@article{44672,
  abstract     = {{With enhancing digitalization, condition monitoring is used in an increasing number of application fields across various industrial sectors. By its application, increased reliability as well as reduced risks and costs can be achieved. Based on different approaches, technical systems are monitored and measured data is analyzed to enable condition-based or predictive maintenance. To this end, machine learning approaches are usually implemented to diagnose the health states or predict the health index of the monitored system. However, these trained models are often black-box models, not intuitively explainable for a human. To overcome this shortcoming, a model-based approach based on physics is developed for piezoelectric bending actuators. Such a model enables a transparent representation of the system. Moreover, the model-based approach is extended by a parameter-estimation to account for sudden changes in behavior e. g. caused by occurring cracks.}},
  author       = {{Bender, Amelie}},
  issn         = {{0924-4247}},
  journal      = {{Sensors and Actuators A: Physical}},
  keywords     = {{Condition Monitoring, Model-based approach Diagnostics, Varying conditions, Explainability, Piezoelectric bending actuators}},
  publisher    = {{Elsevier BV}},
  title        = {{{Model-based condition monitoring of piezoelectric bending actuators}}},
  doi          = {{10.1016/j.sna.2023.114399}},
  volume       = {{357}},
  year         = {{2023}},
}

@article{44687,
  abstract     = {{Entwicklungsprojekte stehen in einem Spannungsfeld von Volatilität, Unsicherheit, Komplexität und Ambiguität (VUCA). Resilient Requirements Engineering (RRE) ist ein vielversprechender Ansatz, diesen Rahmenbedingungen gerecht zu werden und erfolgreich zu entwickeln. Es werden Methoden aus den drei Innovationsfeldern des RRE – Vorausschau, Effizienz und Nachhaltigkeit – angewendet, um Effizienzpotenziale in der Produktentwicklung zu nutzen und frühzeitig Nachhaltigkeitsdimensionen in der Ermittlung von Stakeholderbedürfnissen zu verankern.}},
  author       = {{Gräßler, Iris and Oleff, Christian and Preuß, Daniel and Koch, Anna-Sophie}},
  issn         = {{2511-0896}},
  journal      = {{Zeitschrift für wirtschaftlichen Fabrikbetrieb}},
  keywords     = {{Management Science and Operations Research, Strategy and Management, General Engineering}},
  number       = {{4}},
  pages        = {{222--225}},
  publisher    = {{Walter de Gruyter GmbH}},
  title        = {{{Resilient Requirements Engineering}}},
  doi          = {{10.1515/zwf-2023-1030}},
  volume       = {{118}},
  year         = {{2023}},
}

@article{44857,
  abstract     = {{Ancestral reconstruction is a classic task in comparative genomics. Here, we study the genome median problem, a related computational problem which, given a set of three or more genomes, asks to find a new genome that minimizes the sum of pairwise distances between it and the given genomes. The distance stands for the amount of evolution observed at the genome level, for which we determine the minimum number of rearrangement operations necessary to transform one genome into the other. For almost all rearrangement operations the median problem is NP-hard, with the exception of the breakpoint median that can be constructed efficiently for multichromosomal circular and mixed genomes. In this work, we study the median problem under a restricted rearrangement measure called c4-distance, which is closely related to the breakpoint and the DCJ distance. We identify tight bounds and decomposers of the c4-median and develop algorithms for its construction, one exact ILP-based and three combinatorial heuristics. Subsequently, we perform experiments on simulated data sets. Our results suggest that the c4-distance is useful for the study the genome median problem, from theoretical and practical perspectives.}},
  author       = {{Silva, Helmuth O.M. and Rubert, Diego P. and Araujo, Eloi and Steffen, Eckhard and Doerr, Daniel and Martinez, Fábio V.}},
  issn         = {{0399-0559}},
  journal      = {{RAIRO - Operations Research}},
  keywords     = {{Management Science and Operations Research, Computer Science Applications, Theoretical Computer Science}},
  number       = {{3}},
  pages        = {{1045--1058}},
  publisher    = {{EDP Sciences}},
  title        = {{{Algorithms for the genome median under a restricted measure of rearrangement}}},
  doi          = {{10.1051/ro/2023052}},
  volume       = {{57}},
  year         = {{2023}},
}

