We may earn an affiliate commission when you visit our partners.
孔令傑 (Ling-Chieh Kung)
Operations Research (OR) is a field in which people use mathematical and engineering methods to study optimization problems in Business and Management, Economics, Computer Science, Civil Engineering, Electrical Engineering, etc.
The series of courses consists of three parts, we focus on deterministic optimization techniques, which is a major part of the field of OR.
Read more
Operations Research (OR) is a field in which people use mathematical and engineering methods to study optimization problems in Business and Management, Economics, Computer Science, Civil Engineering, Electrical Engineering, etc.
The series of courses consists of three parts, we focus on deterministic optimization techniques, which is a major part of the field of OR.
Read more
Operations Research (OR) is a field in which people use mathematical and engineering methods to study optimization problems in Business and Management, Economics, Computer Science, Civil Engineering, Electrical Engineering, etc.
The series of courses consists of three parts, we focus on deterministic optimization techniques, which is a major part of the field of OR.
As the third part of the series, we study mathematical properties of linear programs, integer programs, and nonlinear programs. We also introduce applications of these theoretical properties: How they help us develop better ways to solve mathematical programs.
Register for this course and see more details by visiting:
OpenCourser.com/course/u1cku7/operations
Two deals to help you save
Save money when you learn. Here are two deals and offers that may be relevant to this course.
All coupon codes, vouchers, and discounts are applied automatically unless otherwise noted.
Valid until July 14
Coursera Plus Annual
Work toward what's next for your career with access to 10,000+ programs. Discover emerging skills and save.
Up to
40%
off
Get offer
Valid until August 30
Google AI App Builder
Learn how to use Gemini API and API Studio with a three-course series from Google DeepMind
Take
100%
off
Get offer
What's inside
Syllabus
Course Overview
In the first lecture, after introducing the course and the importance of mathematical properties, we study the matrix way to run the simplex method. Being more familiar with matrices will help us understand further lectures.
Read more
Syllabus
Course Overview
In the first lecture, after introducing the course and the importance of mathematical properties, we study the matrix way to run the simplex method. Being more familiar with matrices will help us understand further lectures.
Read more
Traffic lights
Traffic lights
Read about what's good
what should give you pause and
possible dealbreakers
Involves advanced mathematical concepts
Provides a strong foundation for those interested in deterministic optimization
Covers diverse applications, including network flow, transportation, and resource allocation
Taught by an experienced instructor with expertise in optimization
Requires a background in linear algebra and calculus
Save this course
Create your own learning path.
Save this course to your list so you can find it easily later.
Save
Save
Reviews summary
Rigorous operations research theory
According to students, this course offers a rigorous and in-depth exploration of Operations Research theory, particularly focusing on mathematical properties of optimization problems. Learners praise the clarity of the lectures and the instructor's ability to explain complex mathematical proofs. While providing a strong theoretical foundation, especially beneficial for advanced studies in areas like machine learning, some found the pacing challenging, often requiring a solid prerequisite in linear algebra and calculus. The inclusion of practical case studies helps bridge the gap between abstract concepts and real-world applications.
Explanations are clear but content density is high.
"The instructor's explanations of complex proofs were remarkably clear and digestible."
"The lectures cover a lot of ground quickly; be prepared to pause and re-watch sections."
"I had to commit significant time to absorb all the mathematical details presented each week."
Connects abstract mathematical theory to real-world applications.
"I appreciated how the case studies effectively linked the theory to real-world problems like SVM."
"Understanding the duality perspective for machine learning models was a major highlight for me."
"The course shows how theoretical properties lead to developing better solution methods."
Provides a rigorous foundation in OR theory.
"I gained a profound understanding of optimization principles and their underlying math."
"The course rigorously covers complex topics like duality, Lagrangian relaxation, and KKT conditions."
"This course really solidified my mathematical understanding of core OR concepts, beyond just applications."
Requires a solid background in advanced mathematics.
"You absolutely need strong linear algebra and multivariate calculus skills for this course."
"I found myself revisiting foundational math concepts frequently to keep up with the proofs."
"Best suited for those with prior exposure to basic Operations Research or similar quantitative fields."
Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Operations Research (3): Theory with these
activities:
Gather and Organize Course Materials
Show steps
Enhance organization and recall by compiling and reviewing course materials.
