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arXiv · 2412.02720

Quantum Annealing based Hybrid Strategies for Real Time Route Optimization

Sushil Mario·Pavan Teja Pothamsetti·Louie Antony Thalakottor·Trisha Vishwanath·Sanjay H. A·Anees Ahmed·Salvatore Sinno·Shruthi Thuravakkath·Sinthuja M
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Abstract

One of the most well-known problems in transportation and logistics is the Capacitated Vehicle Routing Problem (CVRP). It involves optimizing a set of truck routes to service a set of customers, subject to limits on truck capacity, to reduce travel costs. The biggest challenge faced whilst attempting to solve the issue is that the time complexity of the issue grows exponentially with the number of customers and trucks, rendering it virtually intractable to traditional computers and algorithms. In this paper, we propose a method to circumvent this limitation, employing quantum computers to aid classical computers in solving problems faster while reducing complexity. To obtain our results, we employ two algorithms: Hybrid Two Step (H2S) and Hybrid Three Step (H3S). Both algorithms involve two phases: clustering and routing. It has been observed that both algorithms produce promising results, both in terms of solution time and solution cost.

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Sushil Mario, Pavan Teja Pothamsetti, Louie Antony Thalakottor, Trisha Vishwanath, Sanjay H. A, Anees Ahmed, Salvatore Sinno, Shruthi Thuravakkath, Sinthuja M. 2024-11-21. Quantum Annealing based Hybrid Strategies for Real Time Route Optimization. https://arxiv.org/abs/2412.02720

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