Advanced Logistics

Course Type：Compulsory Course

Credit Hours：32                                   Credits：2

Target Audience: Master's students in Engineering Management

1. Course Description

This course is designed for graduate students in Physical Engineering and Management, offering an in-depth exploration of modern logistics theories and practices. Drawing from Modern Logistics (Liu & Li), the course covers advanced topics such as supply chain integration, intelligent logistics, green logistics, and logistics network optimization. Students will examine cutting-edge technologies (e.g., IoT, AI, big data) and their applications in logistics systems. Case studies from manufacturing, e-commerce, and global supply chains will be used to illustrate key concepts.

2. Learning Outcomes

By the end of the course, students will:

l Understand advanced logistics theories, including lean logistics, reverse logistics, and risk management in supply chains.

l Analyze real-world logistics challenges using quantitative models and optimization techniques.

l Evaluate the impact of emerging technologies (e.g., automation, blockchain) on logistics efficiency and sustainability.

l Develop strategic decision-making skills for logistics system design and performance improvement.

3. Teaching Methods

l Interactive lectures to discuss theoretical frameworks and industry trends.

l Case-based learning to analyze logistics problems and solutions.

l Group projects where students design logistics strategies for simulated or real business scenarios.

4. Assessment Methods

Final Exam (Open Book): 70%

Regular Performance (30%): Attendance and project reports.