@article{45782,
  abstract     = {{<jats:p>The development of automotive components with reduced greenhouse gas (GHG) emissions is needed to reduce overall vehicle emissions. Life Cycle Engineering (LCE) based on Life Cycle Assessment (LCA) supports this by providing holistic information and improvement potentials regarding eco-efficient products. Key factors influencing LCAs of automotive components, such as material production, will change in the future. First approaches for integrating future scenarios for these key factors into LCE already exist, but they only consider a limited number of parameters and scenarios. This work aims to develop a method that can be practically applied in the industry for integrating prospective LCAs (pLCA) into the LCE of automotive components, considering relevant parameters and consistent scenarios. Therefore, pLCA methods are further developed to investigate the influence of future scenarios on the GHG emissions of automotive components. The practical application is demonstrated for a vehicle component with different design options. This paper shows that different development paths of the foreground and background system can shift the ecological optimum of design alternatives. Therefore, future pathways of relevant parameters must be considered comprehensively to reduce GHG emissions of future vehicles. This work contributes to the methodological and practical integration of pLCA into automotive development processes and provides quantitative results.</jats:p>}},
  author       = {{Grenz, Julian and Ostermann, Moritz and Käsewieter, Karoline and Cerdas, Felipe and Marten, Thorsten and Herrmann, Christoph and Tröster, Thomas}},
  issn         = {{2071-1050}},
  journal      = {{Sustainability}},
  keywords     = {{prospective LCA, life cycle engineering (LCE), lightweight design, automotive components, body parts, circular economy, steel, aluminum, hybrid materials, fiber metal laminates}},
  number       = {{13}},
  publisher    = {{MDPI AG}},
  title        = {{{Integrating Prospective LCA in the Development of Automotive Components}}},
  doi          = {{10.3390/su151310041}},
  volume       = {{15}},
  year         = {{2023}},
}

@inproceedings{45793,
  abstract     = {{The global megatrends of digitization and sustainability lead to new challenges for the design and management of technical products in industrial companies. Product management - as the bridge between market and company - has the task to absorb and combine the manifold requirements and make the right product-related decisions. In the process, product management is confronted with heterogeneous information, rapidly changing portfolio components, as well as increasing product, and organizational complexity. Combining and utilizing data from different sources, e.g., product usage data and social media data leads to promising potentials to improve the quality of product-related decisions. In this paper, we reinforce the need for data-driven product management as an interdisciplinary field of action. The state of data-driven product management in practice was analyzed by conducting workshops with six manufacturing companies and hosting a focus group meeting with experts from different industries. We investigate the expectations and derive requirements leading us to open research questions, a vision for data-driven product management, and a research agenda to shape future research efforts.}},
  author       = {{Grigoryan, Khoren and Fichtler, Timm and Schreiner, Nick and Rabe, Martin and Panzner, Melina and Kühn, Arno and Dumitrescu, Roman and Koldewey, Christian}},
  booktitle    = {{Procedia CIRP 33}},
  keywords     = {{Product Management, Data Analytics, Data-Driven Design, Product-related data, Lifecycle Data, Tool-support}},
  location     = {{Sydney}},
  title        = {{{Data-Driven Product Management: A Practitioner-Driven Research Agenda}}},
  year         = {{2023}},
}

@article{46487,
  author       = {{Zander, K.K. and Nguyen, D. and Mirbabaie, Milad and Garnett, S.T.}},
  issn         = {{2212-4209}},
  journal      = {{International Journal of Disaster Risk Reduction}},
  keywords     = {{Geology, Safety Research, Geotechnical Engineering and Engineering Geology, Building and Construction}},
  publisher    = {{Elsevier BV}},
  title        = {{{Aware but not prepared: understanding situational awareness during the century flood in Germany in 2021}}},
  doi          = {{10.1016/j.ijdrr.2023.103936}},
  volume       = {{96}},
  year         = {{2023}},
}

