Linear Programming in MATLAB: Solving the Transportation Problem

Optimization is at the heart of efficient decision-making in logistics, engineering, and business. This text-based course guides you through translating real-world constraints into mathematical models and solving them efficiently using MATLAB. You will transition from understanding basic linear programming theory to writing clean, optimized MATLAB code that solves complex resource allocation challenges, with a special emphasis on the classic transportation problem. What you'll learn: Understand the mathematical foundations of linear programming, objective functions, and decision constraints; Formulate optimization models using modern MATLAB problem-based syntax; Solve classic transportation and logistics problems by defining supply, demand, and cost matrices; Apply the linprog solver and interpret decision variables and shadow prices; Write clean, readable, and vectorized MATLAB code for optimization workflows; Analyze sensitivity and troubleshoot infeasible or unbounded optimization models. The course begins with essential optimization terminology and foundational mathematical definitions before moving into hands-on code implementations. You will progress from simple two-variable problems to multi-source, multi-destination transportation scenarios. Designed for beginners in optimization and MATLAB, this course requires no advanced mathematical background or prior programming experience. Start reading today to master the fundamentals of linear programming and optimize your decision-making workflows.