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Conference Agenda

Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).

Only Sessions at Location/Venue

Session Overview

Session

Regular session : Optimization of production and transportation systems

Time:

Monday, 06/Sept/2021:

2:00pm - 4:00pm

Session Chair: Manoj Kumar Tiwari
Session Chair: Farouk Yalaoui

Virtual location: Monday Room 7

Presentations

ID: 159 / RS-16: 1
Regular Paper Submission
Data-driven Production Management: Advanced Modelling, Simulation and Data Analytics in Production & Supply Networks
Cloud and Collaborative Technologies: Collaborative Design and Engineering
Keywords: Layout problem, Hybrid constructive placing strategy, Interactive design

Interactive Design Optimization of Layout Problems

Xiaoxiao Song¹, Emilie Poirson¹, Yannick Ravaut², Fouad Bennis¹

¹Ecole Centrale de Nantes, France; ²Thales Communications, Cholet, France

ID: 203 / RS-16: 2
Regular Paper Submission
Keywords: Flexible Job Shop Scheduling, Fluid Model, Fluid Relaxation, Re-entrant flows, Large scale optimization.

A Fast and Efficient Fluid Relaxation Algorithm for Large-Scale Re-entrant Flexible Job Shop Scheduling

Linshan Ding, Zailin Guan, Zhengmin Zhang

Huazhong University of Science and Technology, Wuhan, China

ID: 277 / RS-16: 3
Regular Paper Submission
Keywords: Assembly System, Configuration, Industry 4.0, Straight-line, U-shaped line.

Straight and U-shaped assembly lines in Industry 4.0 era: factors influencing their implementation

Marco Simonetto, Fabio Sgarbossa

Norwegian University of Science and Technology (NTNU), Norway

ID: 213 / RS-16: 4
Special session: Novel Approaches in Designing, Balancing and Sequencing of Stochastic Assembly, Disassembly and Machining Lines
Keywords: Manufacturing System, Production Line, Machine Learning, Simulation

Identification of superior improvement trajectories for production lines via simulation-based optimization with reinforcement learning

Günther Schuh, Andreas Gützlaff, Matthias Schmidhuber, Jan Maetschke, Max Barkhausen, Narendiran Sivanesan

WZL of RWTH Aachen University, Germany