Former Employees

From 2017 until 2019, Dr. Adriana Moros Daza was our external PhD student within the Dual Degree Program with Universidad del Norte in Barranquilla, Colombia and now is a lecturer at that same university.

Research Interests:

optimization of port logistics, supply chain management, optimization, simulation and collaboration in foreign trade chains

Background:

Dr. Moros is currently linked to the department of industrial engineering of the Universidad del Norte. She holds an industrial engineering degree and a master's degree in industrial engineering, both awarded by the Universidad del Norte. Ms. Moros has participated in joint projects with the university for the Colombian Caribbean region, as is the case with the LOGPORT project.

From 2017 until 2019 Prof. Dr. Eduardo Lalla-Ruiz was a Alexander-von-Humboldt fellow at the IWI and now is assistant professor at the University of Twente, the Netherlands.

Lectures:

• Informationsmanagement im Verkehr (in English)

Awards:

• extraordinary doctoral award for the best Phd thesis in 2016 by the University of La Laguna (Teneriffe)

Prof. Dr. Lalla-Ruiz was a Von-Humboldt-fellowship-funded Post-Doc researcher at our institute from 2017 until 2018. He is currently Assistant Professor at the University of Twente.

Currently, Yingjie Fan is an Assistant Professor at the University of Leiden, Netherlands. From 2012 until June 2017 she was an external phd student at the IWI.

Research Interests:

Supply Chain Management, Supply Chain Risk Management, Metaheuristics, Simulation-Based Optimization, Multi-Agent-Systems, Production Management, Warehouse Management, Logistics

Publications:

Yingjie Fan, Frank Schwartz, Stefan Voß. Flexible supply chain design under stochastic catastrophic risks. The 9th Hamburg International Conference of Logistics 2014 (HICL), 2014.

Yingjie Fan, Jiangtao Mo. Study on backorder allowed single-manufacturer multi-retailer coordination strategy. Logistics Technology, 2010 (20) 79-82. (in Chinese)

Yingjie Fan. Study on the joint decision-making within a multi-echelon supply chain with invariant demand. Logistics Technology, 2010 (16) 124-126. (in Chinese)

Zengxin Wei, Yingjie Fan, Jiangtao Mo. Research on the decision-making problem of the producer and the retailer on the supply chain. Microcomputer Information, 2008 (15) 24-25. (in Chinese)

Awards and Honours:

scholarship from China Scholarship Council (CSC) for the doctoral degree studies from Oct. 2012 to Sep. 2016.

CV:

From 2007 until 2017 Dr. Silvia Schwarze was a post-Doc and research associate at the IWI.

Research Interests:

• Operative processes at container terminals
• Impact of digital transformation on processes at seaports
• Freight transport planning, tour planning, in particular under vehicle skills
• Planning in public transport, lineplanning
• Network design in telecommunication networks, in particular for fiber networks and content delivery networks
• Metaheuristics
• Game Theory
• Multiagent systems and supply chain management

Publications:

Journal Articles:

S. Schwarze: Pricing Strategies for the Site-Dependent Vehicle Routing Problem. OR Spectrum 38(1), pp. 137-173, 2016.

D. Meignan, S. Schwarze, S. Voß: Improving Local-search Metaheuristics through Look-ahead Policies. Annals of Mathematics and Artificial Intelligence 76, pp. 59-82. 2016.

E. Zehendner, M. Caserta, D. Feillet, S. Schwarze, S. Voß: An Improved Mathematical Formulation for the Blocks Relocation Problem. European Journal of Operational Research 245, pp. 415-422, 2015.

S. Schwarze, S. Voß: Interaction of Maritime Shipping and Hinterland Traffic Using a Two-level
Hierarchical Transport Network. International Journal of Logistics Research and Applications 18(3), pp. 276-290, 2015

A. Schöbel, S. Schwarze: Finding Delay-Resistant Line Concepts using a Game-Theoretic Approach. Netnomics, 14(3), pp. 95-117, 2013

S. Schwarze, S. Voß: Improved Load Balancing and Resource Utilization for the Skill Vehicle Routing Problem. Optimization Letters, 7(8), pp. 1805-1823, 2013

M. Fricke, A. Heckwolf, R. Herber, R. Nitsch, S. Schwarze, S. Voß, S. Wevering: Requirements of 4G-Based Mobile Broadband on Future Transport Networks [PDF]. Journal of Telecommunications and Information Technology, 2/2012, pp. 21 - 28. 2012

M. Caserta, S. Schwarze, S. Voß: Developing a Ring-Based Optical Network Structure with Glass-Through Nodes. Journal of Telecommunications and Information Technology [PDF], 2/2012, pp. 13 - 20. 2012

M. Caserta, S. Schwarze, S. Voß: A mathematical formulation and complexity considerations for the blocks relocation problem. European Journal of Operational Research, 219(1), pp. 96-104, 2012

S. Voß, S. Schwarze: LTE und LTE-A: Mobilfunk der vierten Generation, WISU, Das Wirtschaftsstudium, 5/12, pp. 689 - 692, 2012

S. Schwarze, M. Caserta, S. Voß: Die Kunst des Stapelns – Eine Einführung in das Blocksortierproblem, WiSt, Wirtschaftswissenschaftliches Studium, Vol. 39 (12), pp. 576 - 581, 2010.

