Optimization for Logistics: Solving Transportation Problems

Effective logistics management is crucial for minimizing costs and maximizing efficiency in any business involving physical goods. Transportation problems, which involve finding the most cost-effective way to move products from sources to destinations, are fundamental to this process. By completing this course, you will transform raw supply and demand data into actionable, optimized delivery plans. You will gain the analytical skills necessary to model real-world distribution challenges and derive mathematically proven optimal solutions. What you'll learn: * Understand the foundational structure and terminology of balanced and unbalanced transportation problems. * Apply initial basic feasible solution methods, including the Northwest Corner Rule, Least Cost Method, and Vogel's Approximation Method (VAM). * Master the Modified Distribution (MODI) method for testing and improving solutions to achieve mathematical optimality. * Analyze special cases in optimization, such as degeneracy and the use of penalty costs in assignment problems. * Configure and set up simple transportation models suitable for solution using modern computational optimization software. * Practice interpreting the results of optimization models to inform strategic logistics planning and resource allocation. The course begins with essential concepts and definitions, gradually progressing through step-by-step written explanations of classical solution algorithms. You will then practice applying these techniques through structured exercises designed to build confidence in modeling and solving complex distribution challenges. This course is designed for absolute beginners in operations research, supply chain management, or quantitative logistics who want a foundational understanding of optimization. No prior knowledge of advanced mathematics or programming is required. Start building your analytical foundation for efficient supply chain management today.