Network Optimization Fundamentals: Solving Flow and Routing Problems

Every efficient logistics network, data routing system, and supply chain relies on solving complex path and flow challenges. Understanding how to model these problems mathematically is a key skill for developers, analysts, and operations managers. This text-based course helps you transition from a beginner to a confident practitioner capable of modeling and solving network optimization problems. You will learn to identify key network structures, apply classic optimization algorithms, and implement modern programmatic solutions to streamline real-world operations. What you will learn: 1. Understand foundational graph theory and network terminology, including nodes, edges, capacities, and flows. 2. Solve shortest path and minimum spanning tree problems for optimal routing. 3. Analyze maximum flow and minimum cut problems to eliminate bottlenecks. 4. Formulate minimum cost flow models to minimize transportation expenses. 5. Apply modern Python-based optimization libraries to translate mathematical formulations into clean code. The course begins with core terminology and basic graph theory before guiding you step-by-step through classic algorithms and computational modeling. This course is designed for beginners in operations research, computer science, or logistics, requiring no prior experience in advanced optimization. Start reading today to unlock the power of network optimization.