I. Montalvo, J. Izquierdo, S. Schwarze, R. Pérez-García: Multi-objective particle swarm optimization applied to water distribution systems design: An approach with human interaction, Mathematical and Computer Modelling 52 pp. 1219-1227, 2010

J. Puerto, A. Schöbel, S. Schwarze: The path player game: A network game from the point of view of the network providers, Mathematical Methods of Operations Research, 68(1), pp. 1-20, 2008

Book Chapters and Conference Proceeding Contributions:

L. Heilig, S. Schwarze, S. Voß: An Analysis of Digital Transformation in the History and Future of Modern Ports. In: Proceedings of the 50th Hawaii International Conference on System Sciences (HICCS'2017) pp 1341-1350 (2017)

E. Lalla-Ruiz, S. Schwarze, S. Voß: A Matheuristic Approach for the p-Cable Trench Problem. In: Festa P., Sellmann M., Vanschoren J. (eds) Learning and Intelligent Optimization. LION 2016. Lecture Notes in Computer Science, vol 10079. Springer, pp 247-252 (2016)

S. Schwarze: The multi-commodity cable trench problem. Twenty-Third European Conference on Information Systems (ECIS 2015) Completed Research Papers. Paper 165. (2015)

S. Schwarze, S. Voß: A bicriteria skill vehicle routing problem with time windows and an application to pushback operations at airports. In: J. Dethloff, H.-D. Haasis, H. Kopfer, H. Kotzab, J. Schönberger (eds.) Logistics Management, Lecture Notes in Logistics, Springer, pp. 289-300 (2015)

D. Meignan, S. Schwarze, S. Voß: Two look-ahead strategies for local-search metaheuristics. In: P.M. Pardalos, M.G.C. Resende, C. Vogiatzis, J.L. Walteros (eds.) Learning and Intelligent Optimization, LNCS 8426, Springer, pp.187-202 (2014)

S. Schwarze, S. Voß: Look Ahead Hyper Heuristics, In: A. Fink, M.J. Geiger (eds): Proceedings of the 14th EU/ME Workshop, pages 91-97. (2013)

S. Schwarze, S. Voß, G. Zhou, G. Zhou: Scientometric Analysis of Container Terminals and Ports Literature and Interaction with Publications on Distribution Networks, In: H. Hu, X. Shi, R. Stahlbock,

S. Voß (eds): Computational Logistics, volume 7555 of Lecture Notes in Computer Science, pages 33-52. Springer, Berlin (2012).

I. Montalvo, J. Izquierdo, S. Schwarze, R. Pérez-García: Agent swarm optimization, a novel approach in swarm intelligence, In: S. Mambretti, C.A. Brebbia (eds): Urban Water, WIT Transactions on The Buildt Environment, Vol. 122, pp. 35-47, WIT Press (2012)

S. Schwarze: Einführung in die Spieltheorie, In: A. Schöbel, D. Scholz (eds): Evolution und Epidemie.
Spieltheorie in der Biophysik, pp. 3-16, Shaker (2011)

M. Caserta, S. Schwarze, S. Voß: Container Rehandling at Maritime Container Terminals, In: J.W. Böse (ed): Handbook of Terminal Planning, Operations Research/Computer Science Interfaces Series, Vol. 49, pp. 247-269, Springer (2011)

I. Montalvo, J. Izquierdo, S. Schwarze, R. Pérez-García: Agent Swarm Optimization: a paradigm to tackle complex problems. Application to Water Distribution System Design, In: D.A. Swayne, W. Yang, A.A. Voinov, A. Rizzoli, T. Filatova (Eds.) Proc. of the iEMSs 2010

M. Caserta, S. Schwarze, S. Voß: A New Binary Description of the Blocks Relocation Problem and Benefits in a Look Ahead Heuristic, In: Cotta, C. and Cowling P., editors, Evolutionary Computation in Combinatorial Optimization, volume 5482 of Lecture Notes in Computer Science, pages 37-48. Springer, Berlin (2009)

M. Caserta, A. Fink, A. Raiconi, S. Schwarze, S. Voss: Mathematical Formulations and Metaheuristics Comparison for the Push-Tree Problem. In: J.W. Chinneck, B. Kristjansson and M. Saltzman (eds.) Operations Research and Cyber-infrastructure, Springer, New York (2009), 253 - 278

A. Schöbel, S. Schwarze: Dominance and equilibria in the path player game, In: Operations Research
Proceedings 2005, pages 489 - 494, Springer 2006

J. Puerto, A. Schöbel, S. Schwarze: A class of infinite potential games, Preprint des Instituts für Numerische und Angewandte Mathematik, Nr. 2006-15

A. Schöbel, S. Schwarze: A game-theoretic approach to line planning, In: Proc. of ATMOS 2006 - 6th Workshop on Algorithmic Methods and Models for Optimization of Railways, 2006

Books:

S. Voß, J. Pahl, S. Schwarze (eds.): Logistik Management: Systeme, Methoden, Integration, Physica Verlag, Heidelberg (2009)

S. Schwarze: Path Player Games: Analysis and Applications, Springer, 2008

W. Hamacher, E. Korn, R. Korn, S. Schwarze: Mathe und Ökonomie, Universum Verlag, 2004

Research Projects:

Awards and Honours:

