Developing Skills:

1. Problem Formulation and Model Building

• Acquire the skills to effectively formulate and build linear programming models for real-world problems, emphasizing the translation of practical scenarios into mathematical expressions.

2. Analytical and Computational Techniques

• Master the use of the simplex method for solving linear programming problems, including the handling of large-scale linear programs through software applications.
• Develop the ability to perform sensitivity analysis to understand the impact of changes in the parameters on the optimal solution.

Developing Knowledge Base

1. Foundational Principles of Linear Programming

• Gain a thorough understanding of the general principles, underlying assumptions, basic methods, and application areas of linear programming.

2. Special Linear Programming Problems

• Become familiar with the characteristics and solution strategies for special types of linear programming problems such as transportation, transshipment, assignment, and network flow problems.

3. Advanced Theoretical Concepts

• Understand the concepts of duality theory, its relationship with optimality, and the applications of advanced methods in linear programming, including the revised simplex algorithm.

Competencies

1. Critical Thinking and Decision Making

• Enhance the ability to think critically about complex problems, making reasoned decisions based on the analysis of linear programming models and solutions.

2. Interpretation and Analysis

• Learn to interpret software outputs accurately and conduct sensitivity analyses, enabling the evaluation of alternative solutions and the assessment of their implications for decision making.

3. Multi-Criteria Decision Making

• Develop competencies in dealing with multi-criteria decision-making problems, understanding how to balance competing objectives and constraints in optimization scenarios.

Cross-Cutting Themes

1. Integration of Theory and Practice

• Bridging theoretical concepts with practical applications, ensuring students can apply linear programming techniques to solve problems in various domains such as logistics, finance, healthcare, and energy.

2. Use of Technology in Problem Solving

• Emphasize the importance of leveraging computational tools and software for solving and analyzing large-scale linear programming problems, preparing students for the technological demands of the industry.