Combinatorial Problems and Ant Colony Optimization Algorithm
What you'll learn
- Formulate combinatorial optimization problems
- Solve combinatorial optimization problems
- Develop and use Ant Colony Optimization
- Solve Travelling Salesman Problem
Requirements
- Basics coding skills in Matlab
Description
Search methods and heuristics are of the most fundamental Artificial Intelligence techniques. One of the most well-regarded of them is Ant Colony Optimization that allows humans to solve some of the most challenging problems in history. This course takes you through the details of this algorithm. The course is helpful to learn the following concepts:
Part 1:
1. The main components of the
2. Formulating combinatorial optimization problems
3. Difficulty of combinatorial optimization problems
4. State space tree
5. Search space
6. Travelling Salesman Problem (TSP)
Part 2:
1. Exact methods
2. Heuristics methods
3. Brute-force (exhaustive) algorithm to solve combinatorial problems
4. Branch and bound algorithm to solve combinatorial problems
5. The nearest neighbour to solve the Travelling Salesman Problem
Part 3:
1. Inspirations of the Ant Colony Optimization (ACO)
2. Mathematical models of the Ant Colony Optimization
3. Implementation of the Ant Colony Optimization
4. Testing and analysing the performance of the Ant Colony Optimization
5. Tuning the parameter of the Ant Colony Optimization
Ant Colony Optimization will be the main algorithm, which is a search method that can be easily applied to different applications including Machine Learning, Data Science, Neural Networks, and Deep Learning.
Some of the reviews are as follows:
Fan said: "Another Wonderful course of Dr Seyedali，I really appreciate it！ I also look forward to more applications and examples of ACO."
Ashish said: "This course clears my concept about Ant colony optimization specially with MATLAB and how to apply to our problem. Thank you so much, Sir, for design such a helpful course"
Join 100+ students and start your optimization journey with us. If you are in any way not satisfied, for any reason, you can get a full refund from Udemy within 30 days. No questions asked. But I am confident you won't need to. I stand behind this course 100% and am committed to help you along the way.
Who this course is for:
- Anyone who wants to learn about combinatorial optimization and discrete mathematics
- Anyone who wants to understand different combinatorial optimization algorithms
- Anyone who wants to understand and implement Ant Colony Optimization
- Anyone who wants to solve Travelling Salesman Problem
Instructor
- 4.5 Instructor Rating
- 5,370 Reviews
- 21,493 Students
- 8 Courses
Professor Seyedali (Ali) Mirjalili is internationally recognized for his advances in Artificial Intelligence (AI) and optimization, including the first set of SI techniques from a synthetic intelligence standpoint - a radical departure from how natural systems are typically understood - and a systematic design framework to reliably benchmark, evaluate, and propose computationally cheap robust optimization algorithms. Prof. Mirjalili has published over 500 research outputs.
Prof. Mirjalili has over 110,000 citations in total with an H-index of 110. From Google Scholar metrics, he is globally one of the most-cited researchers in Artificial Intelligence. As the most cited researcher in Robust Optimization, he is in the list of 1% highly-cited researchers and named as one of the most influential researchers in AI by the world by Web of Science. In 2022 and 2023, The Australian newspaper recognized him as a global leader in Artificial Intelligence and a national leader in the Evolutionary Computation and Fuzzy Systems fields.
Ali is a senior member of IEEE and an associate editor of several journals including IEEE Access, Applied Soft Computing, Advances in Engineering Software, and Applied Intelligence. His research interests include Robust Optimization, Engineering Optimization, Multi-objective Optimization, Swarm Intelligence, Evolutionary Algorithms, and Artificial Neural Networks. He is working on the application of multi-objective and robust meta-heuristic optimization techniques as well.
In addition to his excellent research outputs, Prof. Ali has been a teacher for over 15 years and a Udemy instructor for more than three years. He has 10,000+ students, and the majority of his courses have been highly ranked by both Udemy and students. He is the only Udemy instructor in the list of top 1% highly-cited researchers.