6 papers
A Constraint Programming Approach for n-Day Lookahead Playoff Clinching in the NHL
Gili Rosenberg, Kyle E. C. Booth, J. Kyle Brubaker +1
In professional sports, a team has clinched the playoffs if they are guaranteed a postseason spot, regardless of the outcomes of any remaining games. As the season progresses, spor…
Crystal structure prediction using graph neural combinatorial optimization
Stavros Gerolymatos, J. Kyle Brubaker, Martin J. A. Schuetz +1
Crystalline materials are widely used in technological applications, yet their discovery remains a significant challenge. As their properties are driven by structure, crystal struc…
A Random-Key Optimizer for Combinatorial Optimization
Antonio A. Chaves, Mauricio G. C. Resende, Martin J. A. Schuetz +4
This paper introduces the Random-Key Optimizer (RKO), a versatile and efficient stochastic local search method tailored for combinatorial optimization problems. Using the random-ke…
Optimization of Next-Day Delivery Coverage using Constraint Programming and Random Key Optimizers
Kyle Brubaker, Kyle E. C. Booth, Martin J. A. Schuetz +4
We consider the logistics network of an e-commerce retailer, specifically the so-called "middle mile" network, that routes inventory from supply warehouses to distribution stations…
Quadratic unconstrained binary optimization and constraint programming approaches for lattice-based cyclic peptide docking
J. Kyle Brubaker, Kyle E. C. Booth, Akihiko Arakawa +4
The peptide-protein docking problem is an important problem in structural biology that facilitates rational and efficient drug design. In this work, we explore modeling and solving…
Scalable iterative pruning of large language and vision models using block coordinate descent
Gili Rosenberg, J. Kyle Brubaker, Martin J. A. Schuetz +4
Pruning neural networks, which involves removing a fraction of their weights, can often maintain high accuracy while significantly reducing model complexity, at least up to a certa…