CV:

Teaching at UHH:

Lectures:

• Datenerhebung & Statistik (SuTerm16)
• Project Management (WiTerm13/14)
• Production for Engineers (WiTerm13/14)
• Production for Engineers (SuTerm13)
• Advanced Production Planning (WiTerm 9/10)
• Production (SuTerm09)
• Multiagent Systems (WiTerm 08/09)
• Game Theory (WiTerm 06/07)
• Multi-Criteria Optimization (SuTerm06)

Seminars and Tutorials:

• tutorial: Introduction to Information Systems (WiTerm12/13)
• introductory seminar: Telecommunications (WiTerm12/13)
• tutorial: Production (SuTerm12)
• tutorial: Introduction to Information Systems (WiTerm11/12)
• introductory seminar: Optimization Problems in Telecommunications (WiTerm11/12)
• seminar: Production (WiTerm09/10)
• tutorial: Production Planning (SuTerm08) mit Prof. Voß
• Oberseminar Optimization (SuTerm06 - WiTerm 06/07) with Prof. A. Schöbel
• seminar: Location Planning (WiTerm 05/06) with Prof. A. Schöbel
• seminar: Weight Distribution in Networks (SuTerm05) mit Prof. A. Schöbel
• introductory seminar: Game Theory (SuTerm04) with Prof. H.W. Hamacher
• tutorial:Optimization II: Nonlinear Optimization and Game Theory (SuTerm03)
• introductory seminar: Mathematical Modelling (WiTerm 02/03) with Dr. Bracke

Teacher Training:

• Management Mathematics for European School Teacher Meeting (Sept. 2004, Lambrecht)
• Anwendungen der Wirtschaftsmathematik und deren Einsatz im Schulunterricht (June 2004, Speyer)
• Produktionsplanung und lineare Optimierung (Nov. 2003, Düsseldorf)
• Lineare Optimierung in Wirtschaft und Schule (Oct. 2002, Kaiserslautern)

Prof. Dr. Julia Pahl is working as an Associate Professor at University of Southern Denmark at the Department of Technology and Innovation at SDU Engineering Operations Management. From 2008 until 2013 she was employed as a research assistant at the IWI.                                                                                                                           

Research Interests:

Supply Chain Management, Lead Time Management, Load Dependent Lead Times, Tactical Production Planning, Modelling of Deterioration/Perishability, Network Planning, Green Supply Chain Management (GSCM), Airline and Airport Management.

Publications:

Cumulative Dissertation

J. Pahl. Production Planning with Load Dependent Lead Times and Sustainability Aspects (EDISS). Universität Hamburg. (Link)

Peer-Reviewed Jounals
   
J. Pahl, S. Voß, and D.L. Woodruff. Production planning with load dependent lead times. 4OR: A Quarterly Journal of Operations Research, 3(4):257–302, 2005 (Link: Springerlink)     

J. Pahl, S. Voß, and D.L. Woodruff. Production planning with load dependent lead times: An update of research. Annals of Operations Research, 153(1):297-345, 2007 (Link: Springerlink)     
   
    
Double-Blind-Peer-Reviewed Proceedings
   
A. Mies, J. Pahl, S. Voß. Supply Chain Integration: Improvements of Global Lead Times with SCEM in: J. Geldermann, M. Treitz, H. Schollenberger, O. Rentz (Eds.) Challenges for Industrial Production, Workshop of the PepOn Project: Integrated Process Design for Inter-Enterprise Plant Layout Planning of Dynamic Mass Flow Networks, Karlsruhe, Nov. 7-8. 2005 (Link: Book Overview)
 
J. Pahl, S. Voß, D.L. Woodruff. Production Planning with deterioration constraints: A survey. In: J.A. Ceroni (ed.) The Development of Collaborative Production and Service Systems in Emergent Economies, Proceedings of the 19th International Conference on Production Research, IFPR , Valparaiso, Chile (2007), Tu3. 6-2, 6 pages [ISBN: 978-956-310-751-7] (Link: ICPR19)
 
J. Pahl, S. Voß. Discrete Lot-Sizing and Scheduling Including Deterioration and Perishability Constraints. In: W. Danglmainer and A. Blecken and R. Delius and S. Klöpfer (ed.) Advanced Manufacturing and Sustainable Logistics, Proceedings of the 8th International Heinz Nixdorf Symposium, IHNS 2010, Paderborn 2010 (Link: Springerlink)

J. Pahl, S. Voß, D.L. Woodruff. Discrete Lot-Sizing and Scheduling with Sequence-Dependent Setup Times and Costs including Deterioration and Perishability Constraints, IEEE, HICSS-44, January 2011.
(Testinstanzen und Performance [19MB!])
    
T. Reiners, J. Pahl, M. Maroszek, C. Rettig. Integrated Aircraft Scheduling Problem: An Auto-Adapting Algorithm to Find Robust Aircraft Assignments for Large Flight Plans, IEEE, HICSS-45, January 2012, (Quellcode, Testinstanzen, Visual Suite Software [27MB])
 
    
Book Chapters
 
J. Pahl, S. Voß, and D.L. Woodruff. Load dependent lead times - from empirical evidence to mathematical modeling. In H. Kotzab, S. Seuring, M. Müller, and G. Reiner, editors, Research Methodologies in Supply Chain Management, 539–554. Physica, Heidelberg, 2005 (Link: Springerlink)

   
Technical Reports und Working Papers
   
M. Maroszek, C. Rettig. A Tabu Search for the p-Median Problem, Technical Report, Universität Hamburg, 27.03.2008 (Download technical report (PDF))

Other Activities

Member of the international editorial team of the International Journal of Operations Research and Information Systems (IJORIS).

