Quantum Algorithm for Continuous Global Optimization

V. Protopopescu, J. Barhen

Pedro Lara, Renato Portugal, Carlile Lavor

Anna Ouskova Leonteva, Ulviya Abdulkarimova, T. M. Wintermantel +3 more

This paper presents a novel multi-threaded quantum inspired optimization algorithm targeted at global search in continuous domains. The proposed approach is based on a Diffusion Monte Carlo (DMC) physical model and is characterized by a set of parallel quantum walk processes. The effectiveness of the proposed algorithm is demonstrated by experimental results on the 24 noiseless functions from the Black Box Optimization Benchmark of the Comparing Continuous Optimization benchmarking platform (COCO).

Xinghua Zhang

Aimed at the difficulty in solving the continuous functions of general quantum genetic algorithm,an improved quantum genetic algorithm is studied.In this algorithm,H,gate,a novel quantum rotation gate,is adopted to update the population,which can prevent the algorithm from falling into local optimum,and improve the global searching ability of the algorithm.The test results indicate that, when this algorithm optimizes continuous function,its overall performance is superior to that of conventional genetic algorithm and general quantum genetic algorithm.

Ansh Bansal

Yipeng Liu, Gary J. Kœhler