Smart Delivery Systems: Solving Complex Vehicle Routing Problems examines both exact and approximate methods for delivering optimal solutions to rich vehicle routing problems, showing both the advantages and disadvantages of each approach. It shows how to apply machine learning and advanced data analysis techniques to improve routing systems, familiarizing readers with the concepts and technologies used in successfully implemented delivery systems. The book explains both the latest theoretical and practical advances in intelligent delivery and scheduling systems and presents practical applications for designing new algorithms for real-life scenarios.

Emphasizes both sequential and parallel algorithms
Uniquely combines methods and algorithms, real-life applications, and parallel computing
Includes recommendations on how to choose between different methods for solving applications
Provides learning aids, end of chapter references, bibliography, worked examples and exercises

About the Author

Jakub Nalepa is an Assistant Professor in the Department of Automatic Control, Electronics and Computer Science at Silesian University of Technology. His interdisciplinary research encompasses academic and industry applications for vehicle routing optimization, machine learning, evolutionary algorithms, pattern recognition, and parallel computing.

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