International Research Projects with the University of Salerno, Italy

DAAD-PPP Vigoni Research Project "Sustainability and Green Supply Chain Planning - Network Flow Formulations and Solution Methods" in Cooperation with Universitá degli Studi di Salerno, Dipartimento di Informatica, Assistant Professor Monica Gentili, Fisciano/Italy

Awards and Distinctions

Young Graduate Traineeship der European Space Agency, VEGA Small Launcher Project

Research Grant for HICSS-44

Lectures and Courses

Study (Software) Project ( WiTerm 2008/09, SuTerm 2009, SuTerm 2010)                       
Assistence Lecture Information Management (WiTerm 2008/09)                    
Seminar of Information Systems / Information Systems (WiTerm 2008/09, WiTerm 2009/10)
Assistence Lecture Production (Produktion: SuTerm 2009)              
Exercise in Information Management (WiTerm 2008/09)                       
Exercises in Production Planning (SuTerm 2009)                               
Exercises in Statistics II (SuTerm 2009)

Google Scholar Profil

From 2001 until 2014 Prof. Dr. Stefan Lessmann was  a research assistant and lecturer at the IWI. Since 2014 he is a professor at the Humboldt University in Berlin.

Research Interests

I’m particularly interested in applications of computational methods to support managerial decision making, as well as modification and extension of such methods to increase their alignment with corporate requirements. Such endeavors are nowadays commonly referred to as data mining. Candidate applications include, e.g., estimating customers' likelihood of responding to direct-mail (response modeling), identifying customers at the risk of abandoning their relationship with a company (churn prediction), fraud detection, or assessing the risk associated with money lending (credit scoring).
Demand forecasting is another important application of quantitative decision support models and prediction models in particular. Any practical planning approach in, e.g., manufacturing or the wider scope of supply chain management is preconditioned on an accurate estimation of future demand. Therefore, it is an exciting exercise to explore the viability of demand forecasting for particular applications from computational, statistical and process-oriented perspectives, and study interactions between forecasting methodology and subsequent planning.
Predictive data mining methods can also be employed to aid software project management by identifying error prone software modules at an early stage within the development cycle. This may facilitate a more efficient allocation of constraint testing resources.
Finally, I developed a strong interest in studying the mechanisms of, and decision makers’ behavior in, speculative financial markets. Respective work aims at assessing the degree to which publicly available information is discounted in market prices. To foster a deeper understanding of this domain, a research collaboration with Prof. J.E.V. Johnson from the Centre of Risk Research, University of Southampton has been established. A popular approach to shed light on markets’ informational efficiency involves predictive modeling, which can thus be seen as the central theme embracing and unifying most of my research activities.
From a methodological perspective, I’m especially interested in support vector machines and ensemble approaches to solve general classification and regression problems. Furthermore, novel learning paradigms like active, transductive or strategic learning are an area I’m particularly excited about.

Publications (overview @ Google Scholar)

Monographs and editorial work

R. Stahlbock, S.F. Crone, S. Lessmann, (2009), Data Mining - Special Issue in Annals of Information Systems, Springer, Berlin. [ext. Link]

R. Stahlbock, S.F. Crone, S. Lessmann, G. M. Weiss, P. Lenca and W. Lippe (2009), Proceedings of the International Conference on Data Mining - DMIN'09, CSREA Press, Las Vegas.

R. Stahlbock, S.F. Crone, S. Lessmann, (2008), Proceedings of the International Conference on Data Mining - DMIN'08, CSREA Press, Las Vegas.

R. Stahlbock, S.F. Crone, S. Lessmann, (2007), Proceedings of the International Conference on Data Mining - DMIN'07, CSREA Press, Las Vegas. - ISBN 1-60132-004-3

S.F. Crone, S. Lessmann, R. Stahlbock (2006), Proceedings of the International Conference on Data Mining - DMIN'06, CSREA Press, Las Vegas. - ISBN 1-60132-031-0

Peer reviewed international journals

Brandner, H., Lessmann, S., & Voß, S. (2013). A memetic approach to construct transductive discrete support vector machines. European Journal of Operational Research, 230(3), pp. 581-595. [ext. link]

M.-C. Sung, S. Lessmann (2012), Save the Best for Last? The Treatment of Dominant Predictors in Financial Forecasting. Expert Systems With Applications 39(15), pp. 11898-11910 [ext. link]

S. Lessmann, M.-C. Sung, J.E.V. Johnson, T. Ma (2012), A new methodology for generating and combining statistical forecasting models to enhance competitive event prediction. European Journal of Operational Research 218(1), pp.163-174. [ext. link]

S. Lessmann, M. Caserta, I. Montalvo Arango (2011). Tuning metaheuristics: A data mining based approach for particle swarm optimization, Expert Systems With Applications 38(10), pp. 12826-12838. [ext. link]

