@inproceedings{34176,
  abstract     = {{Cascaded H-bridge Converters (CHBs) are a promising solution in converting power from a three-phase medium voltage of 6.6 kV...30 kV to a lower DC-voltage in the range of 100 V...1 kV to provide pure DC power to applications such as electrolyzers for hydrogen generation, data centers with a DC power distribution and DC microgrids. CHBs can be interpreted as modular multilevel converters with an isolated DC-DC output stage per module, require a large DC-link capacitor for each module to handle the second harmonic voltage ripple caused by the fluctuating input power within a fundamental grid period. Without a zero-sequence voltage injection, star-connected CHBs are operated with approximately sinusoidal arm voltages and currents. The floating star point potential enables to utilize different zero-sequence voltage injection techniques such as a third-harmonic injection with 1/6 of the grid voltage amplitude or a Min-Max voltage injection. Both well-known methods have the advantage to reduce the peak arm voltage and thereby the number of required modules by 13.4 % (to √ 3 2). This paper proves analytically that the third-harmonic injection with 1/6 of the grid voltage amplitude reduces the second harmonic voltage ripple by only 15.1 % compared to no-voltage injection for unity power factor operation and balanced grid voltages. Then it is shown, that the Min-Max injection has the often overlooked advantage of reducing the second harmonic voltage ripple by even 18.8 %. By applying the here proposed zero-sequence voltage injection in saturation modulation, the second harmonic voltage ripple of the DC-link capacitors is reduced by even 24.3 %, while still requiring the same number of modules as the Min-Max injection. For a realistic number of reserve modules, the overall energy ripple in the DC-link capacitors is reduced by 40 %.}},
  author       = {{Unruh, Roland and Schafmeister, Frank and Böcker, Joachim}},
  booktitle    = {{24th European Conference on Power Electronics and Applications (EPE'22 ECCE Europe)}},
  isbn         = {{978-9-0758-1539-9}},
  keywords     = {{Cascaded H-Bridge, Solid-State Transformer, Zero sequence voltage, Third harmonic injection, Capacitor voltage ripple}},
  location     = {{Hanover, Germany}},
  publisher    = {{IEEE}},
  title        = {{{Zero-Sequence Voltage Reduces DC-Link Capacitor Demand in Cascaded H-Bridge Converters for Large-Scale Electrolyzers by 40%}}},
  year         = {{2022}},
}

@inproceedings{46306,
  abstract     = {{Hyperparameter optimization (HPO) is a key component of machine learning models for achieving peak predictive performance. While numerous methods and algorithms for HPO have been proposed over the last years, little progress has been made in illuminating and examining the actual structure of these black-box optimization problems. Exploratory landscape analysis (ELA) subsumes a set of techniques that can be used to gain knowledge about properties of unknown optimization problems. In this paper, we evaluate the performance of five different black-box optimizers on 30 HPO problems, which consist of two-, three- and five-dimensional continuous search spaces of the XGBoost learner trained on 10 different data sets. This is contrasted with the performance of the same optimizers evaluated on 360 problem instances from the black-box optimization benchmark (BBOB). We then compute ELA features on the HPO and BBOB problems and examine similarities and differences. A cluster analysis of the HPO and BBOB problems in ELA feature space allows us to identify how the HPO problems compare to the BBOB problems on a structural meta-level. We identify a subset of BBOB problems that are close to the HPO problems in ELA feature space and show that optimizer performance is comparably similar on these two sets of benchmark problems. We highlight open challenges of ELA for HPO and discuss potential directions of future research and applications.}},
  author       = {{Schneider, Lennart and Schäpermeier, Lennart and Prager, Raphael Patrick and Bischl, Bernd and Trautmann, Heike and Kerschke, Pascal}},
  booktitle    = {{Parallel Problem Solving from Nature — PPSN XVII}},
  editor       = {{Rudolph, Günter and Kononova, Anna V. and Aguirre, Hernán and Kerschke, Pascal and Ochoa, Gabriela and Tušar, Tea}},
  isbn         = {{978-3-031-14714-2}},
  pages        = {{575–589}},
  publisher    = {{Springer International Publishing}},
  title        = {{{HPO x ELA: Investigating Hyperparameter Optimization Landscapes by Means of Exploratory Landscape Analysis}}},
  doi          = {{10.1007/978-3-031-14714-2_40}},
  year         = {{2022}},
}

