A New Hybrid Classical-Quantum Algorithm for Continuous Global Optimization Problems

TL;DR

This paper introduces a hybrid classical-quantum algorithm that combines local search with Grover's algorithm to efficiently solve continuous global optimization problems, demonstrating promising simulation results.

Contribution

It presents a novel hybrid approach integrating classical local minima search with quantum search to improve global optimization performance.

Findings

Quadratic speedup potential demonstrated with Grover's algorithm

Effective escape from local minima shown in simulations

Comparative advantage over existing algorithms in test cases

Abstract

Grover's algorithm can be employed in global optimization methods providing, in some cases, a quadratic speedup over classical algorithms. This paper describes a new method for continuous global optimization problems that uses a classical algorithm for finding a local minimum and Grover's algorithm to escape from this local minimum. Simulations with testbed functions and comparisons with algorithms from the literature are presented.