Course title
V04605002
Mathematical Programming

 zhai guisheng Click to show questionnaire result at 2018
Course description
Learn about several important mathematical programming problems and their solutions, including linear mathematical programming, combinatorial optimization, network planning, and nonlinear mathematical programming.
Purpose of class
Learn about several important mathematical programming problems and their solutions, including linear mathematical programming, combinatorial optimization, network planning, and nonlinear mathematical programming.
Goals and objectives
  1. understand the basic idea of linear mathematical programming and simplex method.
  2. understand the formulation of combinatorial optimization and its simple algorithms
  3. understand several typical algorithms of nonlinear mathematical programming
Language
Japanese
Class schedule

 Class schedule HW assignments (Including preparation and review of the class.) Amount of Time Required
1. Guidance, mathematical programming models Prepare mathematical programming models 190minutes
2. Linear mathematical programming 1 (basic solution and optimal solution) Review of Linear mathematical programming problems learned at System Engineering B 190minutes
3. Linear mathematical programming 2 (simplex method) Summarize the algorithm of simplex method with exercises 190minutes
4. Linear mathematical programming 3 (dual problem and dual theorem) Review the duality property and check how to use it. 190minutes
5. Linear mathematical programming 4 (other algorithms) Review of the algorithms learned by now. 190minutes
6. Combinatorial optimization Prepare the problem formulation and the idea. 190minutes
7. Network planning 1 (basic on graph theory） Review and the related part in the textbook, including basic definitions in graph theory. 190minutes
8. Mid-term exam and review Review of the first half of the course 190minutes
9. Network planning 2 (shortest path） Review the related part in the textbook, and study the meaning of shortest path together with application background. 190minutes
10. Network planning 3 (maximal flow) Review the related part in the textbook, and study the meaning of maximal flow. 190minutes
11. Nonlinear mathematical programming 1 (gradient and Hessian matrix of a function) Review of basic calculus in optimization problems 190minutes
12. Nonlinear mathematical programming 2 (optimization without constraints) Review basic knowledge about positive/negative definite matrices. Summarize the algorithms with exercises 190minutes
13. Nonlinear mathematical programming 3 (optimization condition with constraints) Review basic knowledge about positive/negative definite matrices with constraints. Prepare the problem formulation and the theoretical part 190minutes
14. Final exam and review Review of the whole course 190minutes
Total. - - 2660minutes
Relationship between 'Goals and Objectives' and 'Course Outcomes'

 Exams Total.
1. 30% 30%
2. 30% 30%
3. 40% 40%
Total. 100% -
Evaluation method and criteria
Evaluation by both mid-term and final exams
Mid-term exam: 40%; Final exam: 60%
Textbooks and reference materials
Fukushima, M.: Introduction to Mathematical Programmning (New Version), Asakura Publishing
Prerequisites
Desirable to have basic knowledge on linear algebra and elementary calculus.
Office hours and How to contact professors for questions
  • Tuesday 12:30 -- 13:00
Relation to the environment
Environment-related course (20%)
Regionally-oriented
Non-regionally-oriented course
Development of social and professional independence
  • Course that cultivates a basic self-management skills
  • Course that cultivates an ability for utilizing knowledge
Active-learning course
More than one class is interactive
Course by professor with work experience
Work experience Work experience and relevance to the course content if applicatable
N/A N/A
Last modified : Tue Jun 11 04:01:29 JST 2019