本课程通过理论与实例相结合的形式使得学生能充分掌握运筹与优化的基本工具、理论和方法, 尤其在数学和数据科学领
域。初步掌握模型化方法来描述、分析、建模和求解现实的运筹优化问题,进而支持决策。
By providing a balanced view of "theory" and "practice", the course should allow the student to understand, use, and
build practical analysis and planning of complex systems in the field of big data and data science. The goal of this
course is to teach students to formulate, analyze, and solve mathematical models that represent real-world optimization
problems for decision analysis.
通过本课程的学习,学生预期可达到:
掌握运筹与优化分支(线性&动态规划、网络优化、运输与指派、排队论、数据建模等)的基本理论、方法
运用所学知识和方法对实际优化及数据问题进行量化分析、建模、检验及应用推广
独立或以小组的形式分析运筹优化的应用案例并给出最佳决策
应用课程提供的软件( Matlab, excel)解决实际优化问题
On successful completion of the course, students should be able to:
Understand the basic theoretical workings (including linear and dynamic programming, the transportation and
assignment problems; network optimization models, dynamic programming, queueing models, and
mathematical models in data science, etc. ) in operational research and optimization.
Formulate a real-world problem as a mathematical model and quickly explore, solve it if possible, check and
and apply it.
Build their own formulations independently or in groups, to expand existing formulations, to critically evaluate
the impact of model assumptions and to choose an appropriate solution technique for a given formulation.
Be able to implement practical cases by software( MATLAB, .etc) presented in class.
课程内容及教学日历 (如授课语言以英文为主,则课程内容介绍可以用英文;如团队教学或模块教学,教学日历须注明
主讲人)
Course Contents (in Parts/Chapters/Sections/Weeks. Please notify name of instructor for course section(s), if
this is a team teaching or module course.)