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Operations Research (2)

Optimization Algorithms

4.8 Filled star Filled star Filled star Filled star Half star
Based on 143 ratings
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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.

As the second part of the series, we study some efficient algorithms for solving linear programs, integer programs, and nonlinear programs.

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 second part of the series, we study some efficient algorithms for solving linear programs, integer programs, and nonlinear programs.

We also introduce the basic computer implementation of solving different programs, integer programs, and nonlinear programs and thus an example of algorithm application will be discussed.

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What's inside

Syllabus

Course Overview
In the first lecture, we briefly introduce the course and give a quick review about some basic knowledge of linear algebra, including Gaussian elimination, Gauss-Jordan elimination, and definition of linear independence.
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Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Teaches tools and techniques that are indispensable in business, management, economics, and technology
Provides a comprehensive overview of deterministic optimization techniques within operations research
Involves computer implementation of algorithms, providing practical experience
Involves real-world case studies, connecting theories to practical applications
Introduces essential optimization algorithms like the Simplex Method, Branch-and-Bound, and Gradient Descent
Covers nonlinear programming, extending the scope of optimization techniques

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Reviews summary

In-depth optimization algorithms for professionals

According to students, this course offers a deep dive into optimization algorithms, particularly praised for its coverage of the Simplex Method, Branch-and-Bound, and Gradient Descent. Learners found the lectures well-structured, providing a solid theoretical foundation combined with practical applications, including a notable NEC Taiwan case study. While many found the course highly rewarding and essential for data science or operations, a significant number of reviews highlight its challenging nature, stressing that it requires a strong mathematical background, especially in linear algebra and calculus. Some found the pace very fast and felt certain sections were rushed, potentially leading to difficulty for beginners or those without adequate prerequisites. Quizzes and coding examples also received mixed feedback.
Good blend of theoretical concepts and practical case studies.
"I appreciated the focus on both theory and implementation. The practical application with the NEC Taiwan case study was insightful."
"I loved the hands-on coding aspect and how the instructors broke down complex concepts."
"The basic computer implementation of solving different programs... was helpful."
"The practical applications, even if short, were a nice touch."
Lectures are well-structured, building a solid foundational understanding.
"The lectures were well-structured, and the practical application with the NEC Taiwan case study was insightful."
"It builds a solid foundation for advanced topics."
"I appreciated the attention to detail in the Simplex method module, it was particularly strong."
"Good continuation from OR (1). The algorithms covered are relevant."
Excellent, in-depth coverage of key optimization algorithms.
"This course significantly deepened my understanding of optimization algorithms, especially the Branch-and-Bound method."
"The detailed explanation of Simplex, Gradient Descent, and Newton's method was top-notch."
"A fantastic deep dive into optimization. The mathematical rigor is perfect..."
"The course covers important topics... I liked the structure, moving from linear to integer to nonlinear."
Mixed feedback on how well quizzes and assignments align with lectures.
"The quizzes also felt disconnected from the lecture material at times."
"The problem sets were challenging but fair."
"I think the quizzes could be more indicative of what's taught in the lectures."
"The assignments were almost impossible for me without external resources."
Some sections felt rushed or lacked clear explanations.
"Some sections felt a bit rushed, especially the linear algebra review."
"Disappointed with the lack of clarity in certain sections. The instructor often jumped between concepts without adequate transitions."
"Sometimes the explanations felt abstract without enough concrete examples."
"I found myself re-watching lectures multiple times to grasp the concepts."
Course demands strong mathematical background, not for beginners.
"As someone without a strong math background, I found this course incredibly difficult."
"This course is not for beginners. The prerequisites are understated. I wish they had a stronger warning about the required math background."
"Highly recommend for those with a solid foundation in linear algebra and calculus."
"It definitely requires prior mathematical understanding."

