Experimental study on the information disclosure problem: Branch-and-bound and QUBO solver

Abstract

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The aim of this study was to explore the information disclosure (ID) problem, which involves selecting pairs of two sides before matching toward 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. 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.

Keywords

• information disclosure
• heuristics
• branch-and-bound
• quantum annealing
• quadratic unconstrained binary optimization