@article{46308,
  abstract     = {{Single-objective continuous optimization can be challenging, especially when dealing with multimodal problems. This work sheds light on the effects that multi-objective optimization may have in the single-objective space. For this purpose, we examine the inner mechanisms of the recently developed sophisticated local search procedure SOMOGSA. This method solves multimodal single-objective continuous optimization problems based on first expanding the problem with an additional objective (e.g., a sphere function) to the bi-objective domain and subsequently exploiting local structures of the resulting landscapes. Our study particularly focuses on the sensitivity of this multiobjectivization approach w.r.t. (1) the parametrization of the artificial second objective, as well as (2) the position of the initial starting points in the search space. As SOMOGSA is a modular framework for encapsulating local search, we integrate Nelder–Mead local search as optimizer in the respective module and compare the performance of the resulting hybrid local search to its original single-objective counterpart. We show that the SOMOGSA framework can significantly boost local search by multiobjectivization. Hence, combined with more sophisticated local search and metaheuristics, this may help solve highly multimodal optimization problems in the future.}},
  author       = {{Aspar, Pelin and Steinhoff, Vera and Schäpermeier, Lennart and Kerschke, Pascal and Trautmann, Heike and Grimme, Christian}},
  journal      = {{Natural Computing}},
  pages        = {{1–15}},
  title        = {{{The objective that freed me: a multi-objective local search approach for continuous single-objective optimization}}},
  doi          = {{10.1007/s11047-022-09919-w}},
  volume       = {{1}},
  year         = {{2022}},
}

@inproceedings{35126,
  author       = {{Förster, Nikolas and Hölscher, Jonas and Piepenbrock, Till and Rehlaender, Philipp and Wallscheid, Oliver and Schafmeister, Frank and Böcker, Joachim}},
  booktitle    = {{2022 24th European Conference on Power Electronics and Applications (EPE’22 ECCE Europe)}},
  pages        = {{P.1--P.9}},
  title        = {{{An Open-Source FEM Magnetic Toolbox for Calculating Electric and Thermal Behavior of Power Electronic Magnetic Components}}},
  year         = {{2022}},
}

@article{33952,
  abstract     = {{<jats:p>Aufgrund der heterogenen Schülerschaft im Berufsfeld Ernährung und Hauswirtschaft müssen Studierende für sprachbildenden Fachunterricht professionalisiert werden. Aufbauend auf einer theoretischen Fundierung werden konkrete Umsetzungsbeispiele anhand von drei exemplarischen Online-Modulen für den Ausbildungsberuf Hotelfachfrau/-mann vorgestellt.</jats:p>}},
  author       = {{Dehn, Freya and Meyer, Anja and Niederhaus, Constanze and Schlegel-Matthies, Kirsten}},
  issn         = {{2193-8806}},
  journal      = {{HiBiFo – Haushalt in Bildung & Forschung}},
  number       = {{3}},
  pages        = {{3--17}},
  publisher    = {{Verlag Barbara Budrich GmbH}},
  title        = {{{Professionalisierung von Lehramtsstudierenden für sprachbildenden Fachunterricht im Berufsfeld Ernährung und Hauswirtschaft}}},
  doi          = {{10.3224/hibifo.v11i3.01}},
  volume       = {{11}},
  year         = {{2022}},
}

