课程信息
4.9
232 个评分
50 个审阅
100% 在线

100% 在线

立即开始,按照自己的计划学习。
可灵活调整截止日期

可灵活调整截止日期

根据您的日程表重置截止日期。
中级

中级

完成时间(小时)

完成时间大约为34 小时

建议:8 weeks of study, 10-15 hours per week...
可选语言

英语(English)

字幕:英语(English)

您将获得的技能

Constraint ProgrammingBranch And BoundDiscrete OptimizationLinear Programming (LP)
100% 在线

100% 在线

立即开始,按照自己的计划学习。
可灵活调整截止日期

可灵活调整截止日期

根据您的日程表重置截止日期。
中级

中级

完成时间(小时)

完成时间大约为34 小时

建议:8 weeks of study, 10-15 hours per week...
可选语言

英语(English)

字幕:英语(English)

教学大纲 - 您将从这门课程中学到什么

1
完成时间(小时)
完成时间为 2 小时

Welcome

These lectures and readings give you an introduction to this course: its philosophy, organization, and load. They also tell you how the assignments are a significant part of the class. This week covers the common input/output organization of the assignments, how they are graded, and how to succeed in this class....
Reading
4 个视频 (总计 43 分钟), 3 个阅读材料, 1 个测验
Video4 个视频
Course Motivation - Indiana Jones, challenges, applications20分钟
Course Introduction - philosophy, design, grading rubric11分钟
Assignments Introduction & Any Integer9分钟
Reading3 个阅读材料
Start of Course Survey10分钟
Socialize10分钟
Course Syllabus10分钟
2
完成时间(小时)
完成时间为 7 小时

Knapsack

These lectures introduce optimization problems and some optimization techniques through the knapsack problem, one of the most well-known problem in the field. It discusses how to formalize and model optimization problems using knapsack as an example. It then reviews how to apply dynamic programming and branch and bound to the knapsack problem, providing intuition behind these two fundamental optimization techniques. The concept of relaxation and search are also discussed....
Reading
9 个视频 (总计 101 分钟), 1 个测验
Video9 个视频
Knapsack 2 - greedy algorithms7分钟
Knapsack 3 - modeling8分钟
Knapsack 4 - dynamic programming17分钟
Knapsack 5 - relaxation, branch and bound14分钟
Knapsack 6 - search strategies, depth first, best first, least discrepancy14分钟
Assignments Getting Started13分钟
Knapsack & External Solver10分钟
Exploring the Material - open course design, optimization landscape, picking your adventure10分钟
3
完成时间(小时)
完成时间为 17 小时

Constraint Programming

Constraint programming is an optimization technique that emerged from the field of artificial intelligence. It is characterized by two key ideas: To express the optimization problem at a high level to reveal its structure and to use constraints to reduce the search space by removing, from the variable domains, values that cannot appear in solutions. These lectures cover constraint programming in detail, describing the language of constraint programming, its underlying computational paradigm and how it can be applied in practice....
Reading
13 个视频 (总计 248 分钟), 1 个阅读材料, 2 个测验
Video13 个视频
CP 2 - propagation, arithmetic constraints, send+more=money26分钟
CP 3 - reification, element constraint, magic series, stable marriage16分钟
CP 4 - global constraint intuition, table constraint, sudoku19分钟
CP 5 - symmetry breaking, BIBD, scene allocation18分钟
CP 6 - redundant constraints, magic series, market split11分钟
CP 7 - car sequencing, dual modeling18分钟
CP 8 - global constraints in detail, knapsack, alldifferent33分钟
CP 9 - search, first-fail, euler knight, ESDD25分钟
CP 10 - value/variable labeling, domain splitting, symmetry breaking in search28分钟
Graph Coloring6分钟
Optimization Tools5分钟
Set Cover8分钟
Reading1 个阅读材料
Optimization Tools10分钟
4
完成时间(小时)
完成时间为 13 小时

Local Search

Local search is probably the oldest and most intuitive optimization technique. It consists in starting from a solution and improving it by performing (typically) local perturbations (often called moves). Local search has evolved substantially in the last decades with a lot of attention being devoted on which moves to explore. These lectures explore the theory and practice of local search, from the concept of neighborhood and connectivity to meta-heuristics such as tabu search and simulated annealing....
Reading
10 个视频 (总计 191 分钟), 1 个测验
Video10 个视频
LS 2 - swap neighborhood, car sequencing, magic square15分钟
LS 3 - optimization, warehouse location, traveling salesman, 2-opt, k-opt23分钟
LS 4 - optimality vs feasibility, graph coloring22分钟
LS 5 - complex neighborhoods, sports scheduling21分钟
LS 6 - escaping local minima, connectivity15分钟
LS 7 - formalization, heuristics, meta-heuristics introduction22分钟
LS 8 - iterated location search, metropolis heuristic, simulated annealing, tabu search intuition18分钟
LS 9 - tabu search formalized, aspiration, car sequencing, n-queens26分钟
Traveling Salesman10分钟
4.9
50 个审阅Chevron Right
职业方向

33%

完成这些课程后已开始新的职业生涯
工作福利

40%

通过此课程获得实实在在的工作福利

热门审阅

创建者 AMFeb 6th 2017

I like the instructor teaching approach and the evaluation system, the subject itself took me a lot of effort and i think the LNS technique should be teached just after local search.

创建者 KDSep 4th 2018

i wish there was 6 start rating so i can give this prof his due, he made a very complicated subject look very simple and easy to understand thanks a million

讲师

Avatar

Dr. Carleton Coffrin

Adjunct Lecturer
Computing and Information Systems

关于 The University of Melbourne

The University of Melbourne is an internationally recognised research intensive University with a strong tradition of excellence in teaching, research, and community engagement. Established in 1853, it is Australia's second oldest University....

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  • Good programming skills, knowledge of algorithms and linear algebra.

  • A minimal knowledge of python is necessary to integrate with the course infrastructure. Outside of that, students are free to use any language of their choice.

  • A motivated student spending the time on the programming assignment will succeed in this class.

  • At the discrete optimization store: http://www.zazzle.com.au/discreteoptimization

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