Show steps
-
Gather lecture notes, assignments, and other relevant materials.
-
Organize materials into a logical structure, such as by topic or date.
-
Review materials regularly to reinforce concepts.
📘 Read 'Introduction to Operations Research' by Frederick S. Hillier and Gerald J. Lieberman
Show steps
Establish a foundational understanding of OR concepts by reading a classic textbook in the field.
View
ISE Introduction to Operations Research
on Amazon
Show steps
-
Review chapters 1-5 to understand the basics of OR and linear programming.
-
Focus on chapters 6-10 for integer programming, network flow, and nonlinear programming.
Follow Tutorials on OR Techniques
Show steps
Supplement course materials by exploring online tutorials and resources to reinforce concepts.
Browse courses on
Linear Programming
Show steps
-
Search for tutorials on specific OR topics you want to strengthen.
-
Follow step-by-step instructions and work through examples.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Join a Study Group or Discussion Forum
Show steps
Collaborate with peers to clarify concepts, solve problems, and share insights.
Show steps
-
Join or create a study group with other students in the course.
-
Meet regularly to discuss course material, work on problems together, and quiz each other.
Solve OR Problems on LeetCode
Show steps
Develop problem-solving skills by working through curated OR problems on LeetCode.
Browse courses on
Linear Programming
Show steps
-
Create a LeetCode account and set a goal to solve 10-15 OR-related problems.
-
Focus on problems tagged with 'linear programming', 'integer programming', or 'network flow'.
-
Analyze solutions provided by others to enhance your understanding.
Apply OR Techniques in Practice
Show steps
Reinforce concepts by finding a practical OR problem and applying the techniques covered in the course to develop a solution.
Browse courses on
Linear Programming
Show steps
-
Define the business problem and the constraints involved.
-
Formulate an OR model to represent the problem.
-
Solve the OR model using appropriate software or techniques.
-
Analyze the solution and interpret the results.
-
Implement the solution in practice (optional).
Create OR-Based Visualizations
Show steps
Enhance understanding by visualizing OR concepts and applying them to real-world scenarios.
Browse courses on
Linear Programming
Show steps
-
Choose a topic such as linear programming or integer programming.
-
Create visualizations using tools like Tableau or Python to illustrate concepts and solve problems.
-
Share your visualizations with others for feedback and discussion.
Develop an OR-Based Decision Support Tool
Show steps
Apply your knowledge by creating a practical tool that solves optimization problems in a business or industry context.
Browse courses on
Linear Programming
Show steps
-
Identify a decision-making problem that can be solved using OR techniques.
-
Develop an OR model to represent the problem and solve it using appropriate methods.
-
Create a user-friendly tool that enables non-experts to use the OR model.
Gather and Organize Course Materials
Show steps
Enhance organization and recall by compiling and reviewing course materials.
Show steps
Show steps
Show steps
- Gather lecture notes, assignments, and other relevant materials.
- Organize materials into a logical structure, such as by topic or date.
- Review materials regularly to reinforce concepts.
📘 Read 'Introduction to Operations Research' by Frederick S. Hillier and Gerald J. Lieberman
Show steps
Establish a foundational understanding of OR concepts by reading a classic textbook in the field.
View
ISE Introduction to Operations Research
on Amazon
Show steps
Show steps
Show steps
- Review chapters 1-5 to understand the basics of OR and linear programming.
- Focus on chapters 6-10 for integer programming, network flow, and nonlinear programming.
Follow Tutorials on OR Techniques
Show steps
Supplement course materials by exploring online tutorials and resources to reinforce concepts.
Browse courses on
Linear Programming
Show steps
Show steps
Show steps
- Search for tutorials on specific OR topics you want to strengthen.
- Follow step-by-step instructions and work through examples.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Join a Study Group or Discussion Forum
Show steps
Collaborate with peers to clarify concepts, solve problems, and share insights.
Show steps
Show steps
Show steps
- Join or create a study group with other students in the course.
- Meet regularly to discuss course material, work on problems together, and quiz each other.
Solve OR Problems on LeetCode
Show steps
Develop problem-solving skills by working through curated OR problems on LeetCode.
Browse courses on
Linear Programming
Show steps
Show steps
Show steps
- Create a LeetCode account and set a goal to solve 10-15 OR-related problems.