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 (2): Optimization Algorithms with these activities:
OR Industry Meetup
Networking with professionals in the field can provide insights into career opportunities and industry trends.
Show steps
  • Research and identify an industry meetup related to OR.
  • Prepare an elevator pitch and some questions to ask other attendees.
  • Attend the meetup and actively engage in conversations.
Linear Algebra Practice
Reviewing key concepts from linear algebra helps you to build a strong foundation for operations research.
Browse courses on Linear Algebra
Show steps
  • Solve systems of linear equations using Gaussian elimination or Gauss-Jordan elimination.
  • Calculate nullspaces and column spaces of matrices
  • Determine if a set of vectors is linearly independent or dependent.
Introduction to Operations Research
This book can offer a comprehensive overview of Operations Research, covering fundamental concepts and techniques that are essential for the course.
View ISE Introduction to Operations Research on Amazon
Show steps
  • Read the chapters on linear programming, integer programming, and nonlinear programming.
  • Solve the practice problems at the end of each chapter.
Three other activities
Expand to see all activities and additional details
Show all six activities
Gradient Descent Tutorial
This tutorial can provide a clear and structured approach to understanding the concepts behind gradient descent.
Browse courses on Gradient Descent
Show steps
  • Review the basics of derivatives and partial derivatives.
  • Learn how to calculate the gradient of a function.
  • Apply gradient descent to optimize a simple function.
Operations Research Workshop
Attending a workshop can provide valuable hands-on experience and allow you to learn from experts in the field.
Browse courses on Operations Research
Show steps
  • Research and identify a relevant workshop.
  • Register for the workshop and prepare any necessary materials.
  • Attend the workshop and actively participate in discussions and exercises.
Develop a Simulation Model
Building a simulation model allows you to test and evaluate different scenarios and gain insights into complex systems.
Browse courses on Simulation
Show steps
  • Define the system or process to be simulated.
  • Collect and analyze relevant data.
  • Develop a simulation model using an appropriate software tool.
  • Run the simulation and analyze the results.

