Module #1 Introduction to Green Transportation Overview of green transportation, its importance, and the role of algorithms in optimizing transportation systems
Module #2 Sustainable Transportation Modes Exploring alternative modes of transportation (e.g., electric vehicles, public transit, biking, walking) and their environmental impact
Module #3 Optimization Fundamentals Review of optimization basics (e.g., linear programming, dynamic programming, graph theory) and their application to transportation problems
Module #4 Route Optimization Algorithms Introduction to route optimization algorithms (e.g., Dijkstras, Bellman-Ford, A* search) and their applications in transportation
Module #5 Vehicle Routing Problems Formulation and solution methods for Vehicle Routing Problems (VRPs) and their variants
Module #6 Electric Vehicle Routing and Charging Optimization algorithms for electric vehicle routing and charging, considering range anxiety and charging infrastructure
Module #7 Green Logistics and Supply Chain Management Applying advanced algorithms to optimize logistics and supply chain operations for reduced environmental impact
Module #8 Traffic Flow and Simulation Modeling and simulating traffic flow to optimize traffic management and reduce congestion
Module #9 Machine Learning for Transportation Applications of machine learning in transportation, including predictive modeling and traffic pattern analysis
Module #10 Deep Learning for Traffic Prediction Using deep learning techniques (e.g., CNNs, RNNs) for traffic prediction and forecasting
Module #11 Optimizing Public Transit Systems Applying advanced algorithms to optimize public transit routes, schedules, and operations
Module #12 Shared Mobility and On-Demand Services Optimization algorithms for shared mobility services (e.g., ride-hailing, car-sharing) and on-demand transportation
Module #13 Autonomous Vehicles and Platooning Algorithms for autonomous vehicle control and platooning, including trajectory planning and collision avoidance
Module #14 Smart Charging and Energy Management Optimizing charging schedules and energy management for electric vehicles, considering grid capacity and renewable energy sources
Module #15 Transportation Network Analysis Analyzing transportation networks using graph theory and network science, with applications in route planning and infrastructure optimization
Module #16 Green Transportation Policy and Regulations Exploring policy and regulatory frameworks that support green transportation, including incentives and disincentives
Module #17 Case Studies in Green Transportation Real-world examples and case studies of successful green transportation projects and initiatives
Module #18 Future of Green Transportation Emerging trends and technologies in green transportation, including electrification, autonomous vehicles, and more
Module #19 Capstone Project Development Guided development of individual or group projects applying advanced algorithms to a green transportation problem or case study
Module #20 Course Wrap-Up & Conclusion Planning next steps in Advanced Algorithms for Green Transportation career
