Powered by
Completion
CERTIFICATE
Operations Research (2): Optimization Algorithms
Master advanced algorithms for linear, integer, and nonlinear optimization problems in operations research.
Course Cost
₹ 2,435
Intermediate
Skill Level
12 Hours
Self-paced Video lessons
This intermediate-level course focuses on efficient algorithms for solving various optimization problems in operations research. Students will learn advanced techniques such as the simplex method, branch-and-bound algorithm, gradient descent, and Newton's method. The course covers practical implementation using Gurobi solver with Python. Through lectures, quizzes, and case studies, learners will develop skills to solve complex optimization problems in business, economics, and engineering contexts.
4.9
16,406 Enrolled
English
What you'll learn
Master the simplex method for solving linear programming problems
Implement the branch-and-bound algorithm for integer programming
Apply gradient descent and Newton's method to nonlinear optimization
Use Gurobi solver with Python to implement optimization algorithms
Analyze and evaluate algorithm performance
Design heuristic algorithms for complex optimization problems
Solve real-world case studies using advanced optimization techniques
Understand the theoretical foundations of optimization algorithms
Skills you'll gain
This course includes:
9.62 Hours PreRecorded video
6 assignments
Access on Mobile, Tablet, Desktop
FullTime access
Shareable certificate
Get a Completion Certificate
Share your certificate with prospective employers and your professional network on LinkedIn.
CREATED BY
PROVIDED BY
Get a Completion Certificate
Share your certificate with prospective employers and your professional network on LinkedIn.
CREATED BY
PROVIDED BY
Top companies offer this course to their employees
Top companies provide this course to enhance their employees' skills, ensuring they excel in handling complex projects and drive organizational success.
There are 6 modules in this course
This advanced course in Operations Research focuses on optimization algorithms for solving linear, integer, and nonlinear programming problems. The curriculum begins with a review of linear algebra concepts before delving into the simplex method for linear programming. Students then explore the branch-and-bound algorithm for integer programming, followed by gradient descent and Newton's method for nonlinear optimization. The course emphasizes practical application, teaching students to implement these algorithms using the Gurobi solver with Python. A case study on facility location problem demonstrates the real-world application of these techniques. Throughout the course, learners develop skills in algorithm design, implementation, and performance evaluation, preparing them for advanced optimization challenges in various industries.
Course Overview
Module 1 · 1 Hours to complete
The Simplex Method
Module 2 · 3 Hours to complete
The Branch-and-Bound Algorithm
Module 3 · 2 Hours to complete
Gradient Descent and Newton's Method
Module 4 · 2 Hours to complete
Design and Evaluation of Heuristic Algorithms
Module 5 · 1 Hours to complete
Course Summary and Future Learning Directions
Module 6 · 1 Hours to complete
Fee Structure
Payment options
Financial Aid
Reviews
Testimonials and success stories are a testament to the quality of this program and its impact on your career and learning journey. Be the first to help others make an informed decision by sharing your review of the course.
Faculties
These are the expert instructors who will be teaching you throughout the course. With a wealth of knowledge and real-world experience, they're here to guide, inspire, and support you every step of the way. Get to know the people who will help you reach your learning goals and make the most of your journey.
4.8
173
Reviews
94,481
Students
8
Courses
Dr. Chih-Kang Chiang is an expert in internal medicine, nephrology, toxicology, and food safety risk analysis. He received his Ph.D. in 2006 from the Graduate Institute of Toxicology at National Taiwan University. In 2005, he became a clinical lecturer in the Department of Internal Medicine at National Taiwan University and was promoted to clinical assistant professor in 2007 and clinical associate professor in 2012. He has served as an associate professor since 2014 and was promoted to full professor in 2018 at the Graduate Institute of Toxicology, National Taiwan University. A notable scholar in nephrology and toxicology, Dr. Chiang has published over a hundred peer-reviewed articles throughout his career.
Frequently asked Questions
Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.