Multilevel Quantum Metaheuristics

Applications in Data Exploration

Siddhartha Bhattacharyya, Hiranmoy Roy, Jan Platos, Leo Mršić, Balamurugan Balusamy

• Publisher: Academic Press
• Year: 2026
• eBook ISBN: 9780443331374
• Topic: Computer Science
• Subtopic: Artificial Intelligence (AI) & Semantics
• Index: Computer Science

Multilevel Quantum Metaheuristics: Applications in Data Exploration explores the most recent advances in hybrid quantum-inspired algorithms. Combining principles of quantum mechanics with metaheuristic techniques for efficient data optimization, this book examines multilevel quantum systems characterized by qudits and higher-level quantum states as more robust alternatives to conventional bilevel quantum approaches. It introduces novel multilevel applications of quantum metaheuristics for addressing optimization problems in areas including function optimization, data analysis, scheduling, and signal processing. The book also showcases real-world examples, case studies, and contributions that emphasize the effectiveness of proposed multilevel techniques over existing bilevel methods. Researchers, professionals, and engineers working on intelligent computing, quantum computing, data processing, clustering, and analysis, and those interested in the synergies between quantum computing, metaheuristics, and multilevel quantum systems for enhanced data exploration and analysis will find this book to be of great value. - Provides insights into the future of quantum-inspired optimization by covering recent trends and mathematical techniques - Advances knowledge of evolving time-efficient hybrid quantum algorithms that leverage the processing capabilities of emerging qudit-based paradigms - Presents in-depth analysis of quantum mechanical principles with special reference to multilevel quantum states

Table of contents

• Title of Book
• Chapter 1 Multilevel quantum metaheuristics: fundamentals and applications
• Chapter 2 Multilevel quantum metaheuristics: applications in data exploration
• Chapter 3 Beyond qubits: exploring molecular qudits for advanced quantum computing
• Chapter 4 Neural architecture search using a quantum genetic algorithm for image classification
• Chapter 5 Revolutionizing network optimization: enhancing efficiency and performance through quantum computing and hybrid quantum–classical approaches
• Chapter 6 Automated cluster number detection in hyperspectral images using a qutrit flower pollination algorithm
• Chapter 7 Multiobjective portfolio optimization using multilevel quantum inspired optimization algorithms: a comparative study
• Chapter 8 A study on bi-level quantum-inspired genetic algorithm for gray level image segmentation
• Chapter 9 Quantum-inspired metaheuristics for drug design and discovery
• Chapter 10 Application of quantum metaheuristics techniques in data exploration for Internet of Things environment
• Chapter 11 Task allocation and scheduling
• Chapter 12 Image and signal processing
• Chapter 13 Air quality index improvement through machine learning and quantum computing: a framework for advancing air quality prediction using quantum-inspired metaheuristics on climate change to achieve positive health
• Chapter 14 Quantum approaches to task allocation and scheduling: enhancing efficiency and optimization in distributed systems
• Chapter 15 Multilevel quantum metaheuristics: concluding remarks and future directions of research
• Index