Career center

Learners who complete Operations Research (2): Optimization Algorithms will develop knowledge and skills that may be useful to these careers:
Quantitative Analyst
Quantitative Analysts (QAs) create and apply mathematical and statistical models to solve problems for financial institutions and other companies. They use their knowledge of mathematics, statistics, and computer programming to analyze data, identify trends, and make predictions. The Operations Research (2): Optimization Algorithms course can help QAs build a foundation in the mathematical and algorithmic techniques used to solve optimization problems. This course covers topics such as linear programming, integer programming, and nonlinear programming, which are all essential for QAs who need to develop and implement optimization models that solve real-world problems facing companies.
See salaries and explore the career path for Quantitative Analyst
Operations Research Analyst
Operations Research Analysts apply mathematical and analytical techniques to improve the efficiency and effectiveness of operations within organizations. They use their knowledge of mathematics, statistics, and computer programming to analyze data, identify problems, and develop solutions. The Operations Research (2): Optimization Algorithms course can help Operations Research Analysts build a foundation in the mathematical and algorithmic techniques used to solve optimization problems. This course covers topics such as linear programming, integer programming, and nonlinear programming, which are all essential for Operations Research Analysts who need to develop and implement optimization models that solve real-world problems facing organizations.
See salaries and explore the career path for Operations Research Analyst
Management Consultant
Management Consultants help organizations improve their performance by providing advice on strategy, operations, and technology. They use their knowledge of business, mathematics, and computer programming to analyze data, identify problems, and develop solutions. The Operations Research (2): Optimization Algorithms course can help Management Consultants build a foundation in the mathematical and algorithmic techniques used to solve optimization problems. This course covers topics such as linear programming, integer programming, and nonlinear programming, which are all essential for Management Consultants who need to develop and implement optimization models that solve real-world problems facing organizations.
See salaries and explore the career path for Management Consultant
Data Scientist
Data Scientists use their knowledge of mathematics, statistics, and computer programming to analyze data, identify trends, and make predictions. They work in a variety of industries, including finance, healthcare, and retail. The Operations Research (2): Optimization Algorithms course can help Data Scientists build a foundation in the mathematical and algorithmic techniques used to solve optimization problems. This course covers topics such as linear programming, integer programming, and nonlinear programming, which are all essential for Data Scientists who need to develop and implement optimization models that solve real-world problems facing organizations.
See salaries and explore the career path for Data Scientist
Financial Analyst
Financial Analysts use their knowledge of mathematics, statistics, and computer programming to analyze financial data and make investment recommendations. They work in a variety of industries, including banking, investment management, and insurance. The Operations Research (2): Optimization Algorithms course can help Financial Analysts build a foundation in the mathematical and algorithmic techniques used to solve optimization problems. This course covers topics such as linear programming, integer programming, and nonlinear programming, which are all essential for Financial Analysts who need to develop and implement optimization models that solve real-world problems facing organizations.
See salaries and explore the career path for Financial Analyst
Actuary
Actuaries use their knowledge of mathematics, statistics, and computer programming to assess and manage risk. They work in a variety of industries, including insurance, pension funds, and healthcare. The Operations Research (2): Optimization Algorithms course can help Actuaries build a foundation in the mathematical and algorithmic techniques used to solve optimization problems. This course covers topics such as linear programming, integer programming, and nonlinear programming, which are all essential for Actuaries who need to develop and implement optimization models that solve real-world problems facing organizations.
See salaries and explore the career path for Actuary
Industrial Engineer
Industrial Engineers use their knowledge of mathematics, statistics, and computer programming to improve the efficiency and effectiveness of industrial processes. They work in a variety of industries, including manufacturing, transportation, and healthcare. The Operations Research (2): Optimization Algorithms course can help Industrial Engineers build a foundation in the mathematical and algorithmic techniques used to solve optimization problems. This course covers topics such as linear programming, integer programming, and nonlinear programming, which are all essential for Industrial Engineers who need to develop and implement optimization models that solve real-world problems facing organizations.
