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.
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Basic Modeling for Discrete Optimization
Мельбурнский университетОб этом курсе
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Попробуйте Coursera для бизнесаПриобретаемые навыки
- Constraint Programming
- Problem Solving
- Mathematical Model
- Discrete Optimization
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Попробуйте Coursera для бизнесаПрограмма курса: что вы изучите
MiniZinc introduction
Modeling with Sets
Modeling with Functions
Multiple Modeling
Рецензии
- 5 stars86,23 %
- 4 stars11,35 %
- 3 stars1,69 %
- 2 stars0,24 %
- 1 star0,48 %
Лучшие отзывы о курсе BASIC MODELING FOR DISCRETE OPTIMIZATION
Very interesting and neatly prepared course. It was very easy to dive in the course and to stay motivated. I would highly recommend their course for its amazing quality.
great course for beginners and those who are looking for applications of optimisation. the only problem is it forces you to work with minizinc and may consume extra time than expected
Great introduction to modeling for discrete optimization. Very engaging and challenging.
Compact introduction to the basics of specifying models in MiniZinc. Excellent starter kit, but you will fight a bit with the syntax of MiniZinc.
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