Operations Research Fundamentals: Linear and Dynamic Programming

Operations research provides powerful mathematical tools for making efficient decisions and solving complex resource allocation challenges. This text-based course introduces core optimization techniques without requiring prior experience in decision science. You will learn step-by-step how to analyze business and logistical problems, transform them into mathematical models, and find optimal solutions. Through clear written explanations and practical step-by-step examples, you will build a solid foundation in modern optimization strategies. What you'll learn: - Understand essential terminology, definitions, and foundational concepts of operations research. - Formulate linear programming models to solve resource distribution and allocation problems. - Analyze transportation problems using classic optimization methods and computational heuristics. - Apply dynamic programming concepts to break complex multi-stage decisions into manageable subproblems. - Explore modern software tools and algorithmic formulations used in practical decision science today. The course begins with fundamental terminology and core mathematical concepts before guiding you through structured problem-solving methods for linear, dynamic, and transportation models. This course is designed for beginners, students, and professionals who want to understand optimization techniques from scratch with no prior background in operations research. Start reading today to master the mathematical principles behind smart decision-making.