Smart Logistics and Supply Chains (edX)

Smart Logistics and Supply Chains (edX)
Learn the foundations of analytical tools, methods, and applications of logistics systems in the context of planning and operations of integrated supply chain systems. This course provides a foundation of analytical tools, methods and applications of logistics systems in the context of planning and operations of integrated supply chain systems. The material is useful for students interested in managing supply chain systems providing background on where and how specific methods can be used for improving overall performance of the supply chain.

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The course is broadly divided into two parts: (1) Science of Logistics which provides an introduction to unique characteristics of supply chain management; demand forecasting, planning and management; inventory control and planning; operational transportation issues such as vehicle routing and supply chain contracts and network design. (2) Business of Logistics which discusses the applications of the science to real-world logistics systems. Real-world case studies from past problems will be the basis for discussion and will include the nature of costs in supply chain networks, operational issues, vehicle routing problems, and interactions of carriers and shippers using auctions. The course will use intuitive arguments and mathematical optimization tools to illustrate the concepts in a rigorous fashion. Examples of problems that will be discussed include a few examples of real-world problems in logistics (Dell supply chain, multimodal transportation from Asia to Europe), supply chain contracts, auctions in freight supply chains, and intermodal considerations in freight modeling.

What you'll learn

- Reinforce the integrated nature of logistics systems from tactical, operational and strategic perspectives, different actors in this system and the role of logistics systems as an economic driver.

- Understand the basics concepts and models of demand prediction, inventory management, operational and tactical planning in supply chain management.

- Demonstrate the ability to develop appropriate quantitative tools for planning and logistics problems using optimization techniques and solve them using appropriate solution algorithms, techniques and software.

- Apply the science of logistics systems to improve the cost and overall efficiency of real-world logistics problems


Undergraduate calculus, basic knowledge of probability and statistics at the undergraduate level. Competency in using excel and VB for data analysis. As a graduate elective, this course is appropriate for students with an interest in learning about models and business aspects of logistics systems.


Unit 1. Conceptual Foundation

- Role of Supply Chain Modeling

- Definition of Logistics Management

- Functional View

- Segmentation

- ABC Analysis

Unit 2. Tactical Level

(Demand Forecasting Methods)

- Regression & Time series Model

- Adaptive Forecasting Methods

- Measures of Forecast Error

- Causal & BASS Model

- Case Study 0: HBR Materials

(Inventory Control Methods)

- Costs in Inventory System

- EOQ Models with Constant Demands, Stochastic Demands, and Time varying Demands

- Case Study1: Improving the Logistics Handling of Dell Systems

Unit 3. Operational Level

(Operational Networks)

- Key Components

- Driving Influences

- Case Study 2: Multimodal Transportation: an Example of Labtop

(Basics of Network Flows)

- Fundamental Definitions of Networks

- Mathematical Description

- Shortest Path Problem

- Dijkstra’s Algorithm

- Maximum Flow Problem

- Minimum Spanning Tree

(Shipper Perspective)

- Traveling Salesman Problem

- Vehicle Routing Problem

Unit 4. Strategic Level

- Network Design

- Supply Chain Contracts

- Auction in Freight Supply Chains

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