UNDERCOVER - a primal heuristic for MINLP based on sub-MIPs generated by set covering
[In a bid to generate and foster a sense of community, we invite you for a coffee/tea in the staff tea room after the seminar to chat with our guest and each other.]
by Timo Berthold
Abstract: We present Undercover, a primal heuristic for mixed-integer nonlinear programming (MINLP). The heuristic constructs a mixed-integer linear subproblem (sub-MIP) of a given MINLP by fixing a subset of the variables. We solve a set covering problem to identify a minimal set of variables which need to be fixed in order to linearise each constraint.
Subsequently, these variables are fixed to approximate values, e.g.
obtained from a linear outer approximation. The resulting sub-MIP is solved by a mixed-integer linear programming solver. Each feasible solution of the sub-MIP corresponds to a feasible solution of the original problem.
Although general in nature, the heuristic seems most promising for mixed-integer quadratically constrained programmes (MIQCPs). We present computational results on a general test set of MIQCPs selected from the MINLPLib.
For More Information: contact: Christina Burt. email email@example.com