Course Summary
Learn the fundamentals of basic modeling in this course, including how to create, analyze, and optimize models to solve real-world problems.Key Learning Points
- Understand the basics of modeling and how to apply it to real-world problems.
- Learn how to use optimization techniques to improve your models.
- Gain hands-on experience with modeling tools and software.
Related Topics for further study
Learning Outcomes
- Develop the skills to create, analyze, and optimize models for real-world problems.
- Learn how to use modeling software and tools effectively.
- Gain hands-on experience with real-world case studies and examples.
Prerequisites or good to have knowledge before taking this course
- Basic understanding of algebra and statistics.
- Some knowledge of programming languages like Python or R is helpful.
Course Difficulty Level
BeginnerCourse Format
- Online
- Self-Paced
- Video Lectures
- Hands-On Exercises
Similar Courses
- Advanced Modeling Techniques
- Data Analysis and Visualization
Related Education Paths
Notable People in This Field
- Kaggle
- INFORMS
Related Books
Description
Optimization is a common form of decision making, and is ubiquitous in our society. Its applications range from solving Sudoku puzzles to arranging seating in a wedding banquet. The same technology can schedule planes and their crews, coordinate the production of steel, and organize the transportation of iron ore from the mines to the ports. Good decisions in manpower and material resources management also allow corporations to improve profit by millions of dollars. Similar problems also underpin much of our daily lives and are part of determining daily delivery routes for packages, making school timetables, and delivering power to our homes. Despite their fundamental importance, all of these problems are a nightmare to solve using traditional undergraduate computer science methods.
Outline
- MiniZinc introduction
- Welcome to Basic Modeling for Discrete Optimization
- 1.1.1 First Steps
- 1.1.2 Second Model
- 1.1.3 Third Model
- 1.1.4 Models and Instances
- 1.1.5 Modeling Objects
- 1.1.6 Arrays and Comprehensions
- 1.1.7 Global Constraints
- 1.1.8 Module 1 Summary
- Workshop 0 Solution
- Workshop 1 Solution
- Assignment Submission - IDE
- Assignment Submission - CLI
- Reference 1: Basic Features
- Reference 2: Booleans Expressions
- Reference 3: Sets, Arrays, Comprehensions
- Reference 4: Enumerated Types
- Reference 5: Strings and Output
- Reference 6: Option Types
- Reference 7: Command Line Interface
- Course Overview
- Start of Course Survey (Research Team: NTHU & CUHK)🎁👕Get the course Signature T-shirt👕🎁
- Start of Course Survey (Researcher: Professor Gregor Kennedy, Melbourne Centre for the Study of Higher Education)
- “Building Decision Support Systems using MiniZinc” by Professor Mark Wallace
- Getting MiniZinc
- Workshop 0: First Steps
- Workshop 1: Temperature
- About the Reference Material
- Modeling with Sets
- 1.2.1 Selecting a Set
- 1.2.2 Choosing a Set Representation
- 1.2.3 Choosing a Fixed Cardinality Set
- 1.2.4 Sets with Bounded Cardinality
- 1.2.5 Module 2 Summary
- Workshop 2 Solution
- Workshop 2: Surrender Negotiations
- Modeling with Functions
- 1.3.1 Modeling Functions
- 1.3.2 Another Assignment Problem Example
- 1.3.3 Modeling Partitions
- 1.3.4 Global Cardinality Constraint
- 1.3.5 Pure Partitioning
- 1.3.6 Module 3 Summary
- Workshop 3 Solution
- Workshop 3: Feast Trap
- Multiple Modeling
- 1.4.1 Multiple Modeling
- 1.4.2 Permutation
- 1.4.3 More Permutation Problem
- 1.4.4 More Multiple Models
- 1.4.5 Module 4 Summary
- Workshop 4 Solution
- Workshop 4: Composition
- End of Course Survey (Research Team: NTHU & CUHK)🎁👕Get the course Signature T-shirt👕🎁
- End of Course Survey (Researcher: Professor Gregor Kennedy, Melbourne Centre for the Study of Higher Education)
Summary of User Reviews
Discover the fundamentals of basic modeling with this highly-rated course on Coursera. Students have praised the course for its comprehensive coverage of key concepts and hands-on exercises that reinforce learning.Key Aspect Users Liked About This Course
Comprehensive coverage of key conceptsPros from User Reviews
- Clear and concise explanations
- Interactive and engaging exercises
- Great support from instructors and community
- Practical application of concepts
Cons from User Reviews
- Some sections may be too basic for advanced learners
- Course material can be repetitive at times
- Lack of real-world case studies
- Limited flexibility in course schedule
- No certificate of completion for free version
Prof. Peter James Stuckey
4.8 Raiting
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