Course title
6M007100,7M8200001
Engineering Optimization

 hasegawa hiroshi Click to show questionnaire result at 2017
Course content
The scope of this course is an optimal design for Engineering Design. This course is composed of three parts. The first one lectures on modeling and computational principles of an optimal design. Several optimization methods are described in the second topics including CAX technologies. The last one exercises optimization and presentation for a pasta bridge competition.
Purpose of class
To acquire the thinking process, the theory, and methods of optimal design which combined CAE and optimization technologies
Goals and objectives
  1. Can translate a design problem into optimization problems
  2. Can understand optimization methodologies
  3. Can apply an optimization algorithm
Language
English
Class schedule

 Class schedule HW assignments (Including preparation and review of the class.) Amount of Time Required
1． Orientation and interview of your study plans Writing up your study plan related to an optimal design 60minutes
2． Translating design problem into optimization problems The brush up about a linear programming method 120minutes
3． Translating constraint conditions into penalty functions The brush up about translation of a design problem 120minutes
4． Definition of optimal design for pasta bridge competition Checking the specification for pasta bridge competition 120minutes
The definition of optimization problem for pasta bridge competition 240minutes
5． Presentation and discussion for pasta bridge definitions Making of the presentation document 120minutes
6． Basic algorithms derived from optimality conditions—Gradient method Seeing about Gradient method and SLP 60minutes
7． Non-linear optimization algorithm—SQP method Seeing about SQP method 60minutes
Reporting HJ method as a direct algorithm 120minutes
8． Soft computing method for Multi-peak problems—SA method Seeing about SA 90minutes
9． Evolutional algorithm for Multi-peak problems—GA method Seeing about GA 90minutes
10． Approximation method for optimal design—RSM Seeing about RSM 90minutes
11． Optimal design for pasta bridge competition (definition step) The brush up about definition of the optimization problem with constraint functions 120minutes
Creating your optimization algorithm 240minutes
12． Optimal design for paste bridge competition (optimization step) The brush up about optimization approach to use 120minutes
Creating your optimization algorithm 240minutes
13． Optimal design for paste bridge competition (validation step) Applying your optimization algorithm to Pasta Bridge design problem, and estimation of optimization result 240minutes
Making Pasta Bridge 180minutes
14． Presentation and discussion for your optimal designs Making Pasta Bridge 120minutes
Making final presentation material 120minutes
Total. - - 2670minutes
Relationship between 'Goals and Objectives' and 'Course Outcomes'

 Problem definition HJ method report Presentation material Optimal design solution Total.
1. 25% 25%
2. 25% 25%
3. 25% 25% 50%
4. 0%
Total. 25% 25% 25% 25% -
Evaluation method and criteria
Depending the design review of optimization definition (25%), HJ method report (25%), final presentation (25%), and optimal design solution (25%). If proposed optimal design, satisfied the design specification for pasta bridge competition, is performed by using your optimization method systematically, and also the HJ report can describe the reason clearly, those outcomes will be evaluated as 80%.
Textbooks and reference materials
K. Kawamo, M. Yokoyama and H. Hasegawa, Fundamentals and Applications of Optimization Theory (in Japanese) (2000), Corona Publishing Co. LTD.
Prerequisites
Understanding a linear programming method
Office hours and How to contact professors for questions
  • Wednesday 12:40-13:10
Regionally-oriented
Development of social and professional independence
    Active-learning course
    Course by professor with work experience
    Work experience Work experience and relevance to the course content if applicatable
    Applicatable To perform syllabus planning based on experience and needs of our company period, and setting an exercise problem to obtain CAE and optimization technical ability.
    Education related SDGs:the Sustainable Development Goals
    • 9.INDUSTRY, INNOVATION AND INFRASTRUCTURE
    • 12.RESPONSIBLE CONSUMPTION & PRODUCTION
    Last modified : Sat Mar 21 13:15:03 JST 2020