We may earn an affiliate commission when you visit our partners.
Course image
Michel Bierlaire

Introduction to the mathematical concept of networks, and to two important optimization problems on networks: the transshipment problem and the shortest path problem. Short introduction to the modeling power of discrete optimization, with reference to classical problems. Introduction to the branch and bound algorithm, and the concept of cuts.

Three deals to help you save

What's inside

Learning objectives

  • Networks: you will be introduced to the mathematical formalism of graphs and networks.
  • Transhipment: you will learn about the transhipment problem (also called "minimum cost flow problem"), its properties, and some special instances.
  • Shortest path: you will learn about algorithms to find the shortest path in a network.
  • Discrete optimization: you will learn how to specify a discrete optimization problem.
  • Exact methods for discrete optimization: you will be introduced to two algorithms to solve discrete optimization problems.
  • The course is structured into 5 sections.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Develops skills and knowledge in network modeling, helpful for studying communication and transportation networks
Taught by experienced instructor Michel Bierlaire, recognized for their work in network optimization
Examines core techniques in discrete optimization, such as branch and bound and cuts
Introduces the concept of networks and their applications in real-world scenarios
Provides a comprehensive overview of transhipment and shortest path problems, fundamental in network analysis
Requires a background in mathematics and computing, suitable for students with a strong quantitative foundation

Save this course

Save Optimization: principles and algorithms - Network and discrete optimization to your list so you can find it easily later:
Save

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 Optimization: principles and algorithms - Network and discrete optimization with these activities:
Review Network Fundamentals
Review basic network concepts and terminology to strengthen your foundation.
Show steps
  • Read textbooks or online articles covering fundamental network concepts.
  • Review your notes or past coursework on network fundamentals.
Organize and Review Course Materials
To ensure a strong foundation, systematically organize your lecture notes, assignments, and other course materials for easy access and review.
Show steps
  • Gather all your relevant course materials.
  • Create a logical system to organize the materials.
Solve Network Optimization Problems
Engage in solving practice problems to improve your understanding and problem-solving skills.
Browse courses on Network Optimization
Show steps
  • Find online resources or textbooks with practice problems on network optimization.
  • Attempt to solve the problems independently.
Two other activities
Expand to see all activities and additional details
Show all five activities
Explore Branch and Bound Algorithm
Follow online tutorials or videos to gain a deeper understanding of the concepts and implementation of the branch and bound algorithm.
Browse courses on Branch and Bound
Show steps
  • Identify online tutorials or videos that provide clear explanations.
  • Follow the tutorials and try to implement the algorithm yourself.
Develop a Network Modeling Tool
Create a software tool or script that can perform network modeling tasks, solidifying your knowledge through practical application.
Show steps
  • Identify a specific network modeling task to work on.
  • Design and implement the software tool or script.

