Operational Research for Decision Optimization

Master Operational Research techniques to solve complex business problems, optimize resources, and make smarter data-driven decisions. Learn assignment models, transportation methods, CPM, PERT, decision trees, and queuing theory through practical examples. This course gives you a structured pathway into Operational Research and its real-world applications in management, logistics, project planning, and service operations. You’ll learn how quantitative models help organizations allocate resources, reduce inefficiencies, evaluate alternatives, and improve operational performance. We’ll explore practical optimization techniques such as the Hungarian Method for assignment problems, Vogel’s Approximation Method and MODI for transportation problems, and network planning tools like Critical Path Method (CPM) and Program Evaluation and Review Technique (PERT). These methods help learners solve scheduling, distribution, and resource planning challenges with confidence. You’ll also study decision analysis tools including payoff tables and decision trees to evaluate choices under risk and uncertainty. The course further introduces queuing theory models to analyze waiting lines, service rates, system utilization, and customer flow in service environments. By the end of the course, you’ll be able to apply Operational Research techniques to real business scenarios, optimize decisions, improve efficiency, and support analytical problem-solving across operations, logistics, projects, and management contexts.