@inproceedings{46500,
  abstract     = {{The security of Industrial Control Systems is relevant both for reliable production system operations and for high-quality throughput in terms of manufactured products. Security measures are designed, operated and maintained by different roles along product and production system lifecycles. Defense-in-Depth as a paradigm builds upon the assumption that breaches are unavoidable. The paper at hand provides an analysis of roles, corresponding Human Factors and their relevance for data theft and sabotage attacks. The resulting taxonomy is reflected by an example related to Additive Manufacturing. The results assist in both designing and redesigning Industrial Control System as part of an entire production system so that Defense-in-Depth with regard to Human Factors is built in by design.}},
  author       = {{Pottebaum, Jens and Rossel, Jost and Somorovsky, Juraj and Acar, Yasemin and Fahr, René and Arias Cabarcos, Patricia and Bodden, Eric and Gräßler, Iris}},
  booktitle    = {{2023 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW)}},
  keywords     = {{Defense-in-Depth, Human Factors, Production Engineering, Product Design, Systems Engineering}},
  location     = {{Delft, Netherlands}},
  pages        = {{379--385}},
  publisher    = {{IEEE}},
  title        = {{{Re-Envisioning Industrial Control Systems Security by Considering Human Factors as a Core Element of Defense-in-Depth}}},
  doi          = {{10.1109/eurospw59978.2023.00048}},
  year         = {{2023}},
}

@book{30291,
  abstract     = {{The volume comprises a variety of research approaches that seek to explore and understand employees’ learning and development through and for work. Working life reveals challenges through technological, economic and societal development that can only rudimentarily be addressed by formal education and training. Workplace learning becomes more and more important for employees and enterprises to successfully cope with these challenges.
Workplace learning is a steadily growing field of educational research but it lacks so far a scholastic canon – there is rather a diversity of research approaches. This volume reflects this diversity by bringing together researchers from different countries and different theoretical backgrounds, presenting their current research on topics that all are relevant for understanding presages, processes and outcomes of workplace learning. Hence, this volume is of relevance for researchers as well as practitioners in the field and policy makers.}},
  editor       = {{Harteis, Christian and Gijbels, David and Kyndt, Eva}},
  isbn         = {{9783030895815}},
  issn         = {{2210-5549}},
  keywords     = {{new generation of researchersthe team level of workplace learningindividual level of workplace learningorganizational level of workplace learningsocietal level of workplace learninginterdependent cross-level research approachesWork AgencyWork-life perspectivesTeam learningTeam climateSocial influences on team learningKnowledge construction in teamsLearning cultureAcknowledgement of competencesTechnology and professional learningCreation of a learning eco-systemDiversity as a challenge for organisationsHigher education as preparation for WPLSocial support in networks and professional learningvocational and professional education}},
  publisher    = {{Springer International Publishing}},
  title        = {{{Research Approaches on Workplace Learning}}},
  doi          = {{10.1007/978-3-030-89582-2}},
  year         = {{2022}},
}

@article{30861,
  abstract     = {{<jats:title>Abstract</jats:title><jats:p>We consider the problem of maximization of metabolite production in bacterial cells formulated as a dynamical optimal control problem (DOCP). According to Pontryagin’s maximum principle, optimal solutions are concatenations of singular and bang arcs and exhibit the chattering or <jats:italic>Fuller</jats:italic> phenomenon, which is problematic for applications. To avoid chattering, we introduce a reduced model which is still biologically relevant and retains the important structural features of the original problem. Using a combination of analytical and numerical methods, we show that the singular arc is dominant in the studied DOCPs and exhibits the <jats:italic>turnpike</jats:italic> property. This property is further used in order to design simple and realistic suboptimal control strategies.</jats:p>}},
  author       = {{Caillau, Jean-Baptiste and Djema, Walid and Gouzé, Jean-Luc and Maslovskaya, Sofya and Pomet, Jean-Baptiste}},
  issn         = {{0022-3239}},
  journal      = {{Journal of Optimization Theory and Applications}},
  keywords     = {{Applied Mathematics, Management Science and Operations Research, Control and Optimization}},
  publisher    = {{Springer Science and Business Media LLC}},
  title        = {{{Turnpike Property in Optimal Microbial Metabolite Production}}},
  doi          = {{10.1007/s10957-022-02023-0}},
  year         = {{2022}},
}

