URL: http://133.11.80.48/model22/
The Summer School on Behavioral Model in Networks will be held September 23-25. The keynote lecture will be given by Prof. Teodor Gabriel Crainic (Université de Montréal), an organizer of TRISTAN and a world leader in OR who has been working on optimal transportation problems for many years, on stochastic demand combination optimization problems. There will also be a lecture by Prof. Tetsuo Yai, who has made significant contributions to the advancement of demand forecasting models and their application to planning theory for metropolitan area railroad planning. In order to meet the needs of doctoral students, the lecture will be based on the fundamentals of behavioral models combined with OR, including Statistics in Behavioral Models and Evolutionary Coupling of Machine Learning, and Can Can Urbanists Change Cities with Diverse Mathematics? Latest Optimization Theory and Network Problems, and more. There is no registration fee, so please feel free to attend.
Contact Eiji Hato: hato@bin.t.u-tokyo.ac.jp
Program Outline of the 21st Summer School on Behavioral Modeling in Networks
Day 1 (September 23) :0830-10:00 Opening, Eiji Hato (UTokyo), Commemorative Lecture, Deterministic/Stochastic Demand Optimization for Urban Logistics, Prof. Teodor Gabriel Crainic (Université de Montréal), 10:00-11:00 Python and R Tutorial for Beginners, Risa Kobayashi and Moe Watanabe (UTokyo)11:10-12:00 Esq, Lunch, Lecture Series 1: Sttistics in Behavioral Modelling with Machine Learning, 13:00-14:00 1. Basics of behavioral modelling, Arnab Jana (IIT Bombay)2. Size matters: The use and misuse of statistical tests in discrete choice models, Giancarlos Troncoso Parady (UTokyo), 14:00-14:15 Break1, 14:15-15:45 3. Fundamentals of neural network modelling, Makoto Chikaraishi (Hiroshima University), 4. Fundamentals and applications of weak learners, Muhammad Awais Shafique (University of Central Punjab)5. Overview of machine learning, Hideki Yaginuma (Tokyo University of Science)15:45-16:00 Break, 16:00-17:00 6. Recursive structure of decision-making in networks: Modeling and estimation, Yuki Oyama (Shibaura Institute of Technology), 7. Behavioral mechanism design and Bayesian truth serum, Yusuke Hara (Tohoku University)
Day 2 (September 24) 9:00-10:00, 1. Introduction of Behavioral Models Shinya Kurauchi (Ehime Univ.) 2. Basics of Estimation Kuniaki Sasaki (Waseda Univ.) 10:00-10:30, Break10:30-11:303. Basics of Network Models Takuya Maruyama (Kumamoto Univ.) 4. Applications of Network Models Takamasa Iryo ( (Univ. of Tokyo) 11:30-13:00, Lunch, 13:00-14:30 #1 BinN Research Seminar: Latest Optimization Theory and Network Problems, Chair: Jan-Dirk Schmoecker (Kyoto University)Talk: Takao Dantsuji x Fuga Mayuzumi x Riki Kawase, 1. Meta-reinforcement learning for multi-modal multi-region coordinated control, Takao Dantsuji (Kanazawa University), 2. A structured programming method for matching heterogeneous demand in mixed freight and passenger network, Fuga Mayuzumi (UTokyo), 3. Optimization of inventory transportation strategy, considering the procurement of goods by the affected population, Riki Kawase (Tokyo Institute of Technology)
Day 3 9/25 (September 25) #2 BinN Research Seminar: Can Urbanists Change Cities with Diverse Mathematics?Chair: Yusuke Hara（Tohoku University）Risa Kobayashi x Hiroe Ando x Hajime Watanabe, 1.Modeling and Case Study of Land Transaction Mechanism with Gale-Shapley Algorithm, Risa Kobayashi (UTokyo), 2. Characteristic of transport network based on the eigenvalue analysis, Hiroe Ando (Kumamoto University), 3. Bayesian sample selection model for dealing with non-randomly missing travel behavior outcomes, Hajime Watanabe (UTokyo), 12:00-13:00 Lunch, 13:00-14:00 Keynote lecture, Prof. Tetsuo Yai (Tokyo Institute of Technology) 14:00- Presentation of estimation results of programming competition (10min/team), BinN Young Prize Ceremony, Kasumi Prize, Davis Prize, 18:00-20:00 Online wrap up party