@techreport{47094,
  author       = {{Bartels, Lara and Kesternich, Martin}},
  issn         = {{1556-5068}},
  keywords     = {{General Earth and Planetary Sciences, General Environmental Science}},
  publisher    = {{ZEW Discussion Paper 22-040}},
  title        = {{{Motivate the Crowd or Crowd-Them Out? The Impact of Local Government Spending on the Voluntary Provision of a Green Public Good}}},
  doi          = {{10.2139/ssrn.4251592}},
  year         = {{2022}},
}

@techreport{47096,
  author       = {{Chlond, Bettina and Goeschl, Timo and Kesternich, Martin}},
  issn         = {{1556-5068}},
  keywords     = {{General Earth and Planetary Sciences, General Environmental Science}},
  publisher    = {{ZEW Discussion Paper  22-020}},
  title        = {{{More Money or Better Procedures? Evidence From an Energy Efficiency Assistance Program}}},
  doi          = {{10.2139/ssrn.4151557}},
  year         = {{2022}},
}

@techreport{47092,
  author       = {{Kesternich, Martin and Osberghaus, Daniel and Botzen, Willem Jan Wouter}},
  issn         = {{1556-5068}},
  keywords     = {{General Earth and Planetary Sciences, General Environmental Science}},
  publisher    = {{ZEW Discussion Paper 22-055}},
  title        = {{{The Intention-Behavior Gap in Climate Change Adaptation}}},
  doi          = {{10.2139/ssrn.4288341}},
  year         = {{2022}},
}

@techreport{47097,
  author       = {{Chlond, Bettina and Goeschl, Timo  and Kesternich, Martin}},
  publisher    = {{ZEW Policy Brief 22-01}},
  title        = {{{Wie lässt sich die Energieeffizienz in einkommensschwachen Haushalten steigern?}}},
  year         = {{2022}},
}

@inproceedings{48861,
  abstract     = {{Generating instances of different properties is key to algorithm selection methods that differentiate between the performance of different solvers for a given combinatorial optimization problem. A wide range of methods using evolutionary computation techniques has been introduced in recent years. With this paper, we contribute to this area of research by providing a new approach based on quality diversity (QD) that is able to explore the whole feature space. QD algorithms allow to create solutions of high quality within a given feature space by splitting it up into boxes and improving solution quality within each box. We use our QD approach for the generation of TSP instances to visualize and analyze the variety of instances differentiating various TSP solvers and compare it to instances generated by established approaches from the literature.}},
  author       = {{Bossek, Jakob and Neumann, Frank}},
  booktitle    = {{Proceedings of the Genetic and Evolutionary Computation Conference}},
  isbn         = {{978-1-4503-9237-2}},
  keywords     = {{instance features, instance generation, quality diversity, TSP}},
  pages        = {{186–194}},
  publisher    = {{Association for Computing Machinery}},
  title        = {{{Exploring the Feature Space of TSP Instances Using Quality Diversity}}},
  doi          = {{10.1145/3512290.3528851}},
  year         = {{2022}},
}

@inproceedings{48868,
  author       = {{Bossek, Jakob and Neumann, Aneta and Neumann, Frank}},
  booktitle    = {{Proceedings of the Genetic and Evolutionary Computation Conference Companion}},
  isbn         = {{978-1-4503-9268-6}},
  pages        = {{824–842}},
  publisher    = {{Association for Computing Machinery}},
  title        = {{{Evolutionary Diversity Optimization for Combinatorial Optimization: Tutorial at GECCO’22, Boston, USA}}},
  doi          = {{10.1145/3520304.3533626}},
  year         = {{2022}},
}

