Course title
6M007100,7M8200001
Engineering Optimization
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
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% -
Language
English
Class schedule

Class schedule HW assignments (Including preparation and review of the class.) Amount of Time Required
1． - Orientation and study interview
- Definition step: Translating design problem into optimization problems
Writing up your study plan related to an optimal design 60minutes
The brush up about a linear programming method 60minutes
2． Definition step: Exercise Translating design problem of pasta bridge into optimization problem Checking the specification for pasta bridge competition 60minutes
3． - Definition step: Translating constraint conditions into penalty functions in classroom
- Optimization step: Basic algorithms derived from optimality conditions—Gradient method
The brush up about translation of a design problem 60minutes
4． Definition step: Exercise Definition of optimal design for pasta bridge competition The definition of optimization problem for pasta bridge competition 60minutes
Deploying the pasta bridge optimization definition to the presentation document 60minutes
5． Optimization step: Non-linear algorithm, SLP and approximation method for optimal design, Response Surface Model (RSM) Seeing about SLP 60minutes
6． Design Review: Presentation and discussion for pasta bridge definitions Making of the presentation document 120minutes
7． Soft computing method for Multi-peak problems—SA and GA methods Seeing about SA and GA 120minutes
Reporting HJ method as a direct algorithm 120minutes
8． Optimization step: Exercise Design of optimization algorithm for paste bridge optimization The brush up about definition of the optimization problem with constraint functions 60minutes
Design and creating your optimization algorithm 240minutes
9． Optimization step: Exercise Making optimization algorithm of paste bridge optimization Creating your optimization algorithm 240minutes
10． Optimization step: Exercise Making optimization algorithm of paste bridge optimization Creating your optimization algorithm 240minutes
11． Production step: Exercise Making Pasta Bridge Applying your optimization algorithm to Pasta Bridge design problem, and estimation of optimization result 180minutes
Making Pasta Bridge 240minutes
12． Production step: Exercise Making Pasta Bridge Making Pasta Bridge 240minutes
13． - Production step: Exercise Making Pasta Bridge
- Competition step: Preparation of presentation material
Making Pasta Bridge 120minutes
Making final presentation material 120minutes
14． Competition: Presentation and competition for your optimal designs Making final presentation material 60minutes
Total. - - 2640minutes
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%.
Feedback on exams, assignments, etc.
ways of feedback specific contents about "Other"
Feedback in the class
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
Regional Cooperation PBL
Development of social and professional independence
• Course that cultivates an ability for utilizing knowledge
• Course that cultivates a basic interpersonal skills
Active-learning course
Most classes are interactive
Course by professor with work experience
Work experience Work experience and relevance to the course content if applicable
Applicable To perform syllabus planning based on experience and needs of 10 year's our company period, and setting an exercise problem to obtain CAE and optimization technical ability. Based on research and surveys of manufacturing companies and research institutes, various analysis techniques in system development, system design techniques, AI techniques, etc.
Education related SDGs:the Sustainable Development Goals
• 9.INDUSTRY, INNOVATION AND INFRASTRUCTURE
• 12.RESPONSIBLE CONSUMPTION & PRODUCTION