Experimental study on the information disclosure problem: Branch-and-bound and QUBO solver - Otaki, Keisuke; Okada, Akihisa; Yoshida, Hiroaki (Frontiers in Applied Mathematics and Statistics, 2023)
We study the information disclosure (ID) problem, which involves selecting pairs of two sides before matching towards user-oriented optimization. This problem is known to be useful for mobility-on-demand (MoD) platforms because drivers' choice behaviors are appropriately modeled, but solving the problem is still under development although heuristic solvers have been proposed, e.g., by [Yang et al. 2021]. We develop new branch-and-bound-based (BnB) solvers and a new heuristic solver based on a Quadratic Unconstrained Binary Optimization (QUBO) formulation. Our numerical experiments show that the QUBO-based solver indeed works within the limit of available bits, and the BnB solver performs slightly better than existing heuristic ones.