@inproceedings{48882,
  abstract     = {{In multimodal multi-objective optimization (MMMOO), the focus is not solely on convergence in objective space, but rather also on explicitly ensuring diversity in decision space. We illustrate why commonly used diversity measures are not entirely appropriate for this task and propose a sophisticated basin-based evaluation (BBE) method. Also, BBE variants are developed, capturing the anytime behavior of algorithms. The set of BBE measures is tested by means of an algorithm configuration study. We show that these new measures also transfer properties of the well-established hypervolume (HV) indicator to the domain of MMMOO, thus also accounting for objective space convergence. Moreover, we advance MMMOO research by providing insights into the multimodal performance of the considered algorithms. Specifically, algorithms exploiting local structures are shown to outperform classical evolutionary multi-objective optimizers regarding the BBE variants and respective trade-off with HV.}},
  author       = {{Heins, Jonathan and Rook, Jeroen and Schäpermeier, Lennart and Kerschke, Pascal and Bossek, Jakob and Trautmann, Heike}},
  booktitle    = {{Parallel Problem Solving from Nature (PPSN XVII)}},
  editor       = {{Rudolph, Günter and Kononova, Anna V. and Aguirre, Hernán and Kerschke, Pascal and Ochoa, Gabriela and Tusar, Tea}},
  isbn         = {{978-3-031-14714-2}},
  keywords     = {{Anytime behavior, Benchmarking, Continuous optimization, Multi-objective optimization, Multimodality, Performance metric}},
  pages        = {{192–206}},
  publisher    = {{Springer International Publishing}},
  title        = {{{BBE: Basin-Based Evaluation of Multimodal Multi-objective Optimization Problems}}},
  doi          = {{10.1007/978-3-031-14714-2_14}},
  year         = {{2022}},
}

@inproceedings{48896,
  abstract     = {{Hardness of Multi-Objective (MO) continuous optimization problems results from an interplay of various problem characteristics, e. g. the degree of multi-modality. We present a benchmark study of classical and diversity focused optimizers on multi-modal MO problems based on automated algorithm configuration. We show the large effect of the latter and investigate the trade-off between convergence in objective space and diversity in decision space.}},
  author       = {{Rook, Jeroen and Trautmann, Heike and Bossek, Jakob and Grimme, Christian}},
  booktitle    = {{Proceedings of the Genetic and Evolutionary Computation Conference Companion}},
  isbn         = {{978-1-4503-9268-6}},
  keywords     = {{configuration, multi-modality, multi-objective optimization}},
  pages        = {{356–359}},
  publisher    = {{Association for Computing Machinery}},
  title        = {{{On the Potential of Automated Algorithm Configuration on Multi-Modal Multi-Objective Optimization Problems}}},
  doi          = {{10.1145/3520304.3528998}},
  year         = {{2022}},
}

@article{51294,
  abstract     = {{<jats:p>Der Bericht gibt Einblicke in die Tagung „Fachdidaktische Entwicklungsforschung in der Deutschdidaktik – Gegenstandsspezifische Lernprozesse in den Blick nehmen“. Diese fand am 22. und 23.03.2022 an der Bergischen Universität Wuppertal statt. Im Fokus der Tagung stand die Fragestellung, wie Design-Based Research als Forschungsmethode in der Deutschdidaktik eingesetzt werden kann. Hierzu wurden entsprechende Projekte sowohl unter methodologischer als auch unter fachdidaktischer Perspektive diskutiert.</jats:p>}},
  author       = {{Drepper, Laura and Uhl, Benjamin}},
  issn         = {{2751-6792}},
  journal      = {{Didaktik Deutsch}},
  number       = {{52/53}},
  publisher    = {{University Library J. C. Senckenberg}},
  title        = {{{Tagungsbericht: „Fachdidaktische Entwicklungsforschung in der Deutschdidaktik – Gegenstandsspezifische Lernprozesse in den Blick nehmen“ (22.03.2022 bis 23.03.2022, Bergische Universität Wuppertal)}}},
  doi          = {{10.21248/dideu.97}},
  year         = {{2022}},
}

