Abstract: Tree breeders must select a pedigree of trees in order to conserve genetic diversity while maximizing response to selection. This can be modeled as an optimization problem where a breeding population of fixed size is selected with a constraint on how the members of the selection are related.
The result is a Mixed Integer Quadratically Constrained program (MIQCP), which is solved with a branch-and-bound method that uses a linear relaxation of the quadratic constraints. In this talk we'll discuss the problem and the algorithms for solving it, including a heuristic to find feasible solutions. Real-world case studies on the selection of Scots pine and loblolly pine will be presented (Joint work with Tim Mullin, Skogforsk, the Swedish Forestry Research Institute).
Bio: Pietro Belotti is with the development team of the FICO Xpress-Optimizer, one of the leading solvers for optimization problems. He received a PhD in Computer Engineering in 2003 from the Technical University of Milan and was subsequently a postdoctoral felow at Carnegie Mellon University, a Visiting Professor at Lehigh University, and an Assistant professor at the department of Mathematical Sciences of Clemson University. His research interests lie primarily in mixed integer nonlinear optimization, robust optimization, and discrete bi-objective optimization.