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Solving Algorithms for Discrete Optimization(으)로 돌아가기

멜버른 대학교의 Solving Algorithms for Discrete Optimization 학습자 리뷰 및 피드백

39개의 평가

강좌 소개

Discrete Optimization aims to make good decisions when we have many possibilities to choose from. Its applications are ubiquitous throughout 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 on the use of scarce or expensive resources such as staffing and material resources also allow corporations to improve their 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, these problems are a nightmare to solve using traditional undergraduate computer science methods. This course is intended for students who have completed Advanced Modelling for Discrete Optimization. In this course, you will extend your understanding of how to solve challenging discrete optimization problems by learning more about the solving technologies that are used to solve them, and how a high-level model (written in MiniZinc) is transformed into a form that is executable by these underlying solvers. By better understanding the actual solving technology, you will both improve your modeling capabilities, and be able to choose the most appropriate solving technology to use. Watch the course promotional video here:

최상위 리뷰

필터링 기준:

Solving Algorithms for Discrete Optimization의 8개 리뷰 중 1~8

교육 기관: Alex D

2018년 10월 11일

교육 기관: Miles G

2020년 9월 24일

교육 기관: lucas d

2020년 2월 8일

교육 기관: Boris O

2019년 12월 10일

교육 기관: Jan G

2019년 5월 12일

교육 기관: Leo

2019년 6월 20일


2020년 8월 2일