Informações sobre o curso
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Prazos flexíveis

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Nível intermediário

Aprox. 19 horas para completar

Sugerido: 4 weeks of study, 6-12 hours/week...

Inglês

Legendas: Inglês

Habilidades que você terá

Constraint ProgrammingProblem SolvingMathematical ModelDiscrete Optimization

100% online

Comece imediatamente e aprenda em seu próprio cronograma.

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.

Nível intermediário

Aprox. 19 horas para completar

Sugerido: 4 weeks of study, 6-12 hours/week...

Inglês

Legendas: Inglês

Programa - O que você aprenderá com este curso

Semana
1
7 horas para concluir

MiniZinc introduction

In this first module, you will learn the basics of MiniZinc, a high-level modeling language for discrete optimization problems. Combining the simplicity of MiniZinc with the power of open-source industrial solving technologies, you will learn how to solve applications such as knapsack problems, graph coloring, production planning and tricky Cryptarithm puzzles, with great ease.

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20 vídeos ((Total 219 mín.)), 6 leituras, 1 teste
20 videos
1.1.3 Third Model6min
1.1.4 Models and Instances10min
1.1.5 Modeling Objects8min
1.1.6 Arrays and Comprehensions16min
1.1.7 Global Constraints9min
1.1.8 Module 1 Summary5min
Workshop 0 Solution19min
Workshop 1 Solution21min
Assignment Submission - IDE7min
Assignment Submission - CLI4min
Reference 1: Basic Features13min
Reference 2: Booleans Expressions13min
Reference 3: Sets, Arrays, Comprehensions19min
Reference 4: Enumerated Types7min
Reference 5: Strings and Output8min
Reference 6: Option Types12min
Reference 7: Command Line Interface8min
6 leituras
Course Overview10min
Start of Course Survey (Researcher: Professor Gregor Kennedy, Melbourne Centre for the Study of Higher Education)12min
Getting MiniZinc10min
Workshop 0: First Steps20min
Workshop 1: Temperature45min
About the Reference Material2min
Semana
2
5 horas para concluir

Modeling with Sets

In this module, you will learn how to model problems involving set selection. In particular, you will see different ways of representing set variables when the variable has no constraints on its cardinality, has fixed cardinality and bounded cardinality. You also have to ensure all model decisions are valid decisions, and each valid decision corresponds to exactly one model decision.

...
6 vídeos ((Total 64 mín.)), 1 leitura, 1 teste
6 videos
1.2.4 Sets with Bounded Cardinality13min
1.2.5 Module 2 Summary3min
Workshop 2 Solution19min
1 leituras
Workshop 2: Surrender Negotiations1h 15min
Semana
3
8 horas para concluir

Modeling with Functions

In this module, you will learn how to model pure assignment problems and partition problems, which are functions in disguise. These problems find applications in rostering and constrained clustering. In terms of modeling techniques, you will see the power of common subexpression elimination and intermediate variables, and encounter the global cardinality constraint for the first time. MiniZinc also provides constraints for removing value symmetries.

...
7 vídeos ((Total 86 mín.)), 1 leitura, 1 teste
7 videos
1.3.4 Global Cardinality Constraint9min
1.3.5 Pure Partitioning14min
1.3.6 Module 3 Summary5min
Workshop 3 Solution28min
1 leituras
Workshop 3: Feast Trap2h 50min
Semana
4
7 horas para concluir

Multiple Modeling

In the final module of this course you will see how discrete optimization problems can often be seen from multiple viewpoints, and modeled completely differently from each viewpoint. Each viewpoint may have strengths and weaknesses, and indeed the different models can be combined to help each other.

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6 vídeos ((Total 67 mín.)), 2 leituras, 1 teste
6 videos
1.4.4 More Multiple Models12min
1.4.5 Module 4 Summary7min
Workshop 4 Solution13min
2 leituras
Workshop 4: Composition2h 5min
End of Course Survey (Researcher: Professor Gregor Kennedy, Melbourne Centre for the Study of Higher Education)10min
4.8
44 avaliaçõesChevron Right

Principais avaliações do Basic Modeling for Discrete Optimization

por CJMay 30th 2019

Good teachers. They go gradually from very easy to challenging concepts. Also a good intro to the main optimization problems.

por CTJun 8th 2019

Certainly more effort went into this course than I was expecting; well worth the $0 cost of entry.

Instrutores

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Prof. Peter James Stuckey

Professor
Computing and Information Systems
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Prof. Jimmy Ho Man Lee

Professor
Department of Computer Science and Engineering

Sobre Universidade de 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....

Sobre Universidade Chinesa de Hong Kong

Founded in 1963, The Chinese University of Hong Kong (CUHK) is a forward looking comprehensive research university with a global vision and a mission to combine tradition with modernity, and to bring together China and the West. CUHK teachers and students hail from all corners of the world. CUHK graduates are connected worldwide through an expansive alumni network....

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