linear-programming

I coded my model in gurobipy and I want to get the matrix of constraints and vector of cost. Is there any way to access those? From the python API, there's no single function to get the matrix coefficients from a Gurobi model, but it's not to hard to write one yourself. It is convenient to have lists of your variables and constraints. If you have a gurobi model in variable m dvars = m.getVars() constrs = m.getConstrs() will give you the list of variables and constraints. You can then use m.getAttr to retrieve attributes related to the variables. To obtain the objective function coefficients,

I am new in ampl and I want to use if condition in ampl with the following information: I have a binary variable X[p,r], where {p in P, r in R}. Now I want to make a new constraint such that the variable R[p,r] is used where X[p,r]=0. I do not know how I can write it or even if the ampl can handle it or not, I tried the following constraint but they did not work: s.t. a1{r in R, p in P and X[p,r]=0}: s.t. a2{r in R p in P and X[p,r]=0}; s.t. a2{r in R ,p in P, and X[p,r]=0}; s.t. a2{r in R, p in P: and X[p,r]=0}; You cannot include a decision variable in the "for all" part of the constraint

I am trying to use cplex in eclipse in Ubuntu 12.04 but when I include ilocplex.h I get the following error /opt/ibm/ILOG/CPLEX_Studio124/concert/include/ilconcert/ilosys.h:360:22: fatal error: iostream.h: No such file or directory The only two includes are written as follows: #include <ilcplex/ilocplex.h> #include <iostream> I would appreciate if anyone could help me with this. David Nehme At the time ILOG's Concert library was first released, the older iostream.h headers were still common in C++ compilers, but it supports the standard iostream libraries. To use the standard headers and

I have an optimization problem that has in the objective function 2 multiplied variables, making the model quadratic. I am currently using zimpl, to parse the model, and glpk to solve it. As they don't support quadratic programming, I would need to convert this to an MILP. . The first variable is real, in range [0, 1], the second one is real, from range 0 to inf. This one could without a problem be integer. The critical part in the objective function looks like this: max ... + var1 * var2 + ... I had similar problems in the constraints, but they were easily solvable. How could I solve this

I need to make a linear programming model. Here are the inequalities I'm using (for example): 6x + 4y <= 24 x + 2y <= 6 -x + y <= 1 y <= 2 I need to find the area described by these inequalities, and shade it in a graph, as well as keep track of the vertices of the bounding lines of this area, and draw the bounding line in a different color. See the graph below for an example of what I'm looking for. . I'm using Python 3.2, numpy, and matplotlib. Are there better modules for linear programming in Python? Ali UPDATE: The answer has become somewhat outdated in the past 4 years, here is an update

Can anyone recommend a library - free, or commercial but affordable ( There are some listed here: http://en.wikipedia.org/wiki/Linear_programming#Solvers_and_scripting_.28programming.29_languages ....but I am just starting out with LP and hope someone can recommend something. I am trying to basically minimize pricing for cell phone subscription services. I guess the 1st question is : is linear programming even applicable to solving this problem? A simplified example: Base Plan Options Plan A: 200 Voice minutes, 10 Text Messages, 10 MB Data = $25 Plan B: 400 Voice minutes, 25 Text Messages, 25