@incollection{GotzesBuchholzKallrathetal.2025, author = {Gotzes, Uwe and Buchholz, Annika and Kallrath, Josef and Lindner, Niels and Koch, Thorsten}, title = {Flexible Pooling Pattern Design with Integer Programming}, volume = {226}, booktitle = {Theory, Algorithms and Experiments in Applied Optimization. In Honor of the 70th Birthday of Panos Pardalos}, publisher = {Springer}, year = {2025}, abstract = {Sample pooling has the potential to significantly enhance large-scale screening procedures, especially in scenarios like the COVID-19 pandemic, where rapid and widespread PCR testing has been crucial. Efficient strategies are essential to increase the testing capacity, i.e., the number of tests that can be processed within a given timeframe. Non-adaptive pooling strategies can further streamline the testing process by reducing the required testing rounds. In contrast to adaptive strategies, where subsequent tests depend on prior results, non-adaptive pooling processes all samples in a single round, eliminating the need for sequential retesting and reducing delays. This paper presents a highly flexible method based on integer programming to design optimized pooling patterns suitable for various applications, including medical diagnostics and quality control in industrial production. Using coronavirus testing as a case study, we formulate and solve optimization and satisfiability models that compute efficient pool designs. Our optimized pooling does not only increase testing capacity, but also accelerates the testing process and reduces overall costs. The proposed method is adaptable and can be seamlessly integrated into automated testing systems.}, language = {en} } @incollection{DiekerhofMontiLebedevaetal.2020, author = {Diekerhof, M. and Monti, A. and Lebedeva, E. and Tkaczyk, A. H. and Y{\"u}ksel-Erg{\"u}n, I. and Zittel, J. and Escudero, L. F. and Soroudi, A. and Helmberg, C. and Kanov{\´i}c, Ž. and Petkovic, M. and Lacalandra, F. and Frangioni, A. and Lee, J. and De Filippo, A. and Lombardi, M. and Milano, M. and Ezran, P. and Haddad, Y.}, title = {Production and Demand Management}, volume = {4}, booktitle = {Mathematical Optimization for Efficient and Robust Energy Networks}, publisher = {Springer}, isbn = {978-3-030-57442-0}, doi = {https://doi.org/10.1007/978-3-030-57442-0_1}, year = {2020}, abstract = {Demand Side Management (DSM) is usually considered as a process of energy consumption shifting from peak hours to off-peak times. DSM does not always reduce total energy consumption, but it helps to meet energy demand and supply. For example, it balances variable generation from renewables (such as solar and wind) when energy demand differs from renewable generation.}, language = {en} } @incollection{SchwarzLacalandraScheweetal.2020, author = {Schwarz, R. and Lacalandra, F. and Schewe, L. and Bettinelli, A. and Vigo, D. and Bischi, A. and Parriani, T. and Martelli, E. and Vuik, K. and Lenz, R. and Madsen, H. and Blanco, I. and Guericke, D. and Y{\"u}ksel-Erg{\"u}n, I. and Zittel, J.}, title = {Network and Storage}, volume = {4}, booktitle = {Mathematical Optimization for Efficient and Robust Energy Networks}, publisher = {Springer}, isbn = {978-3-030-57442-0}, doi = {https://doi.org/10.1007/978-3-030-57442-0_6}, year = {2020}, abstract = {Natural gas is considered by many to be the most important energy source for the future. The objectives of energy commodities strategic problems can be mainly related to natural gas and deal with the definition of the "optimal" gas pipelines design which includes a number of related sub problems such as: Gas stations (compression) location and Gas storage locations, as well as compression station design and optimal operation.}, language = {en} } @incollection{PedersenLjubić2024, author = {Pedersen, Jaap and Ljubić, Ivana}, title = {Prize-Collecting Steiner Tree Problem and its Variants}, booktitle = {Encyclopedia of Optimization}, editor = {Pardalos, Panos M. and Prokopyev, Oleg A.}, publisher = {Springer International Publishing}, address = {Cham}, doi = {10.1007/978-3-030-54621-2_869-1}, year = {2024}, language = {en} } @incollection{HoppmannBaumMexiBurdakovetal.2020, author = {Hoppmann-Baum, Kai and Mexi, Gioni and Burdakov, Oleg and Casselgren, Carl Johan and Koch, Thorsten}, title = {Minimum Cycle Partition with Length Requirements}, volume = {12296}, booktitle = {Integration of Constraint Programming, Artificial Intelligence, and Operations Research}, editor = {Hebrard, Emmanuel and Musliu, Nysret}, publisher = {Springer International Publishing}, address = {Cham}, isbn = {978-3-030-58941-7}, doi = {10.1007/978-3-030-58942-4_18}, pages = {273 -- 282}, year = {2020}, abstract = {In this article we introduce a Minimum Cycle Partition Problem with Length Requirements (CPLR). This generalization of the Travelling Salesman Problem (TSP) originates from routing Unmanned Aerial Vehicles (UAVs). Apart from nonnegative edge weights, CPLR has an individual critical weight value associated with each vertex. A cycle partition, i.e., a vertex disjoint cycle cover, is regarded as a feasible solution if the length of each cycle, which is the sum of the weights of its edges, is not greater than the critical weight of each of its vertices. The goal is to find a feasible partition, which minimizes the number of cycles. In this article, a heuristic algorithm is presented together with a Mixed Integer Programming (MIP) formulation of CPLR. We furthermore introduce a conflict graph, whose cliques yield valid constraints for the MIP model. Finally, we report on computational experiments conducted on TSPLIB-based test instances.}, language = {en} }