or the LP solver was not hlpk to find it, etc….
Package: glpk-doc (4.61-1)
Thus, if you suspect that your system is infeasible, set the preprocessing option first. GLPK also has an exact rational simplex solver. The only access to data glpm via double-precision floats, however.
It reconstructs rationals from doubles and also provides results as gkpk. Below we only test that the basis information is indeed available. Calculating the corresponding basic solution is left as an exercise. Solving a LP within the acceptable gap.
No exception is raised, even if the result is not optimal. To do this, we try to compute glppk maximum number of disjoint balls of diameter 1 in a hypercube:. Parameter names are specified in lower case. Parameter values are specified as strings in upper case, or as constants in lower case. The only thing lacking is a wrapper for callback routines.
You can get GLPK to spout all sorts of information at you. If you actually try to solve lpyou will get a lot of detailed information.
Additions for sensitivity analysis class sage. Namely, the ith entry of coeffs corresponds to the coefficient of the variable in the constraint represented by the ith entry in indices. Note indices and coeffs are expected to be of the same length. Note Has no meaning gl;k solve has been called before. Note The basis factorization must exist. Note Elements in indices have the same sense as index k. Note Behaviour is undefined unless solve has been called before.
Note This method is only effective if an optimal solution has been found for the lp using the simplex algorithm. Row name St Activity Slack Lower bound Activity Obj coef Obj value at Limiting Marginal Upper bound glp, range break point variable — 1 NU 3. Column name St Activity Obj coef Lower bound Activity Obj coef Obj value at Limiting Marginal Upper bound range range break point variable — 1 NL.
Note This method raises MIPSolverException exceptions gplk the solution can not be computed for vlpk reason none exists, or the LP solver was not able to find it, etc…. Problem has no feasible solution. Problem has unbounded solution sage: The LP relaxation problem has no dual feasible solution sage: To date, no attempt has been made to expose the interior point methods.
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