Call for Book Chapters
Metaheuristic Optimization Algorithms: Tutorials and Applications in Engineering, Health, and Social Sciences
Editors:
- Dr. Hisham A. Shehadeh; Assistant Professor, Department of Computer Sciences, Faculty of Information Technology and Computer Science, Yarmouk University, Jordan; sh7adeh1990@hotmail.com
- Dr. Yuvraj Gajpal; Professor, Asper School of Business, University of Manitoba, Canada; yuvraj.gajpal@umanitoba.ca
Call for Contributions
In an era of increasing complexity across engineering, health, and social sciences, metaheuristic methods have emerged as essential, high-level tools for efficient problem-solving. These algorithms, inspired by natural phenomena—such as Darwinian evolution, swarm intelligence, and physical processes—are uniquely designed to navigate vast, complex search spaces, allowing them to identify near-optimal or exact solutions within reasonable timeframes. Their inherent flexibility makes them indispensable for addressing non-linear and high-dimensional challenges.
We are seeking high-quality chapter contributions for a new volume that will serve as both a rigorous theoretical foundation and a pragmatic field guide for applying metaheuristic optimization. Our goal is to bridge the gap between complex mathematical formulation and real-world deployment.
Why Contribute?
This book will distinguish itself by moving beyond simple theory to provide a hands-on, actionable resource. We encourage authors to provide:
- Deep Insight: Detailed explanations of design principles, the translation of natural/artificial systems into computational procedures, and an analysis of why specific algorithms succeed in complex, multimodal environments.
- Technical Rigor: Discussions covering exploitation/exploration techniques, convergence behaviors, and performance evaluation metrics.
- Practical Application: Step-by-step procedures for developing and customizing algorithms, including parameter tuning, hybridization, and methods to improve convergence speed and solution quality.
- Tangible Resources: The inclusion of annotated source codes and software examples to ensure readers can directly apply concepts to real-world scenarios.
- Interdisciplinary Impact: Detailed case studies that demonstrate how metaheuristic methods can be tailored to domain-specific constraints in engineering design, healthcare decision-making, and social science modeling.
By combining theoretical insight, practical tools, and real-world application, this volume will serve as a comprehensive, must-have resource for the optimization community.
Target Audience
This book is intended for a diverse, interdisciplinary audience. We invite contributions that cater to:
- Students: Undergraduate and graduate students in engineering, computer science, health, and social sciences seeking both conceptual and practical foundations.
- Researchers and Academics: Professionals looking for a structured overview of algorithmic principles and their applications across various disciplines.
- Industry Practitioners: Professionals involved in solving complex optimization problems in systems design, healthcare management, data analysis, and policy planning.
While basic mathematical, statistical, and programming knowledge is beneficial, the text aims to be accessible to readers with varying levels of expertise, blending introductory explanations with advanced insights.
Recommended Topics
We welcome submissions exploring a wide array of metaheuristic approaches, including but not limited to: Sperm Swarm Optimization, the Chernobyl disaster optimizer (CDO), the Bermuda Triangle Optimizer, the Artificial Protozoa Optimizer, the Five Phases Optimizer, Genetic Algorithms, Tabu Search, Ant Colony Algorithms, Simulated Annealing, and Particle Swarm Optimization.
We are specifically seeking contributions that align with the following thematic sections:
- Applications in mathematics.
- Applications in solving complex engineering problems.
- Applications in solving management problems.
- Applications in solving medical and healthcare problems.
- Applications across different disciplines of social science.
Suggested Chapter Formatting
- Header Information: Include the full chapter title, author name(s), professional affiliation(s), and the email address of the corresponding author.
- Abstract: Provide a concise summary of the chapter, limited to 150–250 words.
- Keywords: Include a list of four to six relevant keywords.
- Introduction: Clearly outline the background, research motivation, and problem statement.
- Theoretical Framework / Methodology: Detail the metaheuristic algorithm, including its design principles and mathematical formulation.
- Implementation / Case Studies: Describe how the algorithm is applied, specifying the datasets used and the experimental setup.
- Results and Discussion: Present your performance metrics and convergence behaviors, and provide a comparison with existing methods.
- Conclusion: Summarize the research findings and discuss potential future work.
- References: Ensure all references are formatted according to APA or IEEE standards.
Submission Deadline: March 30, 2027