S. Lessmann, M.-C. Sung, J.E.V. Johnson (2011), Towards a methodology for measuring the true degree of efficiency in a speculative market, Journal of the Operational Research Society 62, pp.2120-2132. [ext. link]      

S. Lessmann, S. Voß (2010), Customer-centric decision support: A benchmarking study of novel versus established classification models, Business & Information Systems Engineering 2(2), pp. 79-93 [German version appears in Wirtschaftsinformatik]. [ext. link]

S. Lessmann, M.-C. Sung, J.E.V. Johnson (2010), Alternative methods of predicting competitive events: An application in horserace betting markets. International Journal of Forecasting 26(3), pp. 518-536. [ext. link]

R. Stahlbock, S. F. Crone, S. Lessmann (2009), Data Mining and Information Systems: Quo Vadis?, Annals of Information Systems 8, pp. 1-15. [ext. link]

S. Lessmann, S. Voß (2009), A framework for customer-centric data mining with support vector machines, European Journal of Operational Research 199(2), pp. 520-530. [ext. link]

S. Lessmann, M.-C. Sung, J.E.V. Johnson (2009), Identifying winners of competitive events: A SVM-based classification model for horserace prediction, European Journal of Operational Research 196(2), pp. 569-577. [ext. link]

S. Lessmann, B. Baesens, C. Mues, S. Pietsch (2008),  Benchmarking classification models for software defect prediction: A proposed framework and novel findings, IEEE Transactions on Software Engineering 34(4), pp. 485-496. [ext. link]

S. Lessmann, M.-C. Sung, J.E.V. Johnson (2007), Adapting least-square support vector regression models to forecast the outcome of horseraces, Journal of Prediction Markets 1(3), pp. 169-187.

S. F. Crone, S. Lessmann, R. Stahlbock (2006), The impact of preprocessing on data mining: An evaluation of classifier sensitivity in direct marketing, European Journal of Operational Research 173(3), pp. 781-800. [ext. link]

Peer reviewed national journals

S. Lessmann, S. Voß (2010), Unterstützung kundenbezogener Entscheidungsprobleme: Eine Analyse zum Potenzial moderner Klassifikationsverfahren, Wirtschaftsinformatik 52(2), pp. 79-93. [ext. link]

S. Lessmann, S. Schüller, S. Voß (2009), Kostensensitive Klassifikation mit Random Forest, HMD - Praxis der Wirtschaftsinformatik 268, pp. 57-68.

S. Lessmann (2003), Customer Relationship Management, WISU 2, pp. 190-192.

Peer reviewed conference proceedings

H. Brandner, S. Lessmann, S. Voß (2011). Support of Managerial Decision Making by Transductive Learning. Proc. of the 10th Intern. Conf on Wirtschaftsinformatik (WI'11), Zurich, Switzerland.

S. Lessmann, M. Listiani and S. Voß (2010). Decision support in car leasing: A forecasting model for residual value estimation. In: M. Lacity, F. Niederman, S. March (Eds.) Proc. of the Intern. Conf. on Information Systems (ICIS’10), Saint Louis, MO, USA. [ext. link]
      
S. Lessmann, S. Voß (2009), Feature Selection in Marketing Applications. Proc. of the Intern. Conf on Advanced Data Mining and Applications (ADMA'09), Beijing, China. [ext. link]
           S. Schüller, S. Lessmann, S. Voß (2009), A Case Study of Random Forest in Predictive Data Mining. Proc. of the Intern. Tagung Wirtschaftsinformatik (WI'09), Vienna, Austria.
      
M. Caserta, S. Lessmann, S. Voß (2009), A Novel Approach to Construct Discrete Support Vector Machine Classifiers. Proc. of the Anual Conf. of the German Classification Society (GFKL'09), Hamburg, Germany

N. Martin, S. Lessmann, S. Voß (2008), Crowdsourcing: Systematisierung praktischer Ausprägungen und verwandter Konzepte, Proc. of the 2008 Multi-Konferenz Wirtschaftsinformatik (MKWI'08), München, Germany [in German]

S. Lessmann, N. Li, S. Voß (2008), A Case Study of Core Vector Machines in Corporate Data Mining, Proc. of the 41th Hawaiian Intern. Conf. on System Science (HICSS'08), Hawaii, USA.

S. Lessmann, S. Voß (2006), Solving discrete support vector machines with tabu search, Proc. of the 2006 INFORMS Workshop on Artificial Intelligence and Data Mining, Pittsburgh, USA.

S. F. Crone, S. Lessmann, S. Pietsch (2006), Business Advantages with Computational Intelligence –An Investigation of Parameter Preselection for Support Vector Regression and Artificial Neural Networks applied on Time Series Forecasting, Proc. of the Intern. Conf. on Data Mining (DMIN'06), Las Vegas, Nevada, USA.

S. Lessmann, S. F. Crone, R. Stahlbock, N. Zacher (2006), An evaluation of support vector machines for cost-sensitive learning, Proc. of the Intern. Joint Conf. on Neural Networks (IJCNN'06), Vancouver, Canada.

S. Lessmann, R. Stahlbock, S. F. Crone (2006), Genetic algorithms for support vector machine model selection, Proc. of the Intern. Joint Conf. on Neural Networks (IJCNN'06), Vancouver, Canada.

