1. Linear Programming Problem Solving:
- Case study analysis of a real-world linear programming problem, such as optimizing production schedules or resource allocation. The goal is to formulate the problem as a linear programming model and use software (e.g., Excel Solver) to find the optimal solution.
2. Transportation and Assignment Problems:
- Analyze a logistics problem involving transportation costs or assignment of resources. Formulate and solve the problem using the transportation or assignment model. Interpret the results and discuss managerial implications.
3. Queuing Theory Applications:
- Evaluate a queuing system, such as a customer service department or a production line. Use queuing models to analyze waiting times, server utilization, and system performance. Determine optimal strategies to manage the system.
4. Inventory Management Project:
- Develop an inventory management model to determine optimal inventory levels for a given product or set of products. Consider demand patterns, lead times, and inventory costs. Analyze the impact of different inventory policies on overall costs.
5. Simulation of a Supply Chain:
- Create a simulation model of a supply chain involving multiple stages, such as suppliers, manufacturers, and retailers. Use the simulation to analyze the impact of different supply chain strategies on factors like lead times, inventory levels, and customer service.
6. Project Scheduling and Network Analysis:
- Apply network analysis techniques (e.g., CPM or PERT) to schedule a complex project. Identify critical activities and paths, estimate project duration, and analyze the impact of resource constraints.
7. Optimization of a Service System:
- Investigate a service system, such as a call center or a healthcare facility. Use operations research techniques to analyze the system's performance and identify improvement opportunities, such as optimizing staff schedules or resource allocation.
8. Monte Carlo Simulation for Risk Analysis:
- Apply Monte Carlo simulation to assess the risk associated with a business decision. Model uncertain variables and perform simulations to generate probability distributions of potential outcomes.
9. Break-Even Analysis and Cost Optimization:
- Conduct a break-even analysis for a new product or service. Use linear programming or other optimization techniques to find the optimal price, production quantity, and other decision variables to maximize profit.
10. Decision Analysis Case Study:
- Analyze a complex decision-making scenario involving multiple criteria and uncertainty. Use decision analysis techniques (e.g., decision trees or influence diagrams) to structure the problem, evaluate alternatives, and make recommendations.