課程信息
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中級

完成時間大約為33 小時

建議:8 weeks of study, 10-15 hours per week...

英語(English)

字幕:英語(English)

您將獲得的技能

Constraint ProgrammingBranch And BoundDiscrete OptimizationLinear Programming (LP)

100% 在線

立即開始,按照自己的計劃學習。

可靈活調整截止日期

根據您的日程表重置截止日期。

中級

完成時間大約為33 小時

建議:8 weeks of study, 10-15 hours per week...

英語(English)

字幕:英語(English)

教學大綱 - 您將從這門課程中學到什麼

1
完成時間為 2 小時

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.

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4 個視頻 (總計 43 分鐘), 3 個閱讀材料, 1 個測驗
3 個閱讀材料
Start of Course Survey10分鐘
Socialize10分鐘
Course Syllabus10分鐘
2
完成時間為 7 小時

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.

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9 個視頻 (總計 101 分鐘), 1 個測驗
9 個視頻
Knapsack 4 - dynamic programming17分鐘
Knapsack 5 - relaxation, branch and bound14分鐘
Knapsack 6 - search strategies, depth first, best first, least discrepancy14分鐘
Assignments Getting Started13分鐘
Knapsack & External Solver10分鐘
Exploring the Material - open course design, optimization landscape, picking your adventure10分鐘
3
完成時間為 17 小時

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.

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13 個視頻 (總計 248 分鐘), 1 個閱讀材料, 2 個測驗
13 個視頻
CP 4 - global constraint intuition, table constraint, sudoku19分鐘
CP 5 - symmetry breaking, BIBD, scene allocation18分鐘
CP 6 - redundant constraints, magic series, market split11分鐘
CP 7 - car sequencing, dual modeling18分鐘
CP 8 - global constraints in detail, knapsack, alldifferent33分鐘
CP 9 - search, first-fail, euler knight, ESDD25分鐘
CP 10 - value/variable labeling, domain splitting, symmetry breaking in search28分鐘
Graph Coloring6分鐘
Optimization Tools5分鐘
Set Cover8分鐘
1 個閱讀材料
Optimization Tools10分鐘
4
完成時間為 13 小時

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.

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10 個視頻 (總計 191 分鐘), 1 個測驗
10 個視頻
LS 4 - optimality vs feasibility, graph coloring22分鐘
LS 5 - complex neighborhoods, sports scheduling21分鐘
LS 6 - escaping local minima, connectivity15分鐘
LS 7 - formalization, heuristics, meta-heuristics introduction22分鐘
LS 8 - iterated location search, metropolis heuristic, simulated annealing, tabu search intuition18分鐘
LS 9 - tabu search formalized, aspiration, car sequencing, n-queens26分鐘
Traveling Salesman10分鐘
4.9
58 個審閱Chevron Right

40%

完成這些課程後已開始新的職業生涯

38%

通過此課程獲得實實在在的工作福利

來自离散优化的熱門評論

創建者 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.

創建者 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

講師

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Dr. Carleton Coffrin

Adjunct Lecturer
Computing and Information Systems

關於 墨尔本大学

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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