Abstract: Techniques to refine solutions to linear optimization problems using symmetries are described. Some embodiments are particularly directed to techniques to refine solutions to linear optimization problems using symmetries to permute an existing solution into other feasible solutions that may improve upon the objective function. In one embodiment, for example, an apparatus may comprise a configuration component, an optimization component, a symmetries component, and an improvement component. The configuration component may be operative to receive an optimization problem described by an objective and constraints on a plurality of variables. The optimization interface component may be operative to receive an initial feasible solution to the optimization problem, the initial feasible solution comprising an assignment of values to the plurality of variables satisfying all the constraints, the initial feasible solution producing an initial objective value when applied to the objective.

Abstract: Systems and methods for conflict resolution and stabilizing cut generation in a mixed integer linear program (MILP) solver are disclosed. One disclosed method includes receiving a mixed integer linear problem (MILP), the MILP having a root node and one or more global bounds; pre-processing the MILP, the MILP being associated with nodes; establishing a first threshold for a learning phase branch-and-cut process; performing, by one or more processors, the learning phase branch-and-cut process for nodes associated with the MILP, wherein performing the learning phase branch-and-cut process includes: evaluating the nodes associated with the MILP, collecting conflict information about the MILP, and determining whether the first threshold has been reached; responsive to reaching the first threshold, removing all of the nodes and restoring a root node of the MILP; and solving, with the one or more processors, the MILP using the restored root node and the collected conflict information.

Abstract: Techniques to refine solutions to linear optimization problems using symmetries are described. Some embodiments are particularly directed to techniques to refine solutions to linear optimization problems using symmetries to permute an existing solution into other feasible solutions that may improve upon the objective function. In one embodiment, for example, an apparatus may comprise a configuration component, an optimization component, a symmetries component, and an improvement component. The configuration component may be operative to receive an optimization problem described by an objective and constraints on a plurality of variables. The optimization interface component may be operative to receive an initial feasible solution to the optimization problem, the initial feasible solution comprising an assignment of values to the plurality of variables satisfying all the constraints, the initial feasible solution producing an initial objective value when applied to the objective.

Abstract: Systems and methods for conflict resolution and stabilizing cut generation in a mixed integer linear program (MILP) solver are disclosed. One disclosed method includes receiving a mixed integer linear problem (MILP), the MILP having a root node and one or more global bounds; pre-processing the MILP, the MILP being associated with nodes; establishing a first threshold for a learning phase branch-and-cut process; performing, by one or more processors, the learning phase branch-and-cut process for nodes associated with the MILP, wherein performing the learning phase branch-and-cut process includes: evaluating the nodes associated with the MILP, collecting conflict information about the MILP, and determining whether the first threshold has been reached; responsive to reaching the first threshold, removing all of the nodes and restoring a root node of the MILP; and solving, with the one or more processors, the MILP using the restored root node and the collected conflict information.