Abstract: Systems and methods for generating improved solutions to MIP models are described. The present invention involves the use of a polishing algorithm that uses mutation and combination of solutions within a solution pool to generate improved solutions. The polishing algorithm first randomly selects one or more seed solutions from a solution pool for mutation. The selected seed solutions are mutated by fixing a subset of integer variables in the models to the value they take in the seed solution. The remaining variables are then formulated into a sub-MIP problem that is solved by the MIP solver. The solutions generated from this mutation process may then be added to the solution pool. After the one or more iterations of the mutation processes have taken place, the polishing algorithm then selects one or more pluralities of parent solutions from the solution pool to use in generating offspring solutions. The integer variables that agree between one plurality of parent solutions are fixed in the offspring solution.

Abstract: The present invention relates to methods and systems for generating solutions to global optimization problems. In one aspect, the invention allows for determining whether models of optimization problems are infeasible. In another aspect, the invention allows for identifying relatively small sets of constraints that make a model infeasible. In yet another aspect, the invention provides methods and systems for creating one or more artificial infeasibilities in a model so as to seek improvement upon a known value of the objective function. Creation of artificial constraints in this manner may also permit identification of a relatively small set of constraints that may be limiting the value of the objective function.

Abstract: The present invention relates to methods and systems for generating solutions to global optimization problems. In one aspect, the invention allows for determining whether models of optimization problems are infeasible. In another aspect, the invention allows for identifying relatively small sets of constraints that make a model infeasible. In yet another aspect, the invention provides methods and systems for creating one or more artificial infeasibilities in a model so as to seek improvement upon a known value of the objective function. Creation of artificial constraints in this manner may also permit identification of a relatively small set of constraints that may be limiting the value of the objective function.

Abstract: Systems and methods for generating improved solutions to MIP models are described. The present invention involves the use of a polishing algorithm that uses mutation and combination of solutions within a solution pool to generate improved solutions. The polishing algorithm first randomly selects one or more seed solutions from a solution pool for mutation. The selected seed solutions are mutated by fixing a subset of integer variables in the models to the value they take in the seed solution. The remaining variables are then formulated into a sub-MIP problem that is solved by the MIP solver. The solutions generated from this mutation process may then be added to the solution pool. After the one or more iterations of the mutation processes have taken place, the polishing algorithm then selects one or more pluralities of parent solutions from the solution pool to use in generating offspring solutions. The integer variables that agree between one plurality of parent solutions are fixed in the offspring solution.