Modeling city logistics using adaptive dynamic programming based multi-agent simulation
暂无分享,去创建一个
[1] Eiichi Taniguchi,et al. Data Collection for Modelling, Evaluating and Benchmarking City Logistics Schemes , 2005 .
[2] Lóránt Tavasszy,et al. Validation of an agent based model using a participatory simulation gaming approach : The case of city logistics , 2016 .
[3] Huaguang Zhang,et al. An Overview of Research on Adaptive Dynamic Programming , 2013, Acta Automatica Sinica.
[4] Eiichi Taniguchi,et al. Application of exact route optimization for the evaluation of a city logistics truck ban scheme , 2014 .
[5] Kazuya Kawamura,et al. Analysis of Factors that Affect the Frequency of Truck Parking Violations in Urban Areas , 2014 .
[6] J.H.R. van Duin,et al. The Seventh International Conference on City Logistics Towards an agent-based modelling approach for the evaluation of dynamic usage of urban distribution centres , 2012 .
[7] Eiichi Taniguchi,et al. Evaluating city logistics measures using a multi-agent model , 2010 .
[8] Eiichi Taniguchi,et al. Evaluation of Load Factor Control and Urban Freight Road Pricing Joint Schemes with Multi-agent Systems Learning Models☆ , 2014 .
[9] Laetitia Dablanc,et al. Freight transport for development toolkit : urban freight , 2009 .
[10] Eiichi Taniguchi,et al. EVALUATING CITY LOGISTICS MEASURES CONSIDERING THE BEHAVIOR OF SEVERAL STAKEHOLDERS , 2005 .
[11] Donald J. Bowersox,et al. ESTIMATION OF GLOBAL LOGISTICS EXPENDITURES USING NEURAL NETWORKS , 2003 .
[12] Eiichi Taniguchi,et al. Exact solution for the vehicle routing problem with semi soft time windows and its application , 2010 .
[13] E. Taniguchi,et al. Evaluation of Urban Distribution Centers Using Multiagent Modeling with Geographic Information Systems , 2015 .
[14] Eiichi Taniguchi,et al. MULTI-AGENT SIMULATION USING ADAPTIVE DYNAMIC PROGRAMMING IN THE EXISTENCE OF URBAN CONSOLIDATION CENTERS , 2017 .
[15] John N. Tsitsiklis,et al. Neuro-Dynamic Programming , 1996, Encyclopedia of Machine Learning.
[16] Sridhar Mahadevan,et al. Optimizing Production Manufacturing Using Reinforcement Learning , 1998, FLAIRS.
[17] Warren B. Powell,et al. An Adaptive Dynamic Programming Algorithm for Dynamic Fleet Management, I: Single Period Travel Times , 2002, Transp. Sci..
[18] Derek Fagan,et al. Dynamic Multi-agent Reinforcement Learning for Control Optimization , 2014, 2014 5th International Conference on Intelligent Systems, Modelling and Simulation.
[19] Joel S. E. Teo,et al. Multi-agent Systems Modelling for Evaluating Joint Delivery Systems , 2014 .
[20] Otthein Herzog,et al. Machine learning in agent-based stochastic simulation: Inferential theory and evaluation in transportation logistics , 2012, Comput. Math. Appl..
[21] Richard S. Sutton,et al. Generalization in Reinforcement Learning: Successful Examples Using Sparse Coarse Coding , 1995, NIPS.
[22] Eiichi Taniguchi,et al. Recent Developments and Prospects for Modeling City Logistics , 2018, City Logistics 1.
[23] Eiichi Taniguchi,et al. Multi-Agent Simulation Using Adaptive Dynamic Programing for Evaluating Urban Consolidation Centers , 2018 .
[24] Hans Quak,et al. City logistics: A chaos between research and policy making? A review , 2007 .
[25] Jacques Ferber,et al. Multi-agent systems - an introduction to distributed artificial intelligence , 1999 .
[26] Rinaldo A. Cavalcante,et al. A conceptual framework for agent-based modelling of logistics services , 2010 .
[27] R. van Duin,et al. Ontology-based multi-agent system for urban freight transportation , 2014 .
[28] Donald A. Sofge,et al. Handbook of Intelligent Control: Neural, Fuzzy, and Adaptive Approaches , 1992 .
[29] Richard S. Sutton,et al. Reinforcement Learning: An Introduction , 2005, IEEE Transactions on Neural Networks.