S. F. Crone, S. Lessmann, S. Pietsch (2006), Forecasting with Computational Intelligence - An evaluation of support vector regression and artificial neural networks for time series prediction, Proc. of the Intern. Joint Conf. on Neural Networks (IJCNN'06), Vancouver, Canada.

S. F. Crone, S. Lessmann, R. Stahlbock (2005), Utility Based Data Mining for Time Series Analysis - Cost sensitive learning for Neural Network Predictors,  Proc. of the 1st ACM SIGKDD Workshop on Utility based Data Mining (UBDM@KDD'05), Chicago, Illinois, USA.

S. Lessmann, R. Stahlbock, S. F. Crone (2005), Genetically constructed kernels for support vector machines. In Haasis, H.D., Kopfer, H., Schönberger, J. (Eds.):  Operations Research Proceedings  2005, Springer, Berlin, pp. 257-262.

R. Stahlbock, S. F. Crone, S. Lessmann (2005) Evolutionary Neural Classification Approaches for Strategic and Operational Decision Support in Retail Store Planning, Proc. of the Intern. Conf. on Artificial Intelligence (IC-AI’05), Las Vegas, Nevada, USA.

S. Lessmann, R. Stahlbock, S. F. Crone (2005), Optimizing Hyperparameters of Support Vector Machines by Genetic Algorithms, Proc. of the Intern. Conf. on Artificial Intelligence (IC-AI’05), Las Vegas, Nevada, USA.

S. F. Crone, S. Lessmann, R. Stahlbock (2005) A New Perspective on Forecasting Seasonal Time Series with Artificial Neural Networks, Proc. of the Intern. Conf. on Artificial Intelligence (IC-AI’05), Las Vegas, Nevada, USA.

S. F. Crone, S. Lessmann, R. Stahlbock (2004), Empirical Comparison and Evaluation of classifier Performance for data mining in Customer Relationship Management. In: D.Wunsch et al. (eds.): Proc. of the  Int. Joint Conf. on Neural Networks (IJCNN’04), 25.-29. July, Budapest, Hungary, IEEE, New York, pp. 443-448 [ext. link]

S. Lessmann (2004), Solving imbalanced classification Problems with Support Vector Machines, Proc. of the Intern. Conf. on Artificial Intelligence (IC-AI’04), Las Vegas, Nevada, USA.

Chapters in books
         

S. Lessmann, S. Voß (2008), Supervised Classification for Decision Support in Customer Relationship Management. In: Bortfeldt, A., Homberger, J., Kopfer, H., Pankratz, G., Stangmeier, R. (Eds): Intelligent Decision Support, Gabler, Wiesbaden, pp. 231-253.

D. B. Preßmar, S. Lessmann (2008), Wissensexploration mit der Support Vektor Maschine. In: Kortzfleisch, H. F. O., Bohl, O.  (Eds): Wissens Vernetzung Virtualisierung. Josef Eul Verlag, Köln, pp. 187-197.

S. Lessmann, R. Stahlbock (2005), Support Vektor Klassifikatoren im analytischen Kundenbeziehungsmanagement. In: Rommelfanger, H. (Ed.): Neue Anwendungen von Fuzzy-Logik und Künstlicher Intelligenz. Shaker Verlag, Aachen, pp. 113-124.

S. F. Crone, S. Lessmann, R. Stahlbock (2005), Support Vector Machines versus Artificial Neural Networks - new potential in Data Mining for Customer Relationship Management?  In: Wang, D., Lee, K. (Eds.): Neural Networks Applications in Information Technology and Web Engineering. Borneo Publishing, Malaysia, pp. 80-93.

Others

J.E.V. Johnson, S. Lessmann, M.-C. Sung, (2007) A new Method for Predicting the Outcome of Speculative Events, Centre for Risk Research Working Paper CRR-07-03, University of Southampton.

S. Lessmann, S. Voß: Electronic Procurement (2005). In: Häberle, G. (Ed.): Lexikon der Betriebswirtschaftslehre, to appear - accepted

R. Stahlbock, S. Lessmann (2003), Potential von Support Vektor Maschinen im analytischen Customer Relationship Management, Working Paper Institute of Information Systems, University of Hamburg. [in German]

Academic Activity

• Program chair of the International Conference on Data Mining, (DMIN'07)
• Elected program chair of the International Conference on Data Mining, (DMIN'06)
• Invited reviewer for the International Joint Conference on Neural Networks, (IJCNN'07)
• Invited reviewer for Netnomics
• Invited reviewer for Neural Processing Letters
• Invited reviewer for the Journal of Data & Knowledge Engineering 
• Invited reviewer for International Transactions in Operations Research
• Invited reviewer for Annals of Operations Research
• Invited reviewer for Informs Journal of Computing

Corporate Research Collaborations

Awards & Distinctions

Background

Teaching at UHH

Undergraduate Teaching

• Object oriented programming with VB.Net
• Introductory course on usage of MS Word, MS Excel and MS Access in business administration

Postgraduate Teaching

• Development of distributed and web-based systems with ASP.Net
• Supervision of working papers and presentations in seminars on information systems
• Design & pre-correction of final diploma-exams (MBA)

Dr. Torsten Reiners held a position as research assistant at the institute from 2003. Currently he is working as senior lecturer at Curtin Business School (CBS) at Curtin University in Perth, Australia.

