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arXiv · 2002.01351

Solving Vehicle Routing Problem Using Quantum Approximate Optimization Algorithm

Utkarsh Azad·Bikash K. Behera·Emad A. Ahmed·Prasanta K. Panigrahi·Ahmed Farouk
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Abstract

In this paper, we describe the usage of the Quantum Approximate Optimization Algorithm (QAOA), which is a quantum-classical heuristic, to solve a combinatorial optimization and integer programming task known as Vehicle Routing Problem (VRP). We outline the Ising formulation for VRP and present a detailed procedure to solve VRP by minimizing its simulated Ising Hamiltonian using the IBM Qiskit platform. Here, we attempt to find solutions for the VRP problems: (4,2), (5,2), and (5,3), where each (n, k) represents a VRP problem with n locations and k vehicles. We find that the performance of QAOA is not just dependent upon the classical optimizer used, the number of steps p in which an adiabatic path is realized, or the way parameters are initialized, but also on the problem instance itself.

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Utkarsh Azad, Bikash K. Behera, Emad A. Ahmed, Prasanta K. Panigrahi, Ahmed Farouk. 2020-02-02. Solving Vehicle Routing Problem Using Quantum Approximate Optimization Algorithm. https://doi.org/10.1109/tits.2022.3172241

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