See salaries and explore the career path for Industrial Engineer
Software Engineer
Software Engineers use their knowledge of mathematics, statistics, and computer programming to design, develop, and implement software applications. They work in a variety of industries, including technology, finance, and healthcare. The Operations Research (2): Optimization Algorithms course can help Software Engineers build a foundation in the mathematical and algorithmic techniques used to solve optimization problems. This course covers topics such as linear programming, integer programming, and nonlinear programming, which are all essential for Software Engineers who need to develop and implement optimization models that solve real-world problems facing organizations.
See salaries and explore the career path for Software Engineer
Systems Analyst
Systems Analysts use their knowledge of mathematics, statistics, and computer programming to analyze and design computer systems. They work in a variety of industries, including technology, finance, and healthcare. The Operations Research (2): Optimization Algorithms course can help Systems Analysts build a foundation in the mathematical and algorithmic techniques used to solve optimization problems. This course covers topics such as linear programming, integer programming, and nonlinear programming, which are all essential for Systems Analysts who need to develop and implement optimization models that solve real-world problems facing organizations.
See salaries and explore the career path for Systems Analyst
Operations Manager
Operations Managers use their knowledge of mathematics, statistics, and computer programming to manage the operations of organizations. They work in a variety of industries, including manufacturing, transportation, and healthcare. The Operations Research (2): Optimization Algorithms course can help Operations Managers build a foundation in the mathematical and algorithmic techniques used to solve optimization problems. This course covers topics such as linear programming, integer programming, and nonlinear programming, which are all essential for Operations Managers who need to develop and implement optimization models that solve real-world problems facing organizations.
See salaries and explore the career path for Operations Manager
Business Analyst
Business Analysts use their knowledge of mathematics, statistics, and computer programming to analyze business processes and identify opportunities for improvement. They work in a variety of industries, including technology, finance, and healthcare. The Operations Research (2): Optimization Algorithms course can help Business Analysts build a foundation in the mathematical and algorithmic techniques used to solve optimization problems. This course covers topics such as linear programming, integer programming, and nonlinear programming, which are all essential for Business Analysts who need to develop and implement optimization models that solve real-world problems facing organizations.
See salaries and explore the career path for Business Analyst
Statistician
Statisticians use their knowledge of mathematics, statistics, and computer programming to collect, analyze, and interpret data. They work in a variety of industries, including technology, finance, and healthcare. The Operations Research (2): Optimization Algorithms course can help Statisticians build a foundation in the mathematical and algorithmic techniques used to solve optimization problems. This course covers topics such as linear programming, integer programming, and nonlinear programming, which are all essential for Statisticians who need to develop and implement optimization models that solve real-world problems facing organizations.
See salaries and explore the career path for Statistician
Economist
Economists use their knowledge of mathematics, statistics, and computer programming to analyze economic data and make predictions about the economy. They work in a variety of industries, including government, academia, and business. The Operations Research (2): Optimization Algorithms course may be helpful for Economists who need to develop and implement optimization models that solve real-world problems facing organizations.
See salaries and explore the career path for Economist
Market Researcher
Market Researchers use their knowledge of mathematics, statistics, and computer programming to collect and analyze data about consumer behavior. They work in a variety of industries, including technology, finance, and healthcare. The Operations Research (2): Optimization Algorithms course may be helpful for Market Researchers who need to develop and implement optimization models that solve real-world problems facing organizations.
See salaries and explore the career path for Market Researcher
Financial Planner
Financial Planners use their knowledge of mathematics, statistics, and computer programming to help individuals and families plan for their financial future. They work in a variety of industries, including banking, investment management, and insurance. The Operations Research (2): Optimization Algorithms course may be helpful for Financial Planners who need to develop and implement optimization models that solve real-world problems facing organizations.
See salaries and explore the career path for Financial Planner

