이 강좌에 대하여

최근 조회 103,446회

Tired of solving Sudokus by hand? This class teaches you how to solve complex search problems with discrete optimization concepts and algorithms, including constraint programming, local search, and mixed-integer programming.
Optimization technology is ubiquitous in our society. It schedules planes and their crews, coordinates the production of steel, and organizes the transportation of iron ore from the mines to the ports. Optimization clears the day-ahead and real-time markets to deliver electricity to millions of people. It organizes kidney exchanges and cancer treatments and helps scientists understand the fundamental fabric of life, control complex chemical reactions, and design drugs that may benefit billions of individuals.

This class is an introduction to discrete optimization and exposes students to some of the most fundamental concepts and algorithms in the field. It covers constraint programming, local search, and mixed-integer programming from their foundations to their applications for complex practical problems in areas such as scheduling, vehicle routing, supply-chain optimization, and resource allocation.

학습자 경력 결과

40%

가 이 강좌를 수료한 후 새로운 커리어를 시작함

40%

가 이 강좌를 통해 확실한 경력상 이점을 얻음

17%

가 급여 인상 또는 승진 성취

공유 가능한 수료증

완료 시 수료증 획득

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

유동적 마감일

일정에 따라 마감일을 재설정합니다.

중급 단계

완료하는 데 약 65시간 필요

영어

자막: 영어

귀하가 습득할 기술

Constraint ProgrammingBranch And BoundDiscrete OptimizationLinear Programming (LP)

학습자 경력 결과

40%

가 이 강좌를 수료한 후 새로운 커리어를 시작함

40%

가 이 강좌를 통해 확실한 경력상 이점을 얻음

17%

가 급여 인상 또는 승진 성취

공유 가능한 수료증

완료 시 수료증 획득

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

유동적 마감일

일정에 따라 마감일을 재설정합니다.

중급 단계

완료하는 데 약 65시간 필요

영어

자막: 영어

강의 계획 - 이 강좌에서 배울 내용

콘텐츠 평가95%(3,131개의 평가)

주

1

주 1

완료하는 데 2시간 필요

Welcome

These lectures and readings give you an introduction to this course: its philosophy, organization, and load. They also tell you how the assignments are a significant part of the class. This week covers the common input/output organization of the assignments, how they are graded, and how to succeed in this class.

완료하는 데 2시간 필요

4개 동영상 (총 43분), 3 개의 읽기 자료, 1 개의 테스트

4개의 동영상

Course Promo1m

Course Motivation - Indiana Jones, challenges, applications20m

Course Introduction - philosophy, design, grading rubric11m

Assignments Introduction & Any Integer9m

3개의 읽기 자료

Start of Course Survey10m

Socialize10m

Course Syllabus10m

주

2

주 2

완료하는 데 7시간 필요

Knapsack

These lectures introduce optimization problems and some optimization techniques through the knapsack problem, one of the most well-known problem in the field. It discusses how to formalize and model optimization problems using knapsack as an example. It then reviews how to apply dynamic programming and branch and bound to the knapsack problem, providing intuition behind these two fundamental optimization techniques. The concept of relaxation and search are also discussed.

완료하는 데 7시간 필요

9개 동영상 (총 101분)

9개의 동영상

Knapsack 1 - intuition2m

Knapsack 2 - greedy algorithms7m

Knapsack 3 - modeling8m

Knapsack 4 - dynamic programming17m

Knapsack 5 - relaxation, branch and bound14m

Knapsack 6 - search strategies, depth first, best first, least discrepancy14m

Assignments Getting Started13m

Knapsack & External Solver10m

Exploring the Material - open course design, optimization landscape, picking your adventure10m

주

3

주 3

완료하는 데 17시간 필요

Constraint Programming

Constraint programming is an optimization technique that emerged from the field of artificial intelligence. It is characterized by two key ideas: To express the optimization problem at a high level to reveal its structure and to use constraints to reduce the search space by removing, from the variable domains, values that cannot appear in solutions. These lectures cover constraint programming in detail, describing the language of constraint programming, its underlying computational paradigm and how it can be applied in practice.

