- This paper describes the computational challenge developed for a computational com-
petition held in 2023 for the 20th anniversary of the Mixed Integer Programming
Workshop. The topic of this competition was reoptimization, also known as warm
starting, of mixed integer linear optimization problems after slight changes to the
input data for a common formulation. The challenge was to accelerate the proof of
optimality of the modified instances by leveraging the information from the solving
processes of previously solved instances, all while creating high-quality primal solu-
tions. Specifically, we discuss the competition’s format, the creation of public and
hidden datasets, and the evaluation criteria. Our goal is to establish a methodology
for the generation of benchmark instances and an evaluation framework, along with
benchmark datasets, to foster future research on reoptimization of mixed integer linear
optimization problems.