Detailed Program
9/23 Statistics in Behavioral Models and Evolutionary Coupling of Machine Learning, Arnab Jana × Giancarlos Troncoso Parady × Masato Rikiishi × Muhammad Awais Shafique × Hideki Yananuma × Yumi Oyama × Yusuke Hara, Outline: How is machine learning changing behavioral and network models? Through statistical grounding and applications of weak learners and neural networks such as RNNs to the field of transportation such as spatio-temporal correlation, traffic identification, and image processing, you will learn about new decision-making models with recursive structures and cutting-edge research approaches such as behavioral mechanism design. Lecture Series 1:Behavioral Modelling and Machine Learning, 13:00-14:00 1. Basics of behavioral modelling, Arnab Jana (IIT Bombay)2. Size matters: The use and misuse of statistical tests in discrete choice models, Giancarlos Troncoso Parady (UTokyo), 14:00-14:15 Break1, 14:15-15:45 3. Fundamentals of neural network modelling, Makoto Chikaraishi (Hiroshima University), 4. Fundamentals and applications of weak learners, Muhammad Awais Shafique (University of Central Punjab)5. Overview of machine learning, Hideki Yaginuma (Tokyo University of Science)15:45-16:00 Break, 16:00-17:00 6. Recursive structure of decision-making in networks: Modeling and estimation, Yuki Oyama (Shibaura Institute of Technology), 7. Behavioral mechanism design and Bayesian truth serum, Yusuke Hara (Tohoku University)
9/24 #1 BinN Research Seminar：Latest Optimization Theory and Network Problems Talk: Takao Dan Tsujix Kazumasa Mayuzumi x Riki Kawase Moderates: Jan‐Dirk SCHMOECKER, September 24, 2022 1300-1430 There is a growing interest in optimal transportation planning of behaviors and people and goods on networks. When transportation behavior is viewed as a problem of matching heterogeneous preferences and combinatorial optimization, network flows need to be solved as an NP-hard problem, and thus coupling with neighborhood search, column generation, structured processing of alternatives, and AI-assisted parameterization becomes important. Invited talks by three young researchers representing our field will provide graduate students with an overview of these current research issues, while Schomocker moderates a discussion of the latest research results. 1. Meta-reinforcement learning for multi-modal multi-region coordinated control, Takao Dantsuji (Kanazawa University), 2. A structured programming method for matching heterogeneous demand in mixed freight and passenger network, Fuga Mayuzumi (UTokyo), 3. Optimization of inventory transportation strategy, considering the procurement of goods by the affected population, Riki Kawase (Tokyo Institute of Technology)
9/25 #2 BinN Research Seminar：Can Urbanists Change Cities with Diverse Mathematics? Talk: Risa Kobayashi x Hiroe Ando x Hajime Watanabe, Moderates: Yusuke HARA, September 25, 2022 1030-1200, When we recursively relate behaviors on transportation networks through large data to urban transformation and planning interventions, will this bring unprecedented new theories and analytical methods to the field of behavioral modeling? Through the results of eigenvalue analysis of patterns using big data, mutual dynamic mechanism of land transactions, and self-selection problems by young researchers working on unexplored issues, we would like to think about the development of new estimation and analysis methods for behavioral models on networks through discussions with Hara, who is working on advanced research on mechanism design. We would like to consider this through discussion. 1.Modeling and Case Study of Land Transaction Mechanism with Gale-Shapley Algorithm, Risa Kobayashi (UTokyo), 2. Characteristic of transport network based on the eigenvalue analysis, Hiroe Ando (Kumamoto University), 3. Bayesian sample selection model for dealing with non-randomly missing travel behavior outcomes, Hajime Watanabe (UTokyo)