완료하는 데 17시간 필요

13개 동영상 (총 248분), 1 개의 읽기 자료, 2 개의 테스트

13개의 동영상

CP 1 - intuition, computational paradigm, map coloring, n-queens27m

CP 2 - propagation, arithmetic constraints, send+more=money26m

CP 3 - reification, element constraint, magic series, stable marriage16m

CP 4 - global constraint intuition, table constraint, sudoku19m

CP 5 - symmetry breaking, BIBD, scene allocation18m

CP 6 - redundant constraints, magic series, market split11m

CP 7 - car sequencing, dual modeling18m

CP 8 - global constraints in detail, knapsack, alldifferent33m

CP 9 - search, first-fail, euler knight, ESDD25m

CP 10 - value/variable labeling, domain splitting, symmetry breaking in search28m

Graph Coloring6m

Optimization Tools5m

Set Cover8m

1개의 읽기 자료

Optimization Tools10m

주

4

주 4

완료하는 데 13시간 필요

Local Search

Local search is probably the oldest and most intuitive optimization technique. It consists in starting from a solution and improving it by performing (typically) local perturbations (often called moves). Local search has evolved substantially in the last decades with a lot of attention being devoted on which moves to explore. These lectures explore the theory and practice of local search, from the concept of neighborhood and connectivity to meta-heuristics such as tabu search and simulated annealing.

완료하는 데 13시간 필요

10개 동영상 (총 191분)

10개의 동영상

LS 1 - intuition, n-queens13m

LS 2 - swap neighborhood, car sequencing, magic square15m

LS 3 - optimization, warehouse location, traveling salesman, 2-opt, k-opt23m

LS 4 - optimality vs feasibility, graph coloring22m

LS 5 - complex neighborhoods, sports scheduling21m

LS 6 - escaping local minima, connectivity15m

LS 7 - formalization, heuristics, meta-heuristics introduction22m

LS 8 - iterated location search, metropolis heuristic, simulated annealing, tabu search intuition18m

LS 9 - tabu search formalized, aspiration, car sequencing, n-queens26m

Traveling Salesman10m

주

5

주 5

완료하는 데 2시간 필요

Linear Programming

Linear programming has been, and remains, a workhorse of optimization. It consists in optimizing a linear objective subject to linear constraints, admits efficient algorithmic solutions, and is often an important building block for other optimization techniques. These lectures review fundamental concepts in linear programming, including the infamous simplex algorithm, simplex tableau, and duality. .

완료하는 데 2시간 필요

6개 동영상 (총 130분)

6개의 동영상

LP 1 - intuition, convexity, geometric view23m

LP 2 - algebraic view, naive algorithm13m

LP 3 - the simplex algorithm32m

LP 4 - matrix notation, the tableau20m

LP 5 - duality derivation22m

LP 6 - duality interpretation and uses17m

주

6

주 6

완료하는 데 12시간 필요

Mixed Integer Programming

Mixed Integer Programming generalizes linear programming by allowing integer variables, which dramatically changes the complexity of the problems but also broadens the potential applications significantly. These lectures review how to model problems in mixed-integer programming and how to solve mixed-integer programs using branch and bound. Advanced techniques such as cutting planes and polyhedral cuts are also covered.

완료하는 데 12시간 필요

6개 동영상 (총 136분)

6개의 동영상

MIP 1 - intuition, relaxation, branch and bound, knapsack, warehouse location26m

MIP 2 - modeling, big-M, warehouse location, graph coloring28m

MIP 3 - cutting planes, Gomory cuts20m

MIP 4 - convex hull, polyhedral cuts, warehouse location, node packing, graph coloring19m

MIP 5 - cover cuts, branch and cut, seven bridges, traveling salesman31m

Facility Location9m

주

7

주 7

완료하는 데 11시간 필요

Advanced Topics: Part I

These lectures cover some more advanced concepts in optimization. They introduce constraint-programming techniques for scheduling and routing.

완료하는 데 11시간 필요

2개 동영상 (총 51분)

2개의 동영상

Scheduling - jobshop, disjunctive global constraint37m

Vehicle Routing14m

주

8

주 8

완료하는 데 1시간 필요

Advanced Topics: Part II

These lectures continues to cover some more advanced concepts in optimization. They introduce large neighborhood search, which often combines constraint programming and local search, and column generation which decomposes an optimization model into a master and pricing problem, using more complex variables.

완료하는 데 1시간 필요

2개 동영상 (총 32분), 1 개의 읽기 자료

2개의 동영상

Large Neighborhood Search - asymmetric TSP with time windows8m

Column Generation - branch and price, cutting stock23m

1개의 읽기 자료

End of course survey10m

자주 묻는 질문

When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:

The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.

The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I purchase the Certificate?

When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
What is the refund policy?

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Is financial aid available?

Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You’ll be prompted to complete an application and will be notified if you are approved. Learn more.
• What are the pre-requisites for the class?

Good programming skills, knowledge of algorithms and linear algebra.
• What programming language will be used in this class?

A minimal knowledge of python is necessary to integrate with the course infrastructure. Outside of that, students are free to use any language of their choice.
• How difficult is this class?

A motivated student spending the time on the programming assignment will succeed in this class.
• Where can I get one of those T-Shirts?

At the discrete optimization store: http://www.zazzle.com.au/discreteoptimization

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