@inproceedings{29842,
  abstract     = {{To build successful software products, developers continuously have to discover what features the users really need. This discovery can be achieved with continuous experimentation, testing different software variants with distinct user groups, and deploying the superior variant for all users. However, existing approaches do not focus on explicit modeling of variants and experiments, which offers advantages such as traceability of decisions and combinability of experiments. Therefore, our vision is the provision of model-driven continuous experimentation, which provides the developer with a framework for structuring the experimentation process. For that, we introduce the overall concept, apply it to the experimentation on component-based software architectures and point out future research questions. In particular, we show the applicability by combining feature models for modeling the software variants, users, and experiments (i.e., model-driven) with MAPE-K for the adaptation (i.e., continuous experimentation) and implementing the concept based on the component-based Angular framework.}},
  author       = {{Gottschalk, Sebastian and Yigitbas, Enes and Engels, Gregor}},
  booktitle    = {{Proceedings of the 18th International Conference on Software Architecture Companion }},
  keywords     = {{continuous experimentation, model-driven, component-based software architectures, self-adaptation}},
  location     = {{Hawaii}},
  publisher    = {{IEEE}},
  title        = {{{Model-driven Continuous Experimentation on Component-based Software Architectures }}},
  doi          = {{10.1109/ICSA-C54293.2022.00011}},
  year         = {{2022}},
}

@inproceedings{29220,
  abstract     = {{Modern services often comprise several components, such as chained virtual network functions, microservices, or
machine learning functions. Providing such services requires to decide how often to instantiate each component, where to place these instances in the network, how to chain them and route traffic through them. 
To overcome limitations of conventional, hardwired heuristics, deep reinforcement learning (DRL) approaches for self-learning network and service management have emerged recently. These model-free DRL approaches are more flexible but typically learn tabula rasa, i.e., disregard existing understanding of networks, services, and their coordination. 

Instead, we propose FutureCoord, a novel model-based AI approach that leverages existing understanding of networks and services for more efficient and effective coordination without time-intensive training. FutureCoord combines Monte Carlo Tree Search with a stochastic traffic model. This allows FutureCoord to estimate the impact of future incoming traffic and effectively optimize long-term effects, taking fluctuating demand and Quality of Service (QoS) requirements into account. Our extensive evaluation based on real-world network topologies, services, and traffic traces indicates that FutureCoord clearly outperforms state-of-the-art model-free and model-based approaches with up to 51% higher flow success ratios.}},
  author       = {{Werner, Stefan and Schneider, Stefan Balthasar and Karl, Holger}},
  booktitle    = {{IEEE/IFIP Network Operations and Management Symposium (NOMS)}},
  keywords     = {{network management, service management, AI, Monte Carlo Tree Search, model-based, QoS}},
  location     = {{Budapest}},
  publisher    = {{IEEE}},
  title        = {{{Use What You Know: Network and Service Coordination Beyond Certainty}}},
  year         = {{2022}},
}

@phdthesis{29763,
  abstract     = {{Modern-day communication has become more and more digital. While this comes with many advantages such as a more efficient economy, it has also created more and more opportunities for various adversaries to manipulate communication or eavesdrop on it. The Snowden revelations in 2013 further highlighted the seriousness of these threats. To protect the communication of people, companies, and states from such threats, we require cryptography with strong security guarantees.
Different applications may require different security properties from cryptographic schemes. For most applications, however, so-called adaptive security is considered a reasonable minimal requirement of security. Cryptographic schemes with adaptive security remain secure in the presence of an adversary that can corrupt communication partners to respond to messages of the adversaries choice, while the adversary may choose the messages based on previously observed interactions.
While cryptography is associated the most with encryption, this is only one of many primitives that are essential for the security of digital interactions. This thesis presents novel identity-based encryption (IBE) schemes and verifiable random functions (VRFs) that achieve adaptive security as outlined above. Moreover, the cryptographic schemes presented in this thesis are proven secure in the standard model. That is without making use of idealized models like the random oracle model.}},
  author       = {{Niehues, David}},
  keywords     = {{public-key cryptography, lattices, pairings, verifiable random functions, identity-based encryption}},
  title        = {{{More Efficient Techniques for Adaptively-Secure Cryptography}}},
  doi          = {{10.25926/rdtq-jw45}},
  year         = {{2022}},
}

@article{33701,
  abstract     = {{<jats:title>Abstract</jats:title>
               <jats:p>Künstliche Intelligenz bietet großes Potenzial im Engineering. Der Einsatz gestattet insbesondere für Wissensarbeiter eine effiziente Arbeitsteilung, in der beispielsweise fehleranfällige und repetitive Aktivitäten unterstützt werden. Eine erfolgreiche Einführung bedarf einer vorangehenden Analyse von nutzenstiftenden Einsatzpotenzialen, bei der alle Anwendenden frühzeitig einbezogen werden. Der folgende Beitrag verdeutlicht dieses Vorgehen anhand eines realen Beispiels im Sondermaschinenbau.</jats:p>}},
  author       = {{Kharatyan, Aschot and Humpert, Lynn and Anacker, Harald and Dumitrescu, Roman and Wäschle, Moritz and Albers, Albert and Horstmeyer, Sarah}},
  issn         = {{2511-0896}},
  journal      = {{Zeitschrift für wirtschaftlichen Fabrikbetrieb}},
  keywords     = {{Management Science and Operations Research, Strategy and Management, General Engineering}},
  number       = {{6}},
  pages        = {{427--431}},
  publisher    = {{Walter de Gruyter GmbH}},
  title        = {{{Künstliche Intelligenz im Engineering}}},
  doi          = {{10.1515/zwf-2022-1074}},
  volume       = {{117}},
  year         = {{2022}},
}

