Linear Programming and Optimization for Decision Making

Every business and system faces the challenge of limited resources and the need to maximize efficiency. Understanding how to mathematically model these scenarios is the key to making optimal, data-driven decisions. This text-based course guides you through the foundational principles of Linear Programming Problems (LPP) and optimization techniques. You will transition from understanding basic terminology to formulating and solving complex allocation, transportation, and project management problems using structured mathematical approaches. What you will learn: 1. Understand the fundamental terminology and mathematical formulation of Linear Programming Problems. 2. Solve optimization problems visually using the graphical method for two-variable scenarios. 3. Apply the Simplex and Dual Simplex algorithms to resolve multi-variable optimization challenges. 4. Formulate and solve transportation and assignment problems to streamline logistics and resource distribution. 5. Analyze project schedules and dependencies using PERT and CPM network techniques. 6. Explore modern applications of optimization algorithms in machine learning and resource management. The course starts with basic definitions and step-by-step mathematical modeling before moving into algorithmic solutions and network analysis. You will progress through written explanations, clear formulas, and practical scenarios designed to build your analytical confidence. This course is designed for beginners in operations research, computer science, or business analytics, and requires no advanced mathematical prerequisites beyond basic algebra. Start building your optimization toolkit today and learn to solve complex decision-making problems systematically.