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Quantum Annealing for Vehicle Routing Problem with weighted Segment

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arxiv 2203.13469 v1 pith:6SEBZB6H submitted 2022-03-25 quant-ph math.OC

Toufan D. Tambunan , Andriyan B. Suksmono , Ian J.M. Edward , Rahmat Mulyawan This is my paper · ORCID
classification quant-phmath.OC
keywords roadquantumvehicleproblemsquboannealingcongestionoptimization
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Quantum annealing technologies aim to solve computational optimization and sampling problems. QPU (Quantum Processing Unit) machines such as the D-Wave system use the QUBO (Quadratic Unconstrained Binary Optimization) formula to define model optimization problems for quantum annealing. This machine uses quantum effects to speed up computing time better than classical computers. We propose a vehicle routing problem that can be formulated in the QUBO model as a combinatorial problem, which gives the possible route solutions increases exponentially. The solution aims to optimize the vehicle's journey to reach a destination. The study presents a QUBO formulation to solve traffic congestion problems on certain roads. The resulting route selection by optimizing the distribution of the flow of alternative road vehicles based on the weighting of road segments. Constraints formulated as a condition for the level of road density. The road weight parameter influences the cost function for each road choice. The simulations on the D-Wave quantum annealer show optimal results on the route deployment of several vehicles. So that each vehicle will be able to go through different road options and reduce road congestion accurately. This solution provides an opportunity to develop QUBO modeling for more complex vehicle routing problems for road congestion.

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  1. Quantum Annealing for Realistic Traffic Flow Optimization: Clustering and Data-Driven QUBO

    quant-ph 2025-10 conditional novelty 6.0 of 10

    A data-driven QUBO pipeline with Leiden clustering solves traffic route assignment on 10,000-vehicle subproblems with D-Wave's hybrid annealer within ~1% of Gurobi under matched time budgets.

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