A Dynamic Quantum-Inspired Genetic Algorithm with Lengthening Chromosome Size

Abstract

This paper proposes a Dynamic Quantum-inspired Genetic Algorithm (DQGA), which combines the quantum mechanics concepts with metaheuristics principles to enhance the search capability of the genetic algorithm. The proposed algorithm also introduces the lengthening chromosome strategy for a balanced and smooth transition between exploration and exploitation phases. Apart from that, a novel adaptive look-up table for rotation gates is presented to boost the algorithm's optimization abilities. To evaluate the effectiveness of these ideas, the DQGA is tested by various mathematical benchmark functions as well as real-world constrained engineering problems against several well-known and state-of-the-art algorithms. The obtained results indicate the merits of the proposed algorithm.

A Dynamic Quantum-Inspired Genetic Algorithm for Multilevel Satellite Image Segmentation

“…In this section, dynamic quantum-inspired genetic algorithm (DQGA) is explained. The authors of this study have proposed DQGA in [23]. DQGA consists of two main contributions to the classical QGA, namely, lengthening chromosome size and adaptive rotation gates.…”