Reading list

We've selected 14 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 (2): Optimization Algorithms.
Cover image
Linear Programming
Save
Provides a more in-depth look at linear programming, including more advanced topics such as duality and sensitivity analysis. It good resource for students who want to learn more about the theory of linear programming.
Linear Programming: Foundations and Extensions...
Kindle Edition
$$$
Relaxation Methods for Pure and Mixed Integer...
Save
Provides a comprehensive overview of integer programming, including both theoretical and practical aspects. It good resource for students who want to learn more about the theory and practice of integer programming.
Relaxation methods for pure and mixed integer...
Paperback
$$
Cover image
Solutions Manual to accompany Nonlinear Programming
Save
Provides a comprehensive overview of nonlinear programming, including both theoretical and practical aspects. It good resource for students who want to learn more about the theory and practice of nonlinear programming.
Solutions Manual to accompany Nonlinear Programming...
Paperback
$$
Solutions Manual to accompany Nonlinear Programming...
Kindle Edition
$$
Cover image
Maximum-Entropy Sampling
Save
Provides a comprehensive overview of optimization algorithms, including both theoretical and practical aspects. It good resource for students who want to learn more about the theory and practice of optimization algorithms.
Maximum-Entropy Sampling: Algorithms and...
Paperback
$$$$
Cover image
Computational Complexity
Save
Provides a comprehensive overview of discrete optimization, including both theoretical and practical aspects. It good resource for students who want to learn more about the theory and practice of discrete optimization.
Computational Complexity: A Modern Approach
Hardcover
$$$
Computational Complexity: A Modern Approach
Kindle Edition
$$
Cover image
Combinatorial Optimization
Save
Provides a comprehensive overview of combinatorial optimization, including both theoretical and practical aspects. It good resource for students who want to learn more about the theory and practice of combinatorial optimization.
Combinatorial Optimization
Paperback
Check
Combinatorial Optimization
Kindle Edition
Check
Cover image
Introduction to Applied Linear Algebra
Save
Provides a comprehensive overview of convex optimization, including both theoretical and practical aspects. It good resource for students who want to learn more about the theory and practice of convex optimization.
Introduction to Applied Linear Algebra: Vectors,...
Hardcover
$$
Introduction to Applied Linear Algebra: Vectors,...
Kindle Edition
$$
Cover image
Book of Abstracts. Workshop on Simulation and...
Save
Provides a comprehensive overview of stochastic programming, including both theoretical and practical aspects. It good resource for students who want to learn more about the theory and practice of stochastic programming.
Book of Abstracts. Workshop on Simulation and...
Paperback
Check
Book of Abstracts. Workshop on Simulation and...
Kindle Edition
Check
Cover image
Robust Optimization
Save
Provides a comprehensive overview of robust optimization, including both theoretical and practical aspects. It good resource for students who want to learn more about the theory and practice of robust optimization.
Robust Optimization (Princeton Series in Applied...
Hardcover
$$$
Robust Optimization (Princeton Series in Applied...
Kindle Edition
$$$
Cover image
Operations Research: Applications and Algorithms
Save
Provides a comprehensive overview of operations research, with a focus on applications. It good resource for students who want to learn more about how operations research is used in practice.
Operations Research: Applications and Algorithms...
Hardcover
$$$$
Operations Research: Applications and Algorithms
Paperback
$$
Operations research: Applications and algorithms...
Hardcover
$$$
Student Suite CD-ROM for Winston's Operations...
CD-ROM
$$
Operations Research
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Provides a practical introduction to operations research. It good resource for students who want to learn more about how operations research is used in practice.
Operations Research: An Introduction, 10Th Edition
Paperback
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Operations Research: An Introduction
Hardcover
$$$$
Operations Research: An Introduction
Hardcover
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Operations Research An Introduction
Paperback
$$
Operations Research: An Introduction (7th Edition)
Hardcover
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Operations Research
Paperback
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Operation Research (VTU)
Paperback
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Operations Research: An Introduction
Kindle Edition
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Integer Programming: Theory, Applications, and...
Kindle Edition
$$$
Cover image
Student Solutions Manual for Larson/Edwards'...
Save
Provides a comprehensive overview of calculus, including both theoretical and practical aspects. It good resource for students who want to learn more about the theory and practice of calculus.
Student Solutions Manual for Larson/Edwards'...
Paperback
Check
Student Solutions Manual for Larson/Edwards'...
Kindle Edition
Check
Cover image
Student Solutions Manual for...
Save
Provides a comprehensive overview of probability and statistics, including both theoretical and practical aspects. It good resource for students who want to learn more about the theory and practice of probability and statistics.
Student Solutions Manual for...
Paperback
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Student Solutions Manual for...
Kindle Edition
Check
Linear Algebra and Its Applications
Save
Provides a comprehensive overview of linear algebra, including both theoretical and practical aspects. It good resource for students who want to learn more about the theory and practice of linear algebra.
Linear Algebra and Its Applications
Paperback
Check
Linear Algebra and Its Applications
Kindle Edition
Check

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Course image
Rating
4.8 Filled star Filled star Filled star Filled star Half star
Effort
12 hours to complete
Level
Intermediate
Via
Coursera
Institution
National Taiwan University
Instructor
孔令傑 (Ling-Chieh Kung)
Language
English
Transcripts
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Traffic lights
Read about what's good
what should give you pause
and possible dealbreakers
Teaches tools and techniques that are indispensable in business, management, economics, and technology
Provides a comprehensive overview of deterministic optimization techniques within operations research
Involves computer implementation of algorithms, providing practical experience
Involves real-world case studies, connecting theories to practical applications
Introduces essential optimization algorithms like the Simplex Method, Branch-and-Bound, and Gradient Descent
Covers nonlinear programming, extending the scope of optimization techniques
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