@article{47561,
  abstract     = {{<jats:title>Abstract</jats:title><jats:p>Additive manufacturing is a promising tool for tailored solutions in chemical engineering. This applies in particular to the design of lab‐scale packed bed columns. We present experimental results to characterize a lab‐scale 3D printed structured metal packing and compare it to a conventional counterpart. The results indicate that necessary adjustments for the manufacturing process of the metal material have an influence on important operating parameters, resulting in higher specific pressure drop, slightly higher liquid holdup and lower mass transfer efficiency.</jats:p>}},
  author       = {{Riese, Julia and Reitze, Arnulf and Grünewald, Marcus}},
  issn         = {{0009-286X}},
  journal      = {{Chemie Ingenieur Technik}},
  keywords     = {{Industrial and Manufacturing Engineering, General Chemical Engineering, General Chemistry}},
  number       = {{7}},
  pages        = {{993--1001}},
  publisher    = {{Wiley}},
  title        = {{{Experimental Characterization of 3D Printed Structured Metal Packing with an Enclosed Column Wall}}},
  doi          = {{10.1002/cite.202200002}},
  volume       = {{94}},
  year         = {{2022}},
}

@inproceedings{32573,
  author       = {{Maehren, Marcel and Nieting, Philipp and Hebrok, Sven Niclas and Merget, Robert and Somorovsky, Juraj and Schwenk, Jörg}},
  booktitle    = {{31st USENIX Security Symposium (USENIX Security 22)}},
  publisher    = {{USENIX Association}},
  title        = {{{TLS-Anvil: Adapting Combinatorial Testing for TLS Libraries}}},
  year         = {{2022}},
}

@article{53240,
  author       = {{Tavana, Madjid and Azadmanesh, Abdolreza and Nasr, Arash Khalili and Mina, Hassan}},
  issn         = {{1368-3500}},
  journal      = {{Current Issues in Tourism}},
  keywords     = {{Tourism, Leisure and Hospitality Management, Geography, Planning and Development}},
  number       = {{22}},
  pages        = {{3709--3734}},
  publisher    = {{Informa UK Limited}},
  title        = {{{A multicriteria-optimization model for cultural heritage renovation projects and public-private partnerships in the hospitality industry}}},
  doi          = {{10.1080/13683500.2021.2015299}},
  volume       = {{25}},
  year         = {{2022}},
}

@article{53241,
  author       = {{Khalili-Damghani, Kaveh and Tavana, Madjid and Ghasemi, Peiman}},
  issn         = {{0254-5330}},
  journal      = {{Annals of Operations Research}},
  keywords     = {{Management Science and Operations Research, General Decision Sciences}},
  number       = {{1}},
  pages        = {{103--141}},
  publisher    = {{Springer Science and Business Media LLC}},
  title        = {{{A stochastic bi-objective simulation–optimization model for cascade disaster location-allocation-distribution problems}}},
  doi          = {{10.1007/s10479-021-04191-0}},
  volume       = {{309}},
  year         = {{2022}},
}

@article{53245,
  author       = {{Moazzeni, Sahar and Tavana, Madjid and Mostafayi Darmian, Sobhan}},
  issn         = {{0959-6526}},
  journal      = {{Journal of Cleaner Production}},
  publisher    = {{Elsevier BV}},
  title        = {{{A dynamic location-arc routing optimization model for electric waste collection vehicles}}},
  doi          = {{10.1016/j.jclepro.2022.132571}},
  volume       = {{364}},
  year         = {{2022}},
}

@article{53253,
  author       = {{Tavana, Madjid and Nazari-Shirkouhi, Salman and Mashayekhi, Amir and Mousakhani, Saeed}},
  issn         = {{2662-2556}},
  journal      = {{Operations Research Forum}},
  number       = {{1}},
  publisher    = {{Springer Science and Business Media LLC}},
  title        = {{{An Integrated Data Mining Framework for Organizational Resilience Assessment and Quality Management Optimization in Trauma Centers}}},
  doi          = {{10.1007/s43069-022-00132-0}},
  volume       = {{3}},
  year         = {{2022}},
}