Solving break minimization problems in mirrored double round-robin tournament with QUBO solver

TL;DR

This paper demonstrates that a QUBO solver effectively solves the break minimization problem in sports scheduling, outperforming traditional methods even with added practical constraints, highlighting its potential in quantum computing applications.

Contribution

It shows that the QUBO formulation and solver outperform MIQP in solving complex sports scheduling problems, including those with additional constraints.

Findings

QUBO solver outperforms MIQP in break minimization tasks

QUBO approach remains effective with added practical constraints

QUBO formulation is promising for quantum computing in scheduling

Abstract

The break minimization problem is a fundamental problem in sports scheduling. Recently, its quadratic unconstrained binary optimization (QUBO) formulation has been proposed, which has gained much interest with the rapidly growing field of quantum computing. In this paper, we demonstrate that the state-of-the-art QUBO solver outperforms the general mixed integer quadratic programming (MIQP) solver on break minimization problems in a mirrored double round-robin tournament. Moreover, we demonstrate that it still outperforms or is competitive even if we add practical constraints, such as consecutive constraints, to the break minimization problem.