Sebastian Meiswinkel studies optimization problems that arise at container ports from a classic optimization as well as from a mechanism design point of view. The first part of this dissertation is focused on scheduling problems with selfish job owners that have private information about their characteristics. Afterwards the transportations of containers between the quay and a storage area is considered. Variants of this problem are analyzed for utilization of reach stackers and straddle carriers.

Combinatorial optimization is a multidisciplinary scientific area, lying in the interface of three major scientific domains: mathematics, theoretical computer science and management. The three volumes of the Combinatorial Optimization series aim to cover a wide range of topics in this area. These topics also deal with fundamental notions and approaches as with several classical applications of combinatorial optimization. Concepts of Combinatorial Optimization, is divided into three parts: - On the complexity of combinatorial optimization problems, presenting basics about worst-case and randomized complexity; - Classical solution methods, presenting the two most-known methods for solving hard combinatorial optimization problems, that are Branch-and-Bound and Dynamic Programming; - Elements from mathematical programming, presenting fundamentals from mathematical programming based methods that are in the heart of Operations Research since the origins of this field.

Combinatorial optimization is a multidisciplinary scientific area, lying in the interface of three major scientific domains: mathematics, theoretical computer science and management. The three volumes of the Combinatorial Optimization series aims to cover a wide range of topics in this area. These topics also deal with fundamental notions and approaches as with several classical applications of combinatorial optimization. “Applications of Combinatorial Optimization” is presenting a certain number among the most common and well-known applications of Combinatorial Optimization.

This book provides a coherent and systematic view of the key concepts, principles, and techniques in maritime container transport and logistics chains including all the main segments: international maritime trade and logistics, freight logistics, container logistics, vessel logistics, port and terminal management, and sustainability issues in maritime transport. Container Logistics and Maritime Transport emphasizes analytical methods and current optimization models to tackle challenging issues in maritime transport and logistics. This book takes a holistic approach to cover all the main segments of the container shipping supply chains to achieve an efficient and effective logistics service system across the entire global transport chain. Sustainability issues such as social concern and carbon emissions from shipping and ports are also discussed. Each maritime transport segment is addressed using an approach from qualitative/descriptive analytics to quantitative/prescriptive analytics. Cutting-edge optimization models are presented and explained to tackle various strategic, tactical, and operational planning problems. The book will help readers better understand operations management in global maritime container transport chain. It will also provide practical principles and effective techniques and tools for researchers to push forward the frontiers of knowledge and for practitioners to implement decision support systems. It will be directly relevant to academic courses related to maritime transport, maritime logistics, transport management, international shipping, port management, container shipping, container logistics, shipping supply chain, and international logistics.

Container Terminals (CT) operate as central nodes in worldwide hub-and-spoke networks and link ocean-going vessels with smaller feeder vessels as well as with inbound and outbound hinterland transportation systems using road, rail, or inland waterways. The volume of transcontinental container flows has gained appreciably over the last five decades -- throughput figures of CT reached new records, frequently with double-digit annual growth rates. Stimulated by throughput requirements and stronger competition between terminals settled in the same region or serving a similar hinterland, respectively, cost efficiency and throughput capabilities become more and more important. Nowadays, both terminal capacity and costs have to be regarded as key indicators for CT competitiveness. In respect of this steady growth, this handbook focuses on planning activities being aimed at “order of magnitude improvements” in terminal performance and economic viability. On the one hand the book is intended to provide readership with technological and organizational CT basics for strategic planning. On the other hand this book offers methodical assistance for fundamental dimensioning of CT in terms of 'technique', 'organization' or 'man'. The former primarily considers comprehensive information about container handling technologies representing the state of the art for present terminal operations, while the latter refers to methodological support comprising in particular quantitative solutions and modeling techniques for strategic terminal decisions as well as straightforward design guidelines. The handbook includes an introductory contribution which gives an overview of strategic planning problems at CT and introduces the contributions of the volume with regard to their relationship in this field. Moreover, each paper contains a section or paragraph that describes the impact of findings investigated by the author(s) for problem-solving in long-term planning of CT (as an application domain). The handbook intends to provide solutions and insights that are valuable for both practitioners in industry who need effective planning approaches to overcome problems and weaknesses in terminal design/development and researchers who would like to inform themselves about the state of the art in methodology of strategic terminal planning or be inspired by new ideas. That is to say, the handbook is addressed to terminal planners in practice as well as to students of maritime courses of study and (application oriented) researchers in the maritime field.

