Ted K. Ralphs

TL;DR: In today’s changing and competitive industrial environment, the difference between ad hoc planning methods and those that use sophisticated mathematical models to determine an optimal course of action can determine whether or not a company survives.

TL;DR: This work describes a decomposition-based separation methodology for the capacity constraints that takes advantage of the ability to solve small instances of the TSP efficiently and presents some extensions of this basic concept and a general framework within which it can be applied to other combinatorial models.

TL;DR: The fifth version of the Mixed Integer Programming Library is reported on, which comprises 361 instances sorted into several groups and includes scripts to run automated tests in a predefined way.

TL;DR: A rudimentary branch-and-cut algorithm for solving integer bilevel linear programs that extends existing techniques for standard integer linear programs to this very challenging computational setting is described.

TL;DR: For the first time, these sets were compiled using a data-driven selection process supported by the solution of a sequence of mixed integer optimization problems, which encode requirements on diversity and balancedness with respect to instance features and performance data.