Modern logistics brings various challenging and complex problems to researchers’ attention. Among them, planning and control problems need efficient problem-solving approaches; multiagent systems are known as the most state-of-the-art artificial intelligence modeling framework to tackle such complex problems. This book is a published version of a PhD thesis in which the optimization of transport logistics is studied with a multiagent system approach.

Max Gath researches transport optimization of logistics using multiagent systems, in which the framework setup has been used to solve real-world case studies in groupage traffic and courier, express, and parcel services. The background including various aspects of multiagent systems is well investigated, and relevant literature is well reviewed so that a strong justification for the study is provided. Then, an agent-based framework is established, meeting all relevant theoretical requirements. Details such as how tasks (subcomponents) are delegated to individual agents, how coordination is handled among the agents, and how agents are interacted with toward collective problem solving effort are contained in the framework.

The multiagent model is tested with benchmark problems and validated. It is then applied to both real-world logistic problems. The simulation results suggest success for the proposed approach. At this point, I would be interested in comparative results with a typical rival approach to confirm further evidence of achievements by the proposed approach.

The details of the approach are provided in algorithmic pseudocode, and the processes are visualized using modeling diagrams including activity diagrams and flowcharts. This makes the entire study reproducible, and the results ready to be validated. That proves the strength of the book. Some pages of the book, which appear in landscape layout, should be reformatted to improve the readability of the book.