OR 6205. Deterministic Operations Research (4 Hours)

Course Outline:

1. Introduction to Deterministic Operations Research

• • Overview of deterministic models in industrial operations
  • Applications of deterministic operations research in decision-making

1. Linear Programming Formulation

• • Basics of linear programming (LP) models
  • Formulating industrial operations problems as linear programs

1. Solution Techniques for Linear Programming

• • Spreadsheet and algebraic languages software for LP solution
  • Introduction to simplex method and its variants

1. Linear Programming Algorithms

• • Overview of simplex algorithm
  • Big-M method for handling constraints
  • Two-phase and revised simplex algorithms
  • Dual simplex algorithm and its applications

1. Theory of Simplex

• • Fundamental insights into the simplex method
  • Duality in linear programming
  • Sensitivity analysis for decision-making

1. Specialized Linear Programming Problems

• • Transportation problems and solutions
  • Assignment and transshipment problems
  • Solving using linear programming techniques

1. Network Flow Problems

• • Shortest path problems
  • Minimum spanning tree problems
  • Maximum flow and minimum cost network flow problems
  • Project networks in industrial applications

1. Dynamic Programming Models

• • Discrete-state dynamic programming
  • Continuous-state dynamic programming
  • Applications of dynamic programming in operations research

Assignments and Assessments:

• Linear programming formulation projects
• Spreadsheet and software-based problem-solving assignments
• Midterm exam
• Final project: Solving a real-world industrial operations problem using deterministic operations research techniques

This course outline provides a comprehensive structure for OR 6205. Deterministic Operations Research, covering theoretical foundations, computational techniques, and practical applications. Assignments and assessments are included to reinforce learning, and the final project allows students to apply their knowledge to real-world industrial scenarios.