Dr. Marco Caserta held a position as research assistant at the Institute from 2007 until 2009. Currently, he is working as an adjunct Professor of Operations and Technologies at the IE Business School, and at the IE University in Madrid.

Dipl. Kfm. Ronald Krick held a position as research assistant at the institute from 2003 until 2007. Currently he is working as a freelancing Senior Consultant.

Dr. Sebastian Friedrich held a position as research assistant at the institute from 1999 until 2002. Currently he is working in a leading position at the department of mathematical optimization at Initions AG.

Prof. Dr. Andreas Fink held a position as research assistant at the institute from 2002 until 2005. Currently, he is professor at the Institute of Computer Science at the University of Federal Armed Forces (HSU) in Hamburg.

Prof. Dr. Dr. h. c. Dieter B. Preßmar was the founder and former chair of  the Institute of Information Systems.

From 2012 until 2017 Assoc. Prof. Dr. Frederik Schulte was a research assistant at the IWI. He has received and answered a call to the Technical University of Delft.

Lectures and Courses:

• Information Management (lecture and tutorials in summer term 2013)
• Seminar on Information Systems

Dr. Malek Sarhani was a guest researcher and Alexander-von-Humboldt fellow at our institute from 2019 until 2022 and is currently assistant professor at Al Akhawayn University in Rabat, Morocco.

Research Interests:

• Computational Intelligence
• Machine Learning
• Metaheuristics
• Time series prediction
• Logistics

Publications:

Book Chapters:

1. Sarhani, Malek, Abdellatif El Afia, and Rdouan Faizi. "Facing the feature selection problem with a binary PSO-GSA approach".
   Recent Developments in Metaheuristics. Springer, Cham, 2018. 447-462. DOI: 10.1007/978-3-319-58253-5_26
2. Aoun, Oussama, Malek Sarhani, and Abdellatif El Afia. "Hidden markov model classifier for the adaptive particle swarm
   optimization". Recent Developments in Metaheuristics. Springer, Cham, 2018. 1-15. DOI: 10.1007/978-3-319-58253-5_1
3. Sarhani, Malek, and Abdellatif El Afia. "Forecasting Demand with Support Vector Regression Technique Combined with X13-ARIMA-SEATS Method in the Presence of Calendar Effect". Artificial Intelligence: Concepts, Methodologies, Tools, and Applications. IGI Global, 2017. 2146-2159. DOI: 10.4018/978-1-5225-1759-7.ch089
4. Sarhani, Malek, and Abdellatif El Afia. "Forecasting Demand with Support Vector Regression Technique Incorporating Feature Selection in the Presence of Calendar Effect". Contemporary Approaches and Strategies for Applied Logistics. IGI Global, 2018.
   Chapter 12. DOI: 10.4018/978-1-5225-5273-4.ch012
5. El Afia, Abdellatif, and Malek Sarhani. "Optimization of a Predictive Aircraft Maintenance Routing Model Using Mutated Constrained Particle Swarm Optimization". Contemporary Approaches and Strategies for Applied Logistics. IGI Global, 2018.
   Chapter 15. DOI: 10.4018/978-1-5225-5273-4.ch015
6. El Afia, Abdellatif, and Malek Sarhani. "Runtime prediction of optimizers using improved support vector machine". In Cloud Computing and Big Data: Technologies, Applications and Security. Springer, Cham, 2019, 337-350. DOI: 10.1007/978-3-319-97719-5_21
7. El Afia, Abdellatif, Malek Sarhani, and Oussama Aoun. "A Probabilistic Finite State Machine Design of Particle Swarm Optimisation". In Bioinspired Heuristics for Optimization. Springer, Cham, 2019. 185-201. 10.1007/978-3-319-95104-1_12

Journals:

1. Sarhani, Malek, and Abdellatif El Afia. "Simultaneous feature selection and parameter optimisation of support vector machine using adaptive particle swarm gravitational search algorithm". International Journal of Metaheuristics 5.1 (2016): 51-66. DOI: 10.1504/IJMHEUR.2016.079112
2. Sarhani, Malek, Abdellatif El Afia, and Rdouan Faizi. "Hybrid approach-based support vector machine for electric load forecasting incorporating feature selection". International Journal of Big Data Intelligence, 4.3 (2017): 141-148. DOI: 10.1504/IJBDI.2017.085520
3. Aoun, Oussama, Malek Sarhani, and Abdellatif El Afia. "Investigation of hidden markov model for the tuning of metaheuristics in airline scheduling problems". IFAC-PapersOnLine 49.3 (2016): 347-352. DOI: 10.1016/j.ifacol.2016.07.058
4. Aoun, Oussama, Malek Sarhani, and Abdellatif El Afia. "Particle swarm optimisation with population size and acceleration coefficients adaptation using hidden Markov model state classification". International Journal of Metaheuristics 7.1 (2018): 1-29.
   DOI: 10.1504/IJMHEUR.2018.10012905
5. El Afia, Abdellatif, Malek Sarhani, and Oussama Aoun. "Hidden markov model control of inertia weight adaptation for Particle swarm optimization". IFAC-PapersOnLine 50.1 (2017): 9997-10002. DOI: 10.1016/j.ifacol.2017.08.2030
6. Ezzinbi, Omar, Malek Sarhani, Abdellatif El Afia and Youssef Benadada "Preventive Maintenance with Aircraft on Ground Case Consideration, and Airline Crew Scheduling Problem: A Meta-Heuristics Approaches". International Journal of Applied Logistics (IJAL) 5.2 (2014): 62-73. DOI: 10.4018/ijal.2014040105

