1. A machine-implemented method comprising: receiving a programming model and an outcome objective; receiving a plurality of mixed-integer programming (MIP) start vectors, wherein each of the plurality of MIP start vectors specify one or more restrictions to apply to the programming model; detecting that one or more of the plurality of MIP start vectors include an effort level that corresponds to an amount of processing resources to utilize to solve the one or more plurality of MIP start vectors; using the programming model in a processor to compute a potential solution for each of the plurality of MIP start vectors, resulting in a plurality of potential solutions, wherein each one of the potential solutions included in the plurality of potential solutions corresponds to one of the MIP start vectors included in the plurality of MIP start vectors; selecting one of the potential solutions included in the plurality of potential solutions as an optimal intra-group solution that best achieves the outcome objective; and using the optimal intra-group solution to complete the outcome objective.