IEEE CEC 2019 Special Session on Smart Logistics

Scope and Topics

Smart logistics refers to the efficient and effective design, planning and control of the supply chain processes though intelligent technologies, such as software to improve the design of networks, software to automate scheduling, routing, and dispatching, material handling systems, etc. Respectively, the relevant research methods involve clustering, stochastic (dual) dynamic programming, planning and optimization. In recent years, evolutionary computation (EC) techniques have been introduced to the area of logistics. Examples include applying single-objective and multi-objective evolutionary algorithms to facility layout decision problems and vehicle routing problems.

Scope

This special session aims at presenting the latest research on EC applications to logistics. Real-world applications of EC on logistics are highly recommended. The topics include but are not limited to:

various facility (re-)layout decision problems

various routing problems

emergency logistics

reverse logistics

crowd logistics

freight transportation

green supply chain

metropolitan/city logistics

uncertainty modelling in planning and control

large-scale evolutionary optimization to logistics

multi-agent system in logistics

internet of things on smart logistics.

PC Members

To be updated soon

Important Dates

Submission deadline: 7 January 2019

Notification: 7 March 2019

Final paper submission: 31 March 2019

Submission Guidelines

Special session papers should be uploaded online through the paper submission website of IEEE CEC 2019. Please select the corresponding special session name ("CEC44- Special Session on Smart Logistics") as the "main research topic" in submission. For the latest information on important dates, please refer to this page.

Organizers

Jialin Liu, liujl(at)sustc.edu.cn

Research Assistant Professor, Dept. of Computer Science and Engineering, Southern University of Science and Technology, China

Dr. Jialin Liu received her Ph.D. Degree in Computer Science from the Inria Saclay and the Université Paris-Saclay (France) in December 2015 and her Master Degree in Bioinformatics and Biostatistics from the École Polytechnique and the Université Paris-Sud (France) in 2013. She is a Research Assistant Professor at the Department of Computer Science and Engineering of Southern University of Science and Technology (SUSTech, China). Before joining SUSTech, she was a Postdoctoral Research Associate at Queen Mary University of London (QMUL, UK) and one of the founding members of the Game AI research group created in August 2017. Her research interests include meta-heuristics, noisy optimisation, AI and games. She is the Chair of the IEEE Computational Intelligence Society (CIS) Student Games-Based Competitions Sub-Committee and the Vice-Chair of the IEEE CIS Games Technical Committee. She also serves as Program Co-Chair at IEEE CIG2018, as Competition Chair at FDG2018 and IEEE CEC2019.

Yi Mei, yi.mei@ecs.vuw.ac.nz

Lecturer in Computer Science, School of Engineering and Computer Science, Victoria University of Wellington, New Zealand

Dr. Yi Mei is a Lecturer at the School of Engineering and Computer Science, Victoria University of Wellington, Wellington, New Zealand. He received his BSc and PhD degrees from University of Science and Technology of China in 2005 and 2010, respectively. His research interests include evolutionary computation in scheduling, routing and combinatorial optimisation, as well as evolutionary machine learning, genetic programming, feature selection and dimensional reduction. He has more than 70 fully referred publications, including the top journals in EC and Operations Research (OR) such as IEEE TEVC, IEEE Transactions on Cybernetics, European Journal of Operational Research, ACM Transactions on Mathematical Software. He is an Editorial Board Member of International Journal of Bio-Inspired Computation. He serves as a Vice-Chair of the IEEE CIS Emergent Technologies Technical Committee, and a member of three IEEE CIS Task Forces. He is a guest editor of a special issue of the Genetic Programming Evolvable Machine journal. He serves as a reviewer of over 30 international journals including the top journals in EC and OR.

Shengxiang Yang, syang@dmu.ac.uk

Professor, School of Computer Science and Informatics, De Montfort University, UK

Shengxiang Yang is now a Professor in Computational Intelligence and Director of the Centre for Computational Intelligence, School of Computer Science and Informatics, De Montfort University, UK. He has over 260 publications. His current research interests include evolutionary computation (EC), swarm intelligence, meta-heuristics, artificial neural networks, evolutionary multi-objective optimization, computational intelligence in dynamic and uncertain environments, and relevant real-world applications. He was the Chair of IEEE Computational Intelligence Society (CIS) Task Force on EC in Dynamic and Uncertain Environments (2011-2017), and the Founding Chair of IEEE CIS Task Force on Intelligent Network Systems (2012-2017). He has given over 10 invited keynote speeches/tutorials in international conferences and co-organized over 40 workshops and special sessions in conferences. He was the Founding Co-Chair of the IEEE Symposium on Computational Intelligence in Dynamic and Uncertain Environments. He serves an Associate Editor or an Editorial Board Member for seven international journals. He has co-edited several books and conference proceedings and co-guest-edited several journal special issues.