Analysis of The Vehicle Routing Problem Solved via Hybrid Quantum
Algorithms in Presence of Noisy Channels
- URL: http://arxiv.org/abs/2205.07630v2
- Date: Wed, 29 Mar 2023 10:15:54 GMT
- Title: Analysis of The Vehicle Routing Problem Solved via Hybrid Quantum
Algorithms in Presence of Noisy Channels
- Authors: Nishikanta Mohanty, Bikash K. Behera and Christopher Ferrie
- Abstract summary: The objective is to plan routes of vehicles to deliver goods to a fixed number of customers with optimal efficiency.
We build a basic VRP solver for 3 and 4 cities using the variational quantum eigensolver on a fixed ansatz.
We find that the performance of the quantum algorithm depends heavily on what noise model is used.
- Score: 0.0
- License: http://creativecommons.org/licenses/by-nc-sa/4.0/
- Abstract: The vehicle routing problem (VRP) is an NP-hard optimization problem that has
been an interest of research for decades in science and industry. The objective
is to plan routes of vehicles to deliver goods to a fixed number of customers
with optimal efficiency. Classical tools and methods provide good
approximations to reach the optimal global solution. Quantum computing and
quantum machine learning provide a new approach to solving combinatorial
optimization of problems faster due to inherent speedups of quantum effects.
Many solutions of VRP are offered across different quantum computing platforms
using hybrid algorithms such as quantum approximate optimization algorithm and
quadratic unconstrained binary optimization. In this work, we build a basic VRP
solver for 3 and 4 cities using the variational quantum eigensolver on a fixed
ansatz. The work is further extended to evaluate the robustness of the solution
in several examples of noisy quantum channels. We find that the performance of
the quantum algorithm depends heavily on what noise model is used. In general,
noise is detrimental, but not equally so among different noise sources.
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