Course title
V04605002
Mathematical Programming

ZHAI GUISHENG Click to show questionnaire result at 2019
Course description
Mathematical programming is used to maximize or minimize a function under given conditions (constraints). In this course, we explain the problem formulation of mathematical programming, and then talk about some basic approach to solving both linear and nonlinear mathematical programming problems. Numerical methods by using MATLAB solvers and the descent method are also introduced.
Purpose of class
Deliver lectures about problem formulation of mathematical programming, fundamental idea and approach to linear and nonlinear mathematical programming problems.

Introduce numerical solutions by using MATLAB, and by the descent method.

Aim to provide practical formulations and solutions for students.
Goals and objectives
  1. Students can understand the problem formulation and describe the representation of mathematical programming.
  2. Students can understand the basic idea of linear mathematical programming and can solve the problems by using graphical approach and the simplex method.
  3. Students can understand the basic idea of nonlinear mathematical programming and can manage to obtain the analytic solutions and the numerical solutions.
Relationship between 'Goals and Objectives' and 'Course Outcomes'

Mid-term report Final exam Total.
1. 20% 10% 30%
2. 20% 20% 40%
3. 30% 30%
Total. 40% 60% -
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. Minimize functions with one or two variables Review of basic calculus, functions and their extreme value points 190minutes
3. Mathematical Linear Programming (MLP) 1: various MLP models Prepare various MLP models and the problems 190minutes
4. Mathematical Linear Programming (MLP) 2: general problem formulation and graphical solution Prepare general problem formulation and graphical solution 190minutes
5. Mathematical Linear Programming (MLP) 3: simplex method Review linear equations, prepare the simplex method 190minutes
6. Mathematical Linear Programming (MLP) 4: solution by MATLAB solvers;

Mid-term report
Prepare the problem formulation and solution by Excel solvers 190minutes
7. Duality and sensitivity analysis 1: duality and its economic interpretation Prepare the definition of duality and its economic interpretation 190minutes
8. Duality and sensitivity analysis 2: sensitivity analysis Prepare sensitivity analysis 190minutes
9. Application of Mathematical Linear Programming (MLP) 1: two-stage simplex method Prepare two-stage simplex method 190minutes
10. Application of Mathematical Linear Programming (MLP) 2: game theory Review basic optimization problem, and prepare game theory 190minutes
11. Mathematical Nonlinear Programming (MNP) 1: optimal condition of functions with one variable Review and prepare the optimal condition of functions with one variable 190minutes
12. Mathematical Nonlinear Programming (MNP) 2: optimal condition of functions with two variables Review and prepare the optimal condition of functions with two variables 190minutes
13. Mathematical Nonlinear Programming (MNP) 3: steepest descent method Prepare the steepest descent method 190minutes
14. Review and exercise of the whole course, final exam Review of the whole course 190minutes
Total. - - 2660minutes
Evaluation method and criteria
Mid-term report : 40%, Final exam: 60%

Pass when reaching 60% of the whole evaluation, or in other words, reaching the level of describing problem formulation of mathematical programming, solving simple mathematical programming problems in both linear and nonlinear cases.
Feedback on exams, assignments, etc.
ways of feedback specific contents about "Other"
Feedback in outside of the class (ScombZ, mail, etc.)
Textbooks and reference materials
Textbook:
Sakawa, Yano, Nishizaki: Easy-To-Understood Mathematical Programming, Morikita Publishing (ISBN 978-4-627-91771-2)

Reference Book:
Fukushima: Introduction to Mathematical Programming (New Version), Asakura Publishing (ISBN 978-4-254-28004-3)
Prerequisites
Desirable to have basic knowledge on linear algebra and elementary calculus.
Office hours and How to contact professors for questions
  • 火曜日 12:30 -- 13:00
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 applicable
N/A N/A
Education related SDGs:the Sustainable Development Goals
  • 4.QUALITY EDUCATION
  • 5.GENDER EQUALITY
  • 7.AFFORDABLE AND CLEAN ENERGY
  • 9.INDUSTRY, INNOVATION AND INFRASTRUCTURE
  • 12.RESPONSIBLE CONSUMPTION & PRODUCTION
  • 13.CLIMATE ACTION
  • 16.PEACE, JUSTICE AND STRONG INSTITUTIONS
  • 17.PARTNERSHIPS FOR THE GOALS
Last modified : Fri Jun 28 16:56:20 JST 2024