Metaheuristic Optimization Algorithms 1st Edition

Discover a clear, practical guide to advanced search strategies with Metaheuristic Optimization Algorithms, 1st Edition by Laith Abualigah. This authoritative text captures the latest developments in metaheuristics—powerful tools for solving complex optimization problems across engineering, data science, operations research and artificial intelligence.

Packed with intuitive explanations and real-world examples, the book breaks down popular algorithms such as genetic algorithms, particle swarm optimization, differential evolution and newer swarm- and nature-inspired methods. Readers will gain a solid grounding in algorithmic design, convergence behavior, parameter tuning and performance evaluation—presented in an accessible style suitable for graduate students, researchers and industry practitioners.

What sets this edition apart is its emphasis on applicability: clear pseudocode, comparative analyses and case studies demonstrate how metaheuristic optimization drives improvements in scheduling, routing, machine learning model selection and resource allocation. Whether you’re in academia in Europe, a data scientist in North America, an engineer in Asia, or a practitioner in the Middle East, this book offers practical strategies you can apply immediately.

If you seek a single, reliable reference to master modern optimization techniques and enhance problem-solving workflows, this book delivers. Practical, research-informed and globally relevant, it’s an essential addition to professional and university libraries alike.

Order your copy today to advance your optimization skills and stay ahead in disciplines where smart search strategies make the difference.

Note: eBooks do not include supplementary materials such as CDs, access codes, etc.