Objectives of these lessons are to give students learning in the elementary decision tools based in mathematics and informatics. Lessons are constituted of three courses :
Statistics to establish preliminary understanding of problems through data analysis and to support decision facing risky situation ; Linear programming to model and solve problem under constraints ; and Computer science as set of tools useful to manage, analyze and solve data and problems.
Statistics provide models of random situation (based on Probability) and tools to specify risk and to decide facing random environment. Applications come from quality
management, production monitoring, market and marketing studies. Lessons topics are : descriptive statistics - to summarize and to represent data ; inferential statistics
(introduction to estimation and test theory) - to extract knowledge from survey and/or experimental data and to help decision and prediction.
Linear programming as operations research tool allows to model complex problems by identifying variables (continuous or integer), by modeling the problem constraints as equations and linear inequalities on these variables, and by expressing quality of the solutions using a linear function. The study of the solutions produced by the simplex algorithm, coupled with the notion of duality allows a sensitivity analysis of the solutions very useful in decision making. In integer linear programming, the Branch and Bound algorithm will be studied, as well as the concept of quality modeling to improve the resolution.
The use of Computer science as a tool for modeling and solving is enhanced during an IT project for a period equivalent to two full weeks. The students, in teams, shall propose a IT solution at a given industrial problem.
Students will gain skills in:
IT Project (P) : report and computer programms
E1 = Final written exam from 1st exam period - duration 4 hours
E2 = Written exam from 2nd exam period - duration 4 hours
N1 = 0.7*E1 + 0.3*P
N2 = E2
The course exists in the following branches:
Course ID : 3GUC0905
You can find this course among all other courses.
Tous ces livres sont disponibles à la bibliothèque de Grenoble INP - Génie industriel :
Date of update June 5, 2015