Optimization Techniques for Managers

Module 1: Introduction to Optimization Techniques (4 hours)

• Content:
  • Fundamentals of optimization in business.
  • Overview of linear programming, integer programming, and optimization theory.
  • Basic optimization problem-solving techniques.

• Module Objectives (MOs):
  1. Understand the key principles of optimization in a business context.
  2. Learn about different optimization methods and when to apply them.
  3. Formulate and solve simple optimization problems.

Module 2: Linear Programming for Decision Making (6 hours)

• Content:
  • In-depth introduction to linear programming.
  • Constraints and objective functions.
  • Solving linear programming problems using graphical and algebraic methods.
  • Introduction to optimization software like Excel Solver.

• Module Objectives (MOs):
  1. Formulate linear programming problems for business applications.
  2. Solve linear optimization problems using algebraic and graphical methods.
  3. Apply optimization software tools to solve linear programming models.

Module 3: Integer and Mixed-Integer Programming (6 hours)

• Content:
  • Understanding integer programming and its applications in business.
  • Mixed-integer programming techniques and real-world use cases.
  • Application of integer programming in scheduling, logistics, and workforce planning.

• Module Objectives (MOs):
  1. Formulate and solve integer and mixed-integer programming problems.
  2. Apply integer programming in resource allocation and scheduling problems.
  3. Explore practical case studies using mixed-integer programming for business optimization.

Module 4: Supply Chain and Logistics Optimization (6 hours)

• Content:
  • Optimization techniques in supply chain management.
  • Inventory management, transportation, and distribution optimization.
  • Routing problems (e.g., Traveling Salesman Problem) and warehouse optimization.

• Module Objectives (MOs):
  1. Apply optimization methods to solve supply chain and logistics challenges.
  2. Optimize inventory management and reduce transportation costs.
  3. Use algorithms to solve routing and scheduling problems.

Module 5: Resource Allocation and Workforce Scheduling (6 hours)

• Content:
  • Optimizing resource allocation in project management.
  • Workforce scheduling models and techniques.
  • Case studies in resource optimization for teams and projects.

• Module Objectives (MOs):
  1. Use optimization methods to allocate resources effectively in projects.
  2. Apply workforce scheduling techniques to improve productivity and efficiency.
  3. Implement real-world optimization solutions in staffing and team management.

Module 6: Advanced Optimization Methods (5 hours)

• Content:
  • Introduction to advanced optimization techniques like nonlinear programming.
  • Metaheuristics methods: Genetic Algorithms, Simulated Annealing, etc.
  • Applying advanced techniques to complex business optimization problems.

• Module Objectives (MOs):
  1. Understand and apply advanced optimization methods for complex business challenges.
  2. Explore metaheuristic algorithms and their business applications.
  3. Solve complex optimization problems with nonlinear and heuristic techniques.

Module 7: Practical Application: Optimization Project (3 hours)

• Content:
  • Working on a real-world optimization project based on course learnings.
  • Collaborative work to optimize a business process or resource allocation.
  • Presentation of project outcomes and optimization strategies.

• Module Objectives (MOs):
  1. Apply optimization techniques to a real-world business problem.
  2. Develop a comprehensive optimization strategy for a business case.
  3. Present findings and actionable recommendations to stakeholders.