Program for stream Analytics

WB-14: Forecasting
Stream: Analytics
Room: Wetterhorn
Chair(s): Ralph Grothmann, Sven F. Crone

• Using neural networks to forecast parcel quantities in a distribution network
  Gabor Tamas, Elisabeth Zehendner, Christian Paier, Emel Arikan, Gerald Reiner
• Forecasting Customer Demand with Deep Neural Networks
  Ralph Grothmann, Ulrike Dowie
• Using Internet-of-Things Data at the Point-of-Consumption for Demand Forecasting and Inventory Management: The Case of Professional Coffee Machines
  Sandria Weisshuhn, Yale T. Herer, Kai Hoberg
• Dynamic data collection in production and logistics
  Benedikt Finnah, Jochen Gönsch, Alena Otto

TA-14: Data Mining Techniques
Stream: Analytics
Room: Wetterhorn
Chair(s): Jochen Gönsch, Davina Rauhaus

• The Max-Cut Decision Tree: Improving on the Accuracy and Running Time of Decision Trees and Random Forests
  Jonathan Bodine, Dorit Hochbaum
• A k-means algorithm for clustering with hard and soft must-link and cannot-link constraints
  Philipp Baumann, Dorit Hochbaum
• Sparse Random Forests via Mathematical Optimization
  Kseniia Kurishchenko, Emilio CARRIZOSA, Dolores Romero Morales
• Predicting Personal Spending Targets for Promotional Offers
  Buse MERT, Defne İdil Eskiocak, Işıl Öztürk

TD-14: Prescriptive Analytics and Interpretability
Stream: Analytics
Room: Wetterhorn
Chair(s): Philipp Baumann

• An a-priori Parameter Selection Approach to Enhance the Performance of Genetic Algorithms Solving Pickup and Delivery Problems
  Cornelius Rüther, Shabanaz Chamurally, Julia Rieck
• Mathematical Optimization for Individual and Group Level Counterfactual Explanations
  Jasone Ramírez-Ayerbe, Emilio CARRIZOSA, Dolores Romero Morales
• A new Greedy Heuristic driven by Machine Learning for the symmetric Traveling Salesman Problem
  Umberto Junior Mele, Luca Maria Gambardella, Roberto Montemanni
• Predicting Inventory Inaccuracies to Minimize Record-Keeping Errors
  Defne İdil Eskiocak, Buse MERT, Birol Yüceoglu