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I would like to solve an ILP and get all feasible solutions (even the worst one). How could I do that using docplex.cp?

I've seen a similar question in: Using CPLEX "solution pool" to count feasible points

However, if I am not wrong, the answers were only focused on MIP problem, instead of ILP. I was not able to find a function in docplex for ILP problems able to call all feasible solutions. I was wondering that I need to do an intermediate step in order to get these solutions, but I really do not know if it is possible. Could someone help me?

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I am answering my own question because it may help other people.

I could not find a function in docplex able to get all feasible solutions for a ILP problem. For my best knowledge, docplex only has this kind of function for MIP problems. If you are dealing with MIP, you can check additional information here: https://www.ibm.com/support/knowledgecenter/SS9UKU_12.8.0/com.ibm.cplex.zos.help/CPLEX/Parameters/topics/listSolnPool.html https://www.ibm.com/support/knowledgecenter/SSSA5P_12.9.0/ilog.odms.cplex.help/refpythoncplex/html/cplex._internal._subinterfaces.SolnPoolInterface-class.html

Feasible solutions for ILP problems:

With OR-tools I could find a way to get all feasible solutions for constrained problems by using SearchForAllSolutions. As expected, this functions is available for CP-SAT and you cannot state any objective function.

If you are interested in it, I suggest you to take a look at this example: https://developers.google.com/optimization/cp/cp_solver#first_sol_program

PS: In my case, I was trying to solve a 01LP, so it generated many solutions, but with several duplicates. In order to avoid that, you can state a limit (time or number of solutions found). Please, check CP-SAT documentation for additional information.

Hope it will help someone!

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