This book is specially focused on the latest developments and findings on hybrid algorithms and benchmarks in optimization and their applications in sciences, engineering, and industries. The book also provides some comprehensive reviews and surveys on implementations and coding aspects of benchmarks.

1. Nature-Inspired Algorithms: Overview and Open Problems.- 2. Hybrid algorithms: Components, Hybridization and Examples.- 3. Role of Benchmarks in Optimization.- 4. Travelling Salesman Problems: Symmetric and Asymmetric Cases.- 5. Scheduling Problems: Benchmarks and Implementation.- 6. Active Learning Solution for Semantic Labelling of Earth Observation Satellite Images.- 7. Development of an Ensemble Modelling Framework for Data Analytics in Supply Chain Management.- 8. An Application of Data Mining to Build the OD Matrix in Developing Countries: An Argentinean Case Study.- 9. Deep Learning-based Efficient Customer Segmentation for Online Retail Business.- 10. Application of a Routing Model with a Time Limit for the Collection of RSU in an Argentinian City.- 11. Network Weakness Detection: Case Studies.- 12. Unknown Target Searching by Swarm Robots: A Case Study.

This book is specially focused on the latest developments and findings on hybrid algorithms and benchmarks in optimization and their applications in sciences, engineering, and industries. The book also provides some comprehensive reviews and surveys on implementations and coding aspects of benchmarks. The book is useful for Ph.D. students and researchers with a wide experience in the subject areas and also good reference for practitioners from academia and industrial applications.

Presents latest developments and findings on hybrid algorithms and benchmarks in optimization Provides comprehensive reviews and surveys on implementations and coding aspects of benchmarks Serves as a reference resource for researchers and practitioners in academia and industry