welcomes proposals for special sessions within the technical scope of the conference.
Special sessions supplement the regular program of the conference and provide a
sample of the state-of-the-art research in both academia and industry in
special, novel, challenging, and emerging topics.
Special-session proposals should be submitted by the prospective organizer(s)
who will commit to promoting and handling the review process of their special
session as Chairs or Co-Chairs of the event.
Please provide all the information requested above in PDF format by E-mail to email@example.com before October 30, 2023
- Name(s) of organizer(s);
- Email of main contact person;
- Brief bio(s) of organizer(s);
- Brief description;
- Related topics;
- Potential participants;
About the Session:
Machine Learning is a prospective area of investigation for several different aspects of Industrial Engineering. The aim of this section is to provide an overview of the emerging state-of-the-art research in the field. Papers and presentations about innovative research works relying on Machine Learning, both addressing Industrial Engineering problems directly, or supporting traditional approaches, are welcome.
- Artificial Intelligence
- Combinatorial Optimization
- Decision Analysis and Methods
- Decision Support Systems
- Deep Learning
- Information Processing and Engineering
- Intelligent Manufacturing Systems
- Logistics and Supply Chain Management
- Machine Learning
- Mathematical Programming
- Neural Networks
- Operations Research Applications
- Production Planning and Control
- Quality Control and Management
- Reliability and Maintenance Engineering
- Safety, Security and Risk Management
- Scheduling Problems
Please choose session 1
Roberto Montemanni is full professor of operations research at the University of Modena and Reggio Emilia, Italy. He also acts as an external research advisor at the Dalle Molle Institute for Artificial Intelligence, University of Lugano, Switzerland. He obtained a Laurea degree in Computer Science from the University of Bologna, Italy and a Ph.D. in Applied Mathematics from the University of Glamorgan, UK. He has been administrating grants and leading basic and applied research projects both at national (Italy and Switzerland) and international levels. His main research interests are in the fields of mathematical modeling, algorithms and machine learning, with applications mainly in transportations, logistics and industrial engineering.
About the Session:
In the last years, Multi-Robot Systems (MRS) have experienced considerable recognition due to various real-world applications. In particular, Multi-Robot Task Allocation (MRTA) is among the most interesting MRS problems. This problem concerns the situation when a set of given tasks must be performed by a team of mobile robots that collaborate with the intention of optimizing an objective function.
The first objective of this special session is to gather novel approaches devoted to MRS problems and applications. In particular, new contributions for the development of modeling and analysis methods, of verification algorithms and of specific control structures design are encouraged including theoretical and application papers. A non-exhaustive list of some potential topics is provided below:
- Modeling aspect, MILP formulations
- Optimization models and algorithms
- Dynamic routing and scheduling
- Formal methods
- Coordination and collaboration methods
- Artificial intelligence approaches
- Timed and energy constrained MRS problems
- Uncertain and dynamic environments exploration
- Collision and obstacle avoidance
- Applications for manufacturing systems, transportation systems, and so one.
Please choose session 2
Rabah Ammour received the M.Sc. degree in complex systems engineering
from the Ecole Normale Supérieure de Cachan, France, in 2013 and the Ph.D.
degree in Automatic Control from Université Le Havre Normandie, France, in 2017.
Since 2018, he is an Associate Professor at Aix-Marseille Université, Marseille,
France. He is with the Laboratoire d’Informatique et Systèmes (LIS). His
research interests include the modelling, analysis and control of discrete event
systems using Petri nets. (E-mail:
Saïd Amari received the Ph.D. degree from the Institute of Research in Communications and Cybernetic of Nantes, France, in 2005. He is currently an Associate Professor (HdR) at the University of Sorbonne Paris Nord. He carries out research at the Automated Production Research Laboratory from the École Normale Supérieure Paris-Saclay. His main research interests are performance evaluation of networked automation systems, modelling and control of discrete event systems using Petri nets, dioid algebra and timed automata with guards. (E-mail: firstname.lastname@example.org)
Dimitri Lefebvre (M'11, SM'19) received the S.B. in Science and Engineering in 1990, the M.Eng. degree in Automatic Control and Computer Science in 1992, and the Ph.D. degree Automatic Control and Computer Science in 1994, all from University of Sciences and Technologies and Ecole Centrale in Lille, France. In 1995, he joined the University of Franche Comté, Belfort, France, where he served as Associate Professor with the Department of Electrical Engineering and the Research Group about Systems and Transportations. Since 2001, he has been with Université Le Havre Normandie (ULHN), France as Full Professor. He is currently with the Research Group on Electrical Engineering and Automatic Control (GREAH) in Le Havre and was from 2007 to 2012 the head of the group. His current research interests include fault diagnosis and control design for dynamic systems, discrete event systems, learning processes and artificial intelligence, with applications to network security and safety in the domains of electrical engineering, robotics, transportations and logistics. He is the author of more than 140 articles published in indexed journals and more than 250 communications in international conferences. (E-mail: email@example.com)