@article{33710,
  abstract     = {{<jats:title>Abstract</jats:title>
               <jats:p>Um global erfolgreich zu bleiben, wird es bald nicht mehr ausreichen, Kriterien wie ein gutes Produktdesign zu erfüllen. Stattdessen muss der Kundennutzen kontinuierlich über den Produktlebenszyklus hinaus gesteigert werden. Tech-Konzerne verzeichnen bereits Erfolge und verkörpern den Wandel schon heute. Vor diesem Hintergrund ist ein neues Leitbild in der Entwicklung und dem Betrieb von zukünftigen, technischen Systemen erforderlich. EngOps soll diesen Bedarf decken und steht für die agile Kollaboration zwischen Engineering und Operations. Alle Teile des Unternehmens sollen ständig miteinander kooperieren, um so beispielsweise wandelbare Produkte auch nach dem Verkauf entwickeln zu können.</jats:p>}},
  author       = {{Anacker, Harald and Dumitrescu, Roman and Michels, Nico and Rasor, Rik}},
  issn         = {{2511-0896}},
  journal      = {{Zeitschrift für wirtschaftlichen Fabrikbetrieb}},
  keywords     = {{Management Science and Operations Research, Strategy and Management, General Engineering}},
  number       = {{6}},
  pages        = {{405--409}},
  publisher    = {{Walter de Gruyter GmbH}},
  title        = {{{EngOps – Ein Leitbild für das agile Zusammenwirken von Engineering und Operations}}},
  doi          = {{10.1515/zwf-2022-1069}},
  volume       = {{117}},
  year         = {{2022}},
}

@article{33956,
  abstract     = {{<jats:title>Abstract</jats:title>
               <jats:p>Smart Services eröffnen vielfältige Geschäftsmöglichkeiten für produzierende Unternehmen und erfordern zugleich einschneidende Anpassungen ihrer häufig historisch gewachsenen Wertschöpfung. Dieser Beitrag zeigt eine Web-Applikation, die es produzierenden Unternehmen erlaubt, die erforderliche Smart-Service-Transformation zu planen. Dafür werden umfassendes Lösungswissen bereitgestellt und eine individuelle Gestaltungsempfehlungen für die zukünftige Wertschöpfung als Smart-Service-Anbieter gegeben.</jats:p>}},
  author       = {{Reinhold, Jannik and Siewert, Michael and Scholtysik, Michel and Rasor, Anja and Koldewey, Christian and Dumitrescu, Roman}},
  issn         = {{2511-0896}},
  journal      = {{Zeitschrift für wirtschaftlichen Fabrikbetrieb}},
  keywords     = {{Management Science and Operations Research, Strategy and Management, General Engineering}},
  number       = {{5}},
  pages        = {{312--316}},
  publisher    = {{Walter de Gruyter GmbH}},
  title        = {{{Software-gestützte Planung der Smart-Service-Transformation}}},
  doi          = {{10.1515/zwf-2022-1048}},
  volume       = {{117}},
  year         = {{2022}},
}

