Course Outline:

Module 1: Introduction to Operations Research and Optimization

• Overview of operations research and its importance
• Introduction to optimization techniques and their applications
• Basics of LINDO software and its functionalities
• Hands-on Exercise: Navigating LINDO and performing basic optimization tasks
• Case Study: Solving a simple optimization problem using LINDO

Module 2: Linear Programming Fundamentals

• Principles of linear programming and problem formulation
• Introduction to LINDO’s linear programming features
• Solving linear programming problems using LINDO
• Hands-on Exercise: Formulating and solving linear programming models
• Real-Life Project: Linear programming for optimizing resource allocation in manufacturing

Module 3: Integer Programming and Mixed-Integer Programming

• Concepts of integer and mixed-integer programming
• Using LINDO for solving integer and mixed-integer programming problems
• Applications and challenges in integer programming
• Hands-on Exercise: Solving integer and mixed-integer programming models in LINDO
• Case Study: Inventory management optimization using integer programming

Module 4: Nonlinear Programming Techniques

• Introduction to nonlinear programming and problem types
• Utilizing LINDO for nonlinear optimization
• Techniques for solving nonlinear programming problems
• Hands-on Exercise: Solving nonlinear optimization problems with LINDO
• Real-Life Project: Nonlinear programming for optimizing production processes

Module 5: Dynamic Programming and Sequential Decision Making

• Principles of dynamic programming and its applications
• Using LINDO for dynamic programming problems
• Techniques for sequential decision making
• Hands-on Exercise: Implementing dynamic programming models in LINDO
• Case Study: Optimal scheduling and resource allocation using dynamic programming

Module 6: Stochastic Optimization and Simulation

• Introduction to stochastic optimization and simulation techniques
• Using LINDO for stochastic and simulation-based optimization
• Applications in uncertain and dynamic environments
• Hands-on Exercise: Implementing stochastic optimization models in LINDO
• Real-Life Project: Simulation and optimization for supply chain management under uncertainty

Module 7: Network Optimization and Graph Theory

• Concepts of network optimization and graph theory
• Applying LINDO to network optimization problems
• Techniques for solving graph-based optimization problems
• Hands-on Exercise: Network optimization using LINDO
• Case Study: Optimization of transportation and logistics networks

Module 8: Multi-Criteria Decision Analysis (MCDA)

• Principles of multi-criteria decision analysis and its importance
• Using LINDO for MCDA problems
• Techniques for evaluating and optimizing multiple criteria
• Hands-on Exercise: Implementing MCDA models in LINDO
• Real-Life Project: Multi-criteria decision making for project selection

Module 9: Field Visit and Practical Insights

• Field visit to operations research labs and optimization centers
• Observation of real-world applications and practices
• Interaction with industry professionals and experts
• Field Visit Report: Documentation and analysis of field visit observations

Module 10: Capstone Project and Course Review

• Comprehensive project integrating all course concepts and skills
• Participants present their projects and receive feedback from instructors
• Review of key concepts, best practices, and future learning paths
• Final Project Presentation: Showcase of a complete optimization solution using LINDO