Conferences:

1. Sarhani, Malek, and Abdellatif El Afia. "Generalization enhancement of support vector regression in electric load forecasting with model selection." International Conference on Learning and Optimization Algorithms (LOPAL). ACM, 2018. DOI: 10.1145/3230905.3230947
2. Sarhani, Malek, and Abdellatif El Afia. "Electric Load Forecasting Using Hybrid Machine Learning Model incorporating Feature selection". Proceedings of the First International Conference on Big Data, Cloud and Applications: Selected Papers. CEUR Workshop Proceedings, 2015. URN: urn:nbn:de:0074-1580-3
3. Sarhani, Malek, and Abdellatif El Afia. "An extension of X13-ARIMA-SEATS to forecast Islamic holidays effect on logistic activities". Second International Conference on Logistics and Operations Management (GOL). IEEE, 2014. DOI: 10.1109/GOL.2014.6887423
4. Sarhani, Malek, and Abdellatif El Afia. "Intelligent system based support vector regression for supply chain demand forecasting". Second World Conference on Complex Systems (WCCS). IEEE, 2014. DOI: 10.1109/ICoCS.2014.7060941
5. Sarhani, Malek, Omar Ezzinbi, Abdellatif El Afia, and Youssef Benadada "Particle swarm optimization with a mutation operator for solving the preventive aircraft maintenance routing problem". Third International Conference on Logistics and Operations Management (GOL). IEEE, 2016. DOI: 10.1109/GOL.2016.7731683 Journal of Applied Logistics (IJAL) 5.2 (2014): 62-73.
6. Sarhani, Malek, and Abdellatif El Afia. "Feature selection and parameter optimization of support vector regression for electric load forecasting". International Conference on Electrical and Information Technologies (ICEIT). IEEE, 2016. DOI: 10.1109/EITech.2016.7519608
7. El Afia, Abdellatif, and Malek Sarhani. "Particle Swarm Optimization for Model Selection of Aircraft Maintenance Predictive Models". Proceedings of the 2nd international Conference on Big Data, Cloud and Applications. ACM, 2017. DOI: 10.1145/3090354.3090355
8. Ezzinbi, Omar, Malek Sarhani, Abdellatif El Afia, and Youssef Benadada "A metaheuristic approach for solving the airline maintenance routing with aircraft on ground problem". Second International Conference on Logistics and Operations Management (GOL). IEEE, 2014. DOI: 10.1109/GOL.2014.6887447
9. Ezzinbi, Omar, Malek Sarhani, Abdellatif El Afia, and Youssef Benadada "Particle swarm optimization algorithm for solving airline crew scheduling problem". Second International Conference on Logistics and Operations Management (GOL). IEEE, 2014. DOI: 10.1109/GOL.2014.6887446
10. El Afia, Abdellatif, and Malek Sarhani. "Performance prediction using support vector machine for the configuration of optimization algorithms". Third International Conference of Cloud Computing Technologies and Applications. IEEE, 2017. DOI: 10.1109/CloudTech.2017.8284699

Background:

Mr. Michael Myschik has been a research associate and lecturer at the IWI until Dec 31,  2018. He is now retired.

Research Interests:

• Apprenticeship in Information Systems – especiially product-based knowledge and skills related to IT(e.g. handling of application systems, especially of SAP products).
• Since 2009 contact person (SAP-A-User) for central coordination between the Hamburg Business School, the UCC Magdeburg and the SAP AG.

Lectures and Courses:

Winter Term 2016/17: Enterprise Resource Planning: Impact of  ABAP Objects in the context of SAP ERP
Summer Term 2017: Design and Implementation of Business Processes in SAP ERP
Winter Term 20117/18: Enterprise Resource Planning: Impact of  ABAP Objects in the context of SAP ERP
Summer Term 2018: Design and Implementation of Business Processes in SAP ERP

Further Activities:

• administration of central network resources of the HBS
• in case of need supporting consultancy of IT projects and procurement of hard- and software.
• In March 2001 Mr. Myschik and a project team from the Institute of Information Systems installed a client-server-system including an integrated training system for the computer science apprenticeship at the economic University of Tashkent Usbekistan (TSEU).

Background:

Teaching:

Studies:

2024 Postdoc in the project TwinSim (IHATEC), third-party funded
2023 Postdoc in the project Cloud-Application for the Optimal Distribution of Onshore Power in Ports, third-party funded
2022 Guest researcher at the Department of Urban Management, Kyoto University
2019-2023 Research associate and PhD student at the IWI, University of Hamburg
2013-2014 Master (M. Sc.) in Information Systems, University of Rostock
2009-2012 Bachelor (B. Sc.) in Information Systems, University of Applied Sciences Stralsund

Work Experience:

• Volkswagen Group China (2012)
• ml&s GmbH (2011)
• adesso AG (2014-2018)

• Michael Palk
• Dr. Stefan Anschütz
• Dr. Sven Crone
• René Eisenberg
• André Henkel
• Holger Höller
• Imke Sassen