Career center

Learners who complete Optimization: principles and algorithms - Network and discrete optimization will develop knowledge and skills that may be useful to these careers:
Operations Research Analyst
Operations Research Analysts use mathematical and analytical techniques to solve problems in a wide variety of industries. They use their knowledge of networks and optimization to develop solutions that improve the efficiency and effectiveness of operations. This course provides a strong foundation in the mathematical concepts of networks and optimization, which are essential for success in this field. You will learn about the transhipment problem, the shortest path problem, and other important optimization problems on networks. You will also learn about discrete optimization, which is used to solve a wide variety of problems in operations research.
Logistics Manager
Logistics Managers are responsible for planning, implementing, and controlling the movement of goods and services. They use their knowledge of networks and optimization to develop efficient and cost-effective logistics solutions. This course provides a strong foundation in the mathematical concepts of networks and optimization, which are essential for success in this field. You will learn about the transhipment problem, the shortest path problem, and other important optimization problems on networks. You will also learn about discrete optimization, which is used to solve a wide variety of problems in logistics management.
Transportation Analyst
Transportation Analysts play a vital role in the planning, design, and operation of transportation systems. They use their knowledge of networks and optimization to develop solutions that improve the efficiency and effectiveness of transportation systems. This course provides a strong foundation in the mathematical concepts of networks and optimization, which are essential for success in this field. You will learn about the transhipment problem, the shortest path problem, and other important optimization problems on networks. You will also learn about discrete optimization, which is used to solve a wide variety of problems in transportation planning and management.
Statistician
Statisticians use their knowledge of networks and optimization to analyze data. They use mathematical and analytical techniques to develop models that can predict the future and make informed decisions. This course provides a strong foundation in the mathematical concepts of networks and optimization, which are essential for success in this field. You will learn about the transhipment problem, the shortest path problem, and other important optimization problems on networks. You will also learn about discrete optimization, which is used to solve a wide variety of problems in statistics.
Software Engineer
Software Engineers design, develop, and maintain software systems. They use their knowledge of networks and optimization to develop efficient and scalable software solutions. This course provides a strong foundation in the mathematical concepts of networks and optimization, which are essential for success in this field. You will learn about the transhipment problem, the shortest path problem, and other important optimization problems on networks. You will also learn about discrete optimization, which is used to solve a wide variety of problems in software engineering.
Data Analyst
Data Analysts use their knowledge of networks and optimization to extract insights from data. They use mathematical and analytical techniques to develop algorithms that can solve complex problems in a variety of industries. This course provides a strong foundation in the mathematical concepts of networks and optimization, which are essential for success in this field. You will learn about the transhipment problem, the shortest path problem, and other important optimization problems on networks. You will also learn about discrete optimization, which is used to solve a wide variety of problems in data analysis.
Management Consultant
Management Consultants use their knowledge of networks and optimization to help businesses improve their operations. They use mathematical and analytical techniques to identify and solve problems that are costing businesses money. This course provides a strong foundation in the mathematical concepts of networks and optimization, which are essential for success in this field. You will learn about the transhipment problem, the shortest path problem, and other important optimization problems on networks. You will also learn about discrete optimization, which is used to solve a wide variety of problems in management consulting.
Risk Analyst
Risk Analysts use mathematical and statistical techniques to assess and manage risk. They use their knowledge of networks and optimization to develop models that can predict the likelihood and severity of risks. This course provides a strong foundation in the mathematical concepts of networks and optimization, which are essential for success in this field. You will learn about the transhipment problem, the shortest path problem, and other important optimization problems on networks. You will also learn about discrete optimization, which is used to solve a wide variety of problems in risk analysis.
Quantitative Analyst
Quantitative Analysts use mathematical and statistical techniques to analyze financial data. They use their knowledge of networks and optimization to develop models that can predict the performance of financial assets. This course provides a strong foundation in the mathematical concepts of networks and optimization, which are essential for success in this field. You will learn about the transhipment problem, the shortest path problem, and other important optimization problems on networks. You will also learn about discrete optimization, which is used to solve a wide variety of problems in quantitative finance.
Economist
Economists use their knowledge of networks and optimization to analyze economic data. They use mathematical and analytical techniques to develop models that can predict the future and make informed decisions. This course provides a strong foundation in the mathematical concepts of networks and optimization, which are essential for success in this field. You will learn about the transhipment problem, the shortest path problem, and other important optimization problems on networks. You will also learn about discrete optimization, which is used to solve a wide variety of problems in economics.
Systems Analyst
Systems Analysts use their knowledge of networks and optimization to design and implement computer systems. They use mathematical and analytical techniques to ensure that systems are efficient and effective. This course provides a strong foundation in the mathematical concepts of networks and optimization, which are essential for success in this field. You will learn about the transhipment problem, the shortest path problem, and other important optimization problems on networks. You will also learn about discrete optimization, which is used to solve a wide variety of problems in systems analysis.
Computer Programmer
Computer Programmers use their knowledge of networks and optimization to develop software systems. They use mathematical and analytical techniques to ensure that software is efficient and effective. This course provides a strong foundation in the mathematical concepts of networks and optimization, which are essential for success in this field. You will learn about the transhipment problem, the shortest path problem, and other important optimization problems on networks. You will also learn about discrete optimization, which is used to solve a wide variety of problems in computer programming.
Financial Analyst
Financial Analysts use mathematical and statistical techniques to analyze financial data. They use their knowledge of networks and optimization to develop models that can predict the performance of financial assets. This course provides a strong foundation in the mathematical concepts of networks and optimization, which are essential for success in this field. You will learn about the transhipment problem, the shortest path problem, and other important optimization problems on networks. You will also learn about discrete optimization, which is used to solve a wide variety of problems in financial analysis.
Data Scientist
Data Scientists use mathematical and statistical techniques to extract insights from data. They use their knowledge of networks and optimization to develop algorithms that can solve complex problems in a variety of industries. This course provides a strong foundation in the mathematical concepts of networks and optimization, which are essential for success in this field. You will learn about the transhipment problem, the shortest path problem, and other important optimization problems on networks. You will also learn about discrete optimization, which is used to solve a wide variety of problems in data science.
Business Analyst
Business Analysts use their knowledge of networks and optimization to help businesses improve their operations. They use mathematical and analytical techniques to identify and solve problems that are costing businesses money. This course provides a strong foundation in the mathematical concepts of networks and optimization, which are essential for success in this field. You will learn about the transhipment problem, the shortest path problem, and other important optimization problems on networks. You will also learn about discrete optimization, which is used to solve a wide variety of problems in business analysis.