- Focus on problems tagged with 'linear programming', 'integer programming', or 'network flow'.
- Analyze solutions provided by others to enhance your understanding.
Apply OR Techniques in Practice
Show steps
Reinforce concepts by finding a practical OR problem and applying the techniques covered in the course to develop a solution.
Browse courses on
Linear Programming
Show steps
Show steps
Show steps
- Define the business problem and the constraints involved.
- Formulate an OR model to represent the problem.
- Solve the OR model using appropriate software or techniques.
- Analyze the solution and interpret the results.
- Implement the solution in practice (optional).
Create OR-Based Visualizations
Show steps
Enhance understanding by visualizing OR concepts and applying them to real-world scenarios.
Browse courses on
Linear Programming
Show steps
Show steps
Show steps
- Choose a topic such as linear programming or integer programming.
- Create visualizations using tools like Tableau or Python to illustrate concepts and solve problems.
- Share your visualizations with others for feedback and discussion.
Develop an OR-Based Decision Support Tool
Show steps
Apply your knowledge by creating a practical tool that solves optimization problems in a business or industry context.
Browse courses on
Linear Programming
Show steps
Show steps
Show steps
- Identify a decision-making problem that can be solved using OR techniques.
- Develop an OR model to represent the problem and solve it using appropriate methods.
- Create a user-friendly tool that enables non-experts to use the OR model.
Career center
Learners who complete Operations Research (3): Theory will develop knowledge and skills
that may be useful to these careers:
Mathematician
Mathematician
Mathematicians use mathematical techniques to solve problems in a variety of fields, including science, engineering, and business. They use techniques such as linear programming, integer programming, and simulation to develop and evaluate mathematical models. This course provides a strong foundation in the mathematical techniques that are essential for success in the mathematics field.
Operations Research Analyst
Operations Research Analyst
Operations research analysts use mathematical and analytical techniques to solve problems in a variety of industries, including manufacturing, transportation, logistics, and healthcare. They use techniques such as linear programming, integer programming, and simulation to develop and evaluate solutions to problems such as optimizing production schedules, routing vehicles, and managing inventory levels. This course provides a strong foundation in the mathematical and analytical techniques that are essential for success in the operations research field.
Actuary
Actuary
Actuaries analyze the financial consequences of risk and uncertainty. They use mathematical and statistical models to assess the probability and impact of future events, such as death, disability, or property damage. Actuaries play a vital role in the insurance industry, helping insurers to develop products and set prices that are fair to both the insurer and the policyholder. This course provides a strong foundation in the mathematical and statistical principles that are essential for success in the actuarial field. Topics covered in this course include probability, statistics, linear programming, and optimization.
Data Scientist
Data Scientist
Data scientists use mathematical and statistical techniques to analyze data and extract insights that can be used to make better decisions. They use techniques such as linear programming, integer programming, and machine learning to develop and evaluate models that can predict future events or identify trends. This course provides a strong foundation in the mathematical and statistical techniques that are essential for success in the data science field.
Quantitative Trader
Quantitative Trader
Quantitative traders use mathematical and statistical models to trade financial instruments. They use techniques such as linear programming, integer programming, and machine learning to develop and evaluate trading strategies. This course provides a strong foundation in the mathematical and statistical techniques that are essential for success in the quantitative trading field.
Statistician
Statistician
Statisticians use mathematical and statistical techniques to collect, analyze, and interpret data. They use techniques such as linear programming, integer programming, and machine learning to develop and evaluate statistical models. This course provides a strong foundation in the mathematical and statistical techniques that are essential for success in the statistics field.
Economist
Economist
Economists use mathematical and statistical techniques to analyze economic data and make predictions about the economy. They use techniques such as linear programming, integer programming, and simulation to develop and evaluate economic models. This course provides a strong foundation in the mathematical and statistical techniques that are essential for success in the economics field.
Risk Manager
Risk Manager
Risk managers use mathematical and analytical techniques to identify and manage risks. They use techniques such as linear programming, integer programming, and simulation to develop and evaluate risk management strategies. This course provides a strong foundation in the mathematical and analytical techniques that are essential for success in the risk management field.