Maritime Supply Chains breaks the maritime chain into components, consistently relating them to the overall integrated supply chain. The book not only analyzes and provides solutions to frequently encountered problems and key operational issues, it also applies cutting-edge scientific techniques on the maritime supply chain. Sections consider shipping, ports and terminals, hinterland and the issues that intersect different parts of the chain. Readers will find discussions of the various actors at play and how they relate to the overall function of the supply chain. Finally, the book offers solutions to the most pressing problems, thus providing a unique, well-balanced account. - Provides a comprehensive and integrative account of the maritime supply chain, from shipping, to port, to hinterland - Cuts through the maritime supply chain to offer a transversal picture on how the chain functions - Applies rigorous analytical techniques to give solutions to the most frequent and pressing challenges facing maritime supply chains - Considers advances, such as blockchain, that are set to transform maritime supply chains

Heuristics are strategies using readily accessible, loosely applicable information to control problem solving. Algorithms, for example, are a type of heuristic. By contrast, Metaheuristics are methods used to design Heuristics and may coordinate the usage of several Heuristics toward the formulation of a single method. GRASP (Greedy Randomized Adaptive Search Procedures) is an example of a Metaheuristic. To the layman, heuristics may be thought of as ‘rules of thumb’ but despite its imprecision, heuristics is a very rich field that refers to experience-based techniques for problem-solving, learning, and discovery. Any given solution/heuristic is not guaranteed to be optimal but heuristic methodologies are used to speed up the process of finding satisfactory solutions where optimal solutions are impractical. The introduction to this Handbook provides an overview of the history of Heuristics along with main issues regarding the methodologies covered. This is followed by Chapters containing various examples of local searches, search strategies and Metaheuristics, leading to an analyses of Heuristics and search algorithms. The reference concludes with numerous illustrations of the highly applicable nature and implementation of Heuristics in our daily life. Each chapter of this work includes an abstract/introduction with a short description of the methodology. Key words are also necessary as part of top-matter to each chapter to enable maximum search engine optimization. Next, chapters will include discussion of the adaptation of this methodology to solve a difficult optimization problem, and experiments on a set of representative problems.

This newly expanded and updated second edition of the best-selling classic continues to take the "mystery" out of designing algorithms, and analyzing their efficacy and efficiency. Expanding on the first edition, the book now serves as the primary textbook of choice for algorithm design courses while maintaining its status as the premier practical reference guide to algorithms for programmers, researchers, and students. The reader-friendly Algorithm Design Manual provides straightforward access to combinatorial algorithms technology, stressing design over analysis. The first part, Techniques, provides accessible instruction on methods for designing and analyzing computer algorithms. The second part, Resources, is intended for browsing and reference, and comprises the catalog of algorithmic resources, implementations and an extensive bibliography. NEW to the second edition: • Doubles the tutorial material and exercises over the first edition • Provides full online support for lecturers, and a completely updated and improved website component with lecture slides, audio and video • Contains a unique catalog identifying the 75 algorithmic problems that arise most often in practice, leading the reader down the right path to solve them • Includes several NEW "war stories" relating experiences from real-world applications • Provides up-to-date links leading to the very best algorithm implementations available in C, C++, and Java

The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every chapter includes worked examples and exercises to test understanding. Programming tutorials are offered on the book's web site.