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学生对 墨尔本大学 提供的 Basic Modeling for Discrete Optimization 的评价和反馈

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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. This course is intended for students interested in tackling all facets of optimization applications. You will learn an entirely new way to think about solving these challenging problems by stating the problem in a state-of-the-art high level modeling language, and letting library constraint solving software do the rest. This will allow you to unlock the power of industrial solving technologies, which have been perfected over decades by hundreds of PhD researchers. With access to this advanced technology, problems that are considered inconceivable to solve before will suddenly become easy. Watch the course promotional video here:



Nov 7, 2020

Excellent course! I learned a lot. Although the assignments were sometimes hard to fathom, and its online nature mean getting hints was difficult, there's enough there to help get through.


Jul 26, 2019

Thank you so much for the course. I had to fight my coding habits, programming CP models is quite different from the traditional programming I'm, and it could even be more fun!


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