Primal Heuristics for Mixed Integer Nonlinear Programs

In this paper, we describe the implementation of primal heuristics for convex mixed integer nonlinear programs. The work focus on two families of heuristics that have been successfully used for mixed integer linear programs: diving heuristics and the Feasibility Pump. We show how these heuristics can be adapted in the context of mixed integer nonlinear programming. We present results from computational experiments on a set of instances that show how the heuristics implemented help finding feasible solutions faster than the traditional branch-and-bound algorithm and how they help reducing the total solution time of the branch-and-bound algorithm.

By: Pierre Bonami; João P. M. Gonçalves

Published in: Computational Optimization and Applications, volume 51, (no 2), pages 729-47 in 2012

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