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Yunnan Normal University

Operations Research

Yunnan Normal University via XuetangX

Overview

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Operations research is a discipline that has evolved from decision-making problems arising in military, economic, and production activities. It assists individuals in applying mathematical methods to solve practical problems, providing quantitative support for decision-makers in selecting optimal solutions. As a course within the mathematics curriculum, operations research emphasizes both theoretical and practical aspects, guided by a teaching philosophy that prioritizes foundational theory and practical application. The course focuses on establishing mathematical models through real-world examples, exploring practical models and methods applicable to everyday life. Throughout the teaching of operations research, we emphasize effective integration with mathematical modeling competitions, encouraging students to participate in national modeling contests. This approach fosters learning and teaching, laying a solid foundation for enhancing students' critical thinking and comprehensive application skills. By completing this course, students will master quantitative mathematical analysis models, cultivate holistic optimization thinking, and improve their research and innovation capabilities, thereby establishing a strong basis for subsequent specialized coursework.

1. To understand the brief history of operations research and its connections to other disciplines such as military and economics. Students will master models, theories, and algorithms related to linear programming, goal programming, integer programming, dynamic programming, and graph and network optimization, along with the analysis and techniques for solving these models.

2. To proficiently grasp the basic modeling methods, theories, and algorithms of linear programming, goal programming, integer programming, dynamic programming, and network optimization. Students will learn to flexibly apply these techniques using computer software to solve practical problems, aiming for optimal resource allocation and decision-making through mathematical and simulation modeling.

3. To recognize the emergence, history, and cutting-edge developments of operations research in China, thereby enhancing students' national pride and confidence. By applying operations research to address real-life issues, such as improving service quality and reducing living costs, students will cultivate a rigorous academic spirit and holistic awareness. Collaborative activities, such as group discussions, will emphasize the importance of teamwork. Instructors will model the integration of professional knowledge with personal development of worldview, life perspective, and values.

4. To present operations research concepts in an accessible manner, allowing students to appreciate its wisdom and enhance their logical thinking skills. Students will learn to view life and study through the lens of operations research and acquire the ability to model and solve practical problems using foundational theories from various branches of the discipline.


Syllabus

  • Chapter 1: Introduction to Operations Research
    • 1.1 A Brief History and Characteristics of Operations Research
    • 1.2 Steps in Operations Research
  • Chapter 2: Linear Programming and the Simplex Method
    • 2.1 Introduction to Linear Programming Problems and Mathematical Models
    • 2.2 Diagram Method
    • 2.3 Forms and Concepts of Linear Programming Problems
    • 2.4 Geometric Meaning of Linear Programming Problems
    • 2.5 Simplex Method
    • 2.6 Calculation Steps of the Simplex Method
    • 2.7 Artificial Variable Method
  • Chapter 3: Dual Theory and Sensitivity Analysis
    • 3.1 Matrix Description
    • 3.2 Matrix Calculations in the Simplex Method
    • 3.3 Introduction to Dual Problems
    • 3.4 Theory of Dual Problems
    • 3.5 Shadow Prices
    • 3.6 Dual Simplex Method
  • Chapter 4: Transportation Problem
    • 4.1 Mathematical Model of Transportation Problems
    • 4.2 Hitchock Method
    • 4.3 Transportation Problems with Production and Marketing Imbalance and Their Solution Methods
  • Chapter 5: Linear Goal Programming
    • 5.1 Mathematical Model of Goal Programming
    • 5.2 Diagram Method for Solving Goal Programming
    • 5.3 Simplex Method for Solving Goal Programming
  • Chapter 6: Integer Linear Programming
    • 6.1 Introduction to Integer Programming Problems
    • 6.2 Branch and Bound Method
    • 6.3 Cutting Plane Method
    • 6.4 0-1 Integer Linear Programming
    • 6.5 Assignment Problems
  • Chapter 7: Basic Methods of Dynamic Programming
    • 7.1 Multi-phase Decision Processes and Examples
    • 7.2 Basic Concepts and Equations of Dynamic Programming
    • 7.3 Optimality Principles and Theorems in Dynamic Programming
  • Chapter 8: Graph and Network Optimization
    • 8.1 Basic Concepts of Graphs
    • 8.2 Trees
    • 8.3 Shortest Path Problems
    • 8.4 Maximum Flow Problems in Networks
    • 8.5 Minimum Cost Maximum Flow Problems
    • 8.6 The Chinese Postman Problem
  • Final examination

    Taught by

    Huang Binchao, Wang Tianzhi, and Li Feng

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