(1) Understand and learn about the knowledge and methods for optimization and optimal design.
(2) Understand and can calculate basic mathematical formulas for linear and nonlinear programming optimization techniques.
(3) Understand the concepts and mathematical expressions of multi-objective optimization.
(4) Can explain and practice the principles of optimal design for genetic algorithms.
(5) Can create the optimal design for a helical gear reducer as an example of optimal design, and apply the optimization.
Outline:
Optimization (which covers a wide range of fields) and optimal design (which covers design fields) are being actively used in a variety of fields in response to the demand for higher performance in mechanical systems. As computers continue to develop, the importance of optimization and optimal design is expected to increase in the future. In this course, students will learn about the concepts and processes of optimization and optimization design and optimization techniques. They will also learn specific examples of optimal design for various machine systems. Quizzes will be carried out to ensure knowledge.
Style:
Classes will be held in a lecture style. There will be assignments as appropriate.
Notice:
This course's content will amount to 90 hours of study in total. These hours include the learning time guaranteed in classes and the standard self-study time required for pre-study / review, and completing assignment reports.
Students who miss 1/3 or more of classes will not be eligible for a passing grade.
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Theme |
Goals |
| 2nd Semester |
| 3rd Quarter |
| 1st |
Course guidance
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Explain the course content in accordance with the syllabus
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| 2nd |
Optimization concepts and terminology
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Explain concepts, terminology, and techniques of optimization through examples of optimal design, and optimization and optimal design problems.
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| 3rd |
Optimization methods using Optimization Toolbox (Matlab)
Learn the basic operations of Matlab/Simulink and Optimization Toolbox for calculating optimization. |
How to use MATLAB/Simulink and Optimization Toolbox
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| 4th |
Linear programming optimization (1)
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An outline of linear programming optimization problems and formulation methods.
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| 5th |
Linear programming optimization (2)
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Simplex method and examples of its application.
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| 6th |
Linear programming optimization (3)
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Example applications of linear programming methods.
Linear programming optimization using Matlab's Optimization Toolbox.
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| 7th |
Nonlinear programming optimization (1) |
An overview of non-linear optimization problems and optimization techniques.
Explain application examples of nonlinear programming in engineering and unconstrained optimization techniques.
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| 8th |
Nonlinear programming optimization (2) |
Learn about modeling, formulation, preprocessing, optimization calculation programs, and examination of optimization results.
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| 4th Quarter |
| 9th |
Nonlinear programming optimization (3)
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Genetic algorithms (GA)
Learn an overview for genetic algorithms and the contents of an optimal solution search program.
Take design examples and compare them with other optimization techniques.
Explain constrained optimization techniques and learn SUMT, linear minimization techniques, and Powell's conjugate direction method.
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| 10th |
Multi-objective optimization
Report 1: Multi-objective optimization of new bus routes (1)
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Learn about the weighted method for the multi-objective optimization method. Take application examples to learn how to do multi-objective optimization in the exercise.
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| 11th |
Report 1: Multi-objective optimization of new bus routes (2)
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Plan a new bus route to maximize customer satisfaction and profit for the bus operator using multi-objective optimization. Multi-objective optimization using Matlab's Optimization Toolbox.
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| 12th |
Report 2: Optimal designs for helical gear reducers (1) |
Use the gear design knowledge learned in Engineering Design and Design and Drawing, and create the optimal design for a helical gear reducer.
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| 13th |
Report 2: Optimal designs for helical gear reducers (2) |
Formulate methods for objective functions, design variables, and constraints.
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| 14th |
Report 2: Optimal designs for helical gear reducers (3) |
Promote Matlab programming creation (M-files).
Study the optimization results, compare them with the computation results done in this course, and recognize the importance of optimal design.
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| 15th |
Summary and evaluation
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Summarize and review the content learned on this course.
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| 16th |
Final exam
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