Reading list

We've selected 15 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 Optimization: principles and algorithms - Network and discrete optimization.
This well-regarded textbook comprehensively covers graph theory, network optimization, and the algorithms used to solve network optimization problems. It includes chapters on topics such as the transshipment problem, the shortest path problem, and network flows, which would provide valuable background and depth to this course.
This introductory textbook on graph theory provides a strong foundation for understanding networks and their applications. It includes chapters on graph algorithms, network flows, and shortest paths, which would be useful for learners who want to build a strong understanding of the mathematical concepts underlying this course.
While this book focuses on linear programming, it includes a chapter on network flows and provides a good introduction to the topic. It would be a valuable resource for learners who want to explore the connections between linear programming and network optimization.
This classic textbook on combinatorial optimization provides a comprehensive overview of the field. It includes chapters on network flows, shortest paths, and branch and bound algorithms, which would be valuable for learners interested in a more theoretical treatment of these topics.
Provides a unique perspective on optimization by using vector space methods. It includes chapters on network flows and shortest paths, which would be useful for learners who want to explore alternative approaches to solving these problems.
This popular textbook provides a broad overview of operations research, including chapters on network optimization, linear programming, and discrete optimization. It would be a useful reference for learners who want to gain a general understanding of these topics.
This textbook focuses on optimization algorithms, including branch and bound algorithms and network optimization algorithms. It would be valuable for learners who want to learn more about the algorithms used to solve these problems.
This advanced textbook provides a comprehensive treatment of integer programming, which is closely related to discrete optimization. It would be valuable for learners who want to explore this topic in more depth.
Provides a modern treatment of convex optimization, which is related to network optimization. It would be valuable for learners who want to explore this topic in more depth.
Provides a comprehensive overview of graph algorithms, including algorithms for finding shortest paths and network flows. It would be a valuable resource for learners who want to learn more about these algorithms.
Provides a comprehensive treatment of network optimization, covering both theoretical and practical aspects. It would be a valuable reference for learners who want to gain a deep understanding of this topic.
Provides a foundation in discrete mathematics, including topics such as graph theory and logic. It would be a useful resource for learners who need to strengthen their background in these areas.
Provides a comprehensive overview of algorithms and data structures, including algorithms for solving network optimization problems. It would be a useful resource for learners who want to learn more about the algorithms used in this field.
Provides a foundation in linear algebra, which is useful for understanding the mathematical concepts underlying network optimization. It would be a useful resource for learners who need to strengthen their background in this area.
Provides a foundation in calculus, which is useful for understanding the mathematical concepts underlying network optimization. It would be a useful resource for learners who need to strengthen their background in this area.

Share

Help others find this course page by sharing it with your friends and followers:

Similar courses

Here are nine courses similar to Optimization: principles and algorithms - Network and discrete optimization.
Discrete Optimization
Most relevant
Advanced Modeling for Discrete Optimization
Most relevant
Solving Algorithms for Discrete Optimization
Most relevant
Understanding and Applying Numerical Optimization...
Most relevant
Mathematical Optimization for Engineers
Most relevant
Optimization with GAMS: Operations Research Bootcamp A-Z
Introduction to Radio Network Optimization
Optimization: principles and algorithms - Linear...
Optimization with Python: Solve Operations Research...
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 - 2024 OpenCourser