This book contains the proceedings of the 19th Cologne-Twente Workshop on Graphs and Combinatorial Optimization, held during June 20-22, 2023, in Garmisch-Partenkirchen, Germany. This successful series of international workshops is known to attract high-quality research on the theory and application of discrete algorithms, graphs, and combinatorial optimization in a wide sense. The papers collected in this book represent cutting-edge research by leading researchers and attract a broad readership in academia worldwide. The book is addressed to researchers and advanced students, but also to professionals in industry concerned with algorithm design and optimization problems in different areas of application.

Collects newest results in the areas of discrete mathematics, graph theory, OR, and combinatorial optimization Covers connectivity, distance geometry, decomposition, and coloring Features machine learning, exact and heuristic methods, meta-heuristics as well as mixed-integer programming

Autorentext
Andreas Brieden is professor for "Statistics and Risk Management" in the
department of Economics and Management at Universität der Bundeswehr
München, which position he has held since 2005. He studied Applied Mathematics at University of Trier 1989-94; Dipl.-Math. Dec. 1994; doctorate 1998 with award at Technical University Munich; Dr. habil. 2003; venia legendi "Mathematics". Andreas Brieden published more than30 articles in the context of Discrete and Combinatorial Optimization; in 2013, he was awarded together with Peter Gritzmann and Steffen Borgward the European Excellence in Practice Award of the Association of the European Operational Research Societies within IFORS.

Stefan Pickl is professor for "Operations Research" in the department of computer science at Universität der Bundeswehr München, which position he has held since 2005. He studied mathematics, electrical engineering, and philosophy at TU Darmstadt and EPFL Lausanne 1987-93; Dipl.-Ing.1993; doctorate 1998 with award; assistant professor at Cologne University; Dr. habil. 2005; venia legend "Mathematics". Stefan Pickl published more than 80 articles and several books in the context of "Modelling, Simulation and Data-Driven Optimization of Dynamical Systems
and Networks". Since 2010, Prof. Pickl is the chair of the Advisory Board of the German OR Society. In 2001, he organized the first Cologne-Twente Workshop on Graphs and Combinatorial Optimization CTW.

Markus Siegle is professor for "Design of Computer and Communication Systems" in the department of computer science at Universität der Bundeswehr München, which position he has held since 2003. He studied computer science and electrical engineering at Stuttgart University
1984-89; Dipl.-Inf. 1989; master's degree 1990 (as Fulbright scholar) at North Carolina State University; researcher at Erlangen University where he obtained the doctoral (1995) and habilitation degree (2002). Markus Siegle published more than 40 articles in the area of modelling, analysis, and verification of probabilistic and non-deterministic concurrent systems, with special focus on performance and dependability. He has been involved in numerous scientific events, e.g. as PC co-chair of the OR 2010 Munich conference and PC co-chair of the QEST 2013 conference.

Inhalt

On syntactical graphs-of-words.- k-slow Burning: Complexity and Upper Bounds.- Exact approaches for the Connected Vertex Cover problem.- Handling Sub-symmetry in Integer Programming using Activation Handlers.- Online Facility Location: comparing ad-hoc and MIP-based algorithms.- A Multivariate Complexity Analysis of the Generalized Noah's Ark Problem.- On the Optimality Gap of Full Airport Slot Assignments: Capacity-limited Packing with Pareto Optimality Constraints.- The algorithmic complexity of the Paired Matching problem.- Edge Contraction and Forbidden Induced Subgraphs.- Rigidity of frameworks on spheres.- Discrepancies of subtrees.-Data-driven feasibility for the Resource Constraint Shortest Path Problem.-Monte-Carlo Integration on a Union of Polytopes.- Managing Time Expanded Networks: The Strong Lift Problem.