Optimization with Metaheuristics in Python

Dana Knight

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40 Videos (4h 27m)
    • Introduction

      6:43
    • Operations Research

      7:43
    • Continuous vs. Combinatorial

      3:37
    • Metaheuristics

      1:54
    • Search Techniques #1

      2:54
    • Search Techniques #2

      3:48
    • Search Techniques #3

      6:21
    • Simulated Annealing #1

      2:10
    • Simulated Annealing #2

      3:28
    • Simulated Annealing #3

      8:22
    • Simulated Annealing in Python, Continuous

      24:47
    • Simulated Annealing in Python, Combinatorial #1

      4:48
    • Simulated Annealing in Python, Combinatorial #2

      3:41
    • Simulated Annealing in Python, Combinatorial #3

      6:04
    • Simulated Annealing in Python, Combinatorial #4

      3:51
    • Simulated Annealing in Python, Combinatorial #5

      8:19
    • Genetic Algorithm #1

      1:29
    • Genetic Algorithm #2

      4:16
    • Genetic Algorithm #3

      2:54
    • Genetic Algorithm #4

      3:55
    • Genetic Algorithm in Python, Continuous #1

      5:58
    • Genetic Algorithm in Python, Continuous #2

      9:21
    • Genetic Algorithm in Python, Continuous #3

      27:31
    • Genetic Algorithm in Python, Continuous #4

      12:39
    • Genetic Algorithm in Python, Continuous #5

      9:51
    • Genetic Algorithm in Python, Continuous #6

      7:32
    • Genetic Algorithm in Python, Continuous #7

      4:30
    • Genetic Algorithm in Python, Continuous #8

      10:28
    • Genetic Algorithm in Python, Continuous #9

      6:28
    • Genetic Algorithm in Python, Continuous #10

      16:39
    • Genetic Algorithm in Python, Continuous #11

      3:40
    • Tabu Search #1

      0:41
    • Tabu Search #2

      3:29
    • Tabu Search #3

      2:39
    • Tabu Search in Python, Continuous

      9:05
    • Evolutionary Strategies #1

      1:14
    • Evolutionary Strategies #2

      7:21
    • Evolutionary Strategies #3

      3:34
    • Evolutionary Strategies in Python, Continuous #1

      5:39
    • Evolutionary Strategies in Python, Continuous #2

      7:07

About This Class

This course will guide you on what optimization is and what metaheuristics are. You will learn why we use metaheuristics in optimization problems as sometimes, when you have a complex problem you'd like to optimize, deterministic methods will not do; you will not be able to reach the best and optimal solution to your problem, therefore, metaheuristics should be used.

This course covers information on metaheuristics and three widely used techniques which are Simulated Annealing, Genetic Algorithm, Tabu Search, and Evolutionary Strategies. By the end of this course, you will learn what Simulated Annealing, Genetic Algorithm, and Tabu Search are, why they are used, how they work, and best of all, how to code them in Python!

The ideal student should have basic knowledge in Operation Research and basic programming skills.

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Hi! I'm Dana. I'm currently a PhD student in Industrial Engineering. I finished my B.S. in Architectural Engineering and my M.S. in Industrial Engineering. Lean Six Sigma Green Belt certified. I enjoy learning new things. My research interest is Data Science including Deep Learning, Machine Learning, and Artificial Intelligence.

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