Foundations of Linear Programming and Optimization

Linear programming is a powerful mathematical tool used across industries to optimize resources, minimize costs, and maximize efficiency. If you are looking to build a strong foundation in this essential branch of mathematics, this course offers a clear, structured path to mastery. You will transition from understanding basic inequalities to confidently formulating and solving complex optimization problems on your own. Through clear written explanations, you will learn how to translate real-world scenarios into mathematical models and solve them step-by-step. We begin with key terminology and the foundational concepts of linear inequalities before moving on to practical formulation and modern optimization workflows. What you'll learn: - Understand the core concepts of linear programming, objective functions, and constraints - Formulate mathematical models from real-world business and resource-allocation scenarios - Solve linear programming problems using the graphical method and identify feasible regions - Master fundamental optimization techniques, including finding maximum and minimum values - Apply sensitivity analysis concepts to understand how changes in variables affect your outcomes - Practice solving typical academic and real-world optimization problems through step-by-step written exercises This course is structured to build your knowledge from the ground up, starting with basic definitions and algebraic foundations before progressing to multi-constraint optimization problems. You will work through structured written examples that reinforce your understanding of every formula and method. This course is designed for beginners, students, and professionals new to optimization, requiring only a basic understanding of high school algebra. Start reading today to master the core principles of linear programming.