@inproceedings{36335,
  abstract     = {{Transformation of Fe- and Cu-rich primary phase particles was studied in an Al-Li-based alloy prepared by twin-roll casting. Thin foils for combined STEM and SEM experiments were prepared by electrolytic twin-jet polishing. They were in-situ heated in a TEM heating stage and observed at 200 kV in the JEOL JEM 2200FS electron microscope equipped with STEM HAADF and BF detectors and SEM BSE and SE detectors working both in composition and topographic modes. The resulting structures were combined with EDS mapping performed directly in the heating holder. Dissolution and transformation of Cu- and Fe-rich particles occur above 500 °C. EDS maps acquired on the foil cooled down to room temperature show that Cu and Fe are both still present in newly formed particles, most likely indicating the presence of the Al7Cu2Fe phase.}},
  author       = {{CIESLAR, Miroslav and KŘIVSKÁ, Barbora and KRÁLÍK, Rostislav and BAJTOŠOVÁ, Lucia and Grydin, Olexandr and STOLBCHENKO, Mykhailo and Schaper, Mirko}},
  booktitle    = {{METAL 2022 Conference Proeedings}},
  issn         = {{2694-9296}},
  keywords     = {{Al-Li-based alloy, in-situ TEM, homogenization, phase transformation}},
  location     = {{Brno}},
  publisher    = {{TANGER Ltd.}},
  title        = {{{HOMOGENIZATION OF TWIN-ROLL CAST Al-Li-BASED ALLOY STUDIED BY IN-SITU ELECTRON MICROSCOPY}}},
  doi          = {{10.37904/metal.2022.4438}},
  year         = {{2022}},
}

@article{35111,
  abstract     = {{Forschendes Lernen in der Lehrer:innenbildung ist seit der Ausweitung schulpraktischer Anteile bzw. der Einführung des sogenannten Praxissemesters eng verwoben mit der Lehrer:innenausbildung. Gleichzeitig wird bisher weitestgehend different beantwortet, was Forschendes Lernen ist und sein kann sowie warum es wie hochschuldidaktisch gerahmt wird und werden sollte. Der Beitrag widmet sich dieser Frage. Dabei zeigt sich einerseits, dass hochschuldidaktische Zugänge zur Realisierung Forschenden Lernens in der Lehrer:innenbildung erst vor dem Hintergrund theoretischer Annahmen zur Entwicklung von Lehrpersonen und deren Professionalität sowie zur Gestalt - gemeint ist hier der Beitrag zu dieser Entwicklung sowie der Anteil an Professionalität - Forschenden Lernens entwickelt werden können, eine solche Fundierung aber oftmals ausbleibt. Andererseits wird herausgearbeitet, inwiefern eine Differenz zwischen wissenschaftlicher Forschung und Forschung im Forschenden Lernen besteht. Daran anschließend wird eine habitustheoretische Fundierung Forschenden Lernens vorgestellt und es werden exemplarisch deren Implikationen für die Gestaltung Forschenden Lernens benannt. Abschließend wird anhand empirischer Rekonstruktionen beispielhaft eine praktische Umsetzung diskutiert.}},
  author       = {{Bloh, Thiemo and Caruso, Carina}},
  issn         = {{2199-8825}},
  journal      = {{die hochschullehre}},
  keywords     = {{Forschendes Lernen, Lehrer:innenausbildung, Praxissemester, Professionalisierung / Research-based learning, teacher education, internships, professionalization}},
  number       = {{21}},
  pages        = {{299–312}},
  publisher    = {{wbv }},
  title        = {{{Ein kritisch-multiperspektivischer Blick auf Forschendes Lernen in der Lehrkräftebildung}}},
  doi          = {{10.3278/HSL2221W}},
  volume       = {{8}},
  year         = {{2022}},
}

@article{53238,
  author       = {{Tavana, Madjid and Khalili Nasr, Arash and Mina, Hassan and Michnik, Jerzy}},
  issn         = {{0038-0121}},
  journal      = {{Socio-Economic Planning Sciences}},
  keywords     = {{Management Science and Operations Research, Statistics, Probability and Uncertainty, Strategy and Management, Economics and Econometrics, Geography, Planning and Development}},
  publisher    = {{Elsevier BV}},
  title        = {{{A private sustainable partner selection model for green public-private partnerships and regional economic development}}},
  doi          = {{10.1016/j.seps.2021.101189}},
  volume       = {{83}},
  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{53239,
  author       = {{Tavana, Madjid and Ghasrikhouzani, Mohsen and Abtahi, Amir-Reza}},
  issn         = {{0953-7325}},
  journal      = {{Technology Analysis & Strategic Management}},
  keywords     = {{Management Science and Operations Research, Strategy and Management}},
  number       = {{8}},
  pages        = {{859--875}},
  publisher    = {{Informa UK Limited}},
  title        = {{{A technology development framework for scenario planning and futures studies using causal modeling}}},
  doi          = {{10.1080/09537325.2021.1931672}},
  volume       = {{34}},
  year         = {{2022}},
}