A classical hybrid solution to multi-stop routing

The hybrid solver addresses the computational challenges of logistics route optimization by integrating classical and quantum annealing, achieving efficient and rapid solution determination for complex routing problems.

WO2025193273A2 Publication Date: 2025-09-18UNISYS CORP
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Patent Information

Application Number
PCT/US2024/051609
Authority / Receiving Office
WO · WO
Patent Type
Applications
Current Assignee / Owner
Priority Date
2024-10-15
Filing Date
2024-10-16
Publication Date
2025-09-18

AI Technical Summary

Technical Problem

Logistics route optimization, particularly the Traveling Salesman Problem, is computationally challenging due to its combinatorial complexity and large solution domains, making it difficult to determine optimal routes within realistic timeframes using existing quantum computing techniques.

Method used

A hybrid solver approach that combines classical optimization methodologies with quantum annealing, utilizing a classical computing device for manageable solution domains and a quantum annealer for complex ones, determined by a heuristic threshold, to efficiently identify optimal routing solutions.

Benefits of technology

The hybrid solver significantly reduces computational requirements, enabling rapid solution determination within milliseconds, compared to conventional solvers that take seconds to minutes, by leveraging nested graph node data and data distillation methods.

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Abstract

Relational routing data tables are converted into graphs comprising nodes and vertices. The nodes can include origins and destinations associated with routes, while the vertices represent route parameters. Route segments can then be mapped from the graphs. For an origin−destination input, a set of shortest parameterized paths among the route segments is identified. These shortest parameterized paths includes route segments weighted over a range of route parameters. Within a solution domain, an optimal solution can be generated by filtering the shortest parameterized path based on a set of one or more selected parameters to generate an optimal solution. A classical threshold determines whether the optimal solution is generated using a classical computing process or a quantum computing process.
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