Financial Analyst
Financial Analyst
Financial analysts use mathematical and statistical models to analyze financial data and make investment recommendations. They use techniques such as linear programming, integer programming, and simulation to develop and evaluate investment strategies. This course provides a strong foundation in the mathematical and statistical techniques that are essential for success in the financial analysis field.
Management Consultant
Management Consultant
Management consultants use mathematical and analytical techniques to solve problems and improve performance in organizations. They use techniques such as linear programming, integer programming, and simulation to develop and evaluate solutions to problems such as optimizing production schedules, routing vehicles, and managing inventory levels. This course provides a strong foundation in the mathematical and analytical techniques that are essential for success in the management consulting field.
Business Analyst
Business Analyst
Business analysts use mathematical and analytical techniques to analyze business problems and identify solutions. They use techniques such as linear programming, integer programming, and simulation to develop and evaluate solutions to problems such as optimizing production schedules, routing vehicles, and managing inventory levels. This course provides a strong foundation in the mathematical and analytical techniques that are essential for success in the business analysis field.
Industrial Engineer
Industrial Engineer
Industrial engineers use mathematical and analytical techniques to improve the efficiency and effectiveness of industrial processes. They use techniques such as linear programming, integer programming, and simulation to develop and evaluate solutions to problems such as optimizing production schedules, routing vehicles, and managing inventory levels. This course provides a strong foundation in the mathematical and analytical techniques that are essential for success in the industrial engineering field.
Systems Analyst
Systems Analyst
Systems analysts design, develop, and implement computer systems. They use mathematical and analytical techniques to solve problems and develop efficient and reliable systems. This course provides a strong foundation in the mathematical and analytical techniques that are essential for success in the systems analysis field.
Operations Manager
Operations Manager
Operations managers plan, direct, and coordinate the activities of an organization's operations. They use mathematical and analytical techniques to solve problems and improve performance. This course provides a strong foundation in the mathematical and analytical techniques that are essential for success in the operations management field.
Software Engineer
Software Engineer
Software engineers design, develop, and maintain software systems. They use mathematical and analytical techniques to solve problems and develop efficient and reliable software. This course provides a strong foundation in the mathematical and analytical techniques that are essential for success in the software engineering field.
For more career information including salaries, visit:
OpenCourser.com/course/u1cku7/operations
Reading list
We've selected 12 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Operations Research (3): Theory.
Provides a comprehensive overview of operations research techniques, including linear programming, integer programming, and nonlinear programming.
Provides a comprehensive overview of operations research techniques, including linear programming, integer programming, and nonlinear programming.
Reference book on convex optimization, and it is known for its clear and concise writing style.
This reference book is known for its comprehensive treatment of integer programming and its focus on practical applications.
Save
This textbook on linear optimization provides a balanced mix of theoretical foundations and practical algorithms.
Provides a rigorous introduction to linear optimization, including the simplex method and duality theory.
Save
Practical guide to nonlinear optimization and includes a wide range of algorithms and software.
Provides a comprehensive overview of nonlinear programming techniques, including unconstrained optimization, constrained optimization, and global optimization.
Provides a comprehensive overview of linear programming and network flow techniques, including the simplex method, duality theory, and network flow algorithms.
Provides a comprehensive overview of nonlinear optimization techniques, including unconstrained optimization, constrained optimization, and global optimization.
Save
Covers a wide range of operations research topics with a strong emphasis on applications.
Provides a comprehensive overview of convex optimization techniques, including the theory of convex sets, duality theory, and applications to engineering and machine learning.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/u1cku7/operations
Share
Similar courses
Similar courses are unavailable at this time. Please try again later.
Rating
4.9
Effort
14 hours to complete
Level
Advanced
Via
Coursera
Institution
National Taiwan University
Instructor
孔令傑 (Ling-Chieh Kung)
Language
English
Transcripts
Español
Français
Português
Deutsch
Italiano
中文
العربية
한국어
日本語
हिंदी
Nederlands
Svenska
Pусский
Türkçe
Polski
Ελληνικά
українська мова
Bahasa Indonesia
ไทย
қазақша
Our mission
OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.
Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.
Find this site helpful? Tell a friend about us.
Affiliate disclosure
We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.
Your purchases help us maintain our catalog and keep our servers humming without ads.
Thank you for supporting OpenCourser.
© 2016 - 2025 OpenCourser