Higher-Order Quantum-Inspired Genetic Algorithms

TL;DR

This paper introduces Higher-Order Quantum-Inspired Genetic Algorithms, specifically QIGA2, which uses quantum registers to model gene relations, improving efficiency on complex optimization problems.

Contribution

The paper presents a novel Order-2 QIGA that models gene relations with quantum registers, enhancing performance over previous algorithms.

Findings

QIGA2 outperforms previous QIGA algorithms on benchmark problems.

Higher quantum orders improve genetic algorithm efficiency.

Quantum registers enable modeling of gene relations using quantum phenomena.

Abstract

This paper presents a theory and an empirical evaluation of Higher-Order Quantum-Inspired Genetic Algorithms. Fundamental notions of the theory have been introduced, and a novel Order-2 Quantum-Inspired Genetic Algorithm (QIGA2) has been presented. Contrary to all QIGA algorithms which represent quantum genes as independent qubits, in higher-order QIGAs quantum registers are used to represent genes strings which allows modelling of genes relations using quantum phenomena. Performance comparison has been conducted on a benchmark of 20 deceptive combinatorial optimization problems. It has been presented that using higher quantum orders is beneficial for genetic algorithm efficiency, and the new QIGA2 algorithm outperforms the old QIGA algorithm which was tuned in highly compute intensive metaoptimization process.