This class is for the students of B.Tech and MBA.

In operations research, students learn a variety of quantitative and analytical techniques to solve complex problems and optimize decision-making processes. Operations research, also known as management science, is a multidisciplinary field that applies mathematical modeling, statistical analysis, and optimization methods to improve operations and decision-making in organizations.

Here are some of the key topics and techniques that students typically learn in operations research:

1. Mathematical Modeling: Students learn how to represent real-world problems mathematically using equations, functions, and variables. They learn to translate complex situations into mathematical models that can be analyzed and solved.

2. Optimization Techniques: Optimization is a central concept in operations research. Students learn various optimization techniques such as linear programming, integer programming, nonlinear programming, and network optimization. These methods help in finding the best solutions from a set of possible alternatives, taking into account constraints and objectives.

3. Probability and Statistics: Students learn to use probability theory and statistical analysis to analyze and predict uncertain events and outcomes. They learn techniques such as probability distributions, statistical inference, hypothesis testing, regression analysis, and simulation methods.

4. Decision Analysis: Decision analysis focuses on making rational decisions in the face of uncertainty. Students learn decision-making frameworks such as decision trees, utility theory, and risk analysis. They learn how to evaluate alternative courses of action and quantify the potential risks and benefits associated with different decisions.

5. Simulation: Simulation involves creating mathematical or computer models to mimic real-world systems or processes. Students learn simulation techniques to analyze and evaluate the performance of complex systems, such as manufacturing processes, transportation networks, or supply chains.

6. Inventory Management: Students learn techniques for managing inventory levels in organizations to balance costs and customer service levels. This includes determining optimal ordering policies, reorder points, and safety stock levels.

7. Queuing Theory: Queuing theory deals with the analysis and optimization of waiting lines. Students learn how to model and analyze queuing systems to optimize service levels, minimize waiting times, and improve overall system performance.

8. Project Management: Operations research techniques are often applied to project management to optimize project scheduling, resource allocation, and risk assessment. Students learn how to use techniques such as critical path analysis, resource leveling, and project network models.

9. Supply Chain Optimization: Supply chain management involves coordinating the flow of goods, information, and funds across different stages of a product's life cycle. Students learn optimization methods to improve supply chain efficiency, such as inventory management, demand forecasting, transportation optimization, and facility location.

10. Decision Support Systems: Students learn about computer-based decision support systems that use operations research techniques to assist managers in making informed decisions. They learn how to develop and use decision support tools and software.