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Operations Research (1): Models and Applications

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Operations Research (1): Models and Applications

This course is part of Operations Research Specialization

Instructor: 孔令傑 (Ling-Chieh Kung)

46,950 already enrolled

Included with

Learn more

6 modules

Gain insight into a topic and learn the fundamentals.

584 reviews

Beginner level

Recommended experience

Flexible schedule

1 week at 10 hours a week

Learn at your own pace

96%

Most learners liked this course

6 modules

Gain insight into a topic and learn the fundamentals.

584 reviews

Beginner level

Recommended experience

Flexible schedule

1 week at 10 hours a week

Learn at your own pace

96%

Most learners liked this course

What you'll learn

Formulate different types of mathematical models to tackle optimization problems with business applications.
Technically, the concepts and applications of Linear Programming, Integer Programming, and Nonlinear Programming will be delivered.
Solve an optimization problem with one of the most accessible software: Microsoft Excel.

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

6 assignments

Taught in English

91% of learners achieved a positive career outcome

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Build your subject-matter expertise

This course is part of the Operations Research Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 6 modules in this course

Operations Research (OR) is a field in which people use mathematical and engineering methods to study optimization problems in Business and Management, Economics, Computer Science, Civil Engineering, Industrial Engineering, etc. This course introduces frameworks and ideas about various types of optimization problems in the business world. In particular, we focus on how to formulate real business problems into mathematical models that can be solved by computers.

Module details

This lecture gives students an overview of what they may expect from this course, including the fundamental concept and brief history of Operations Research. We will also talk about how mathematical programming can be used to solve real-world business problem.

What's included

6 videos1 reading1 assignment

Linear programming (LP) is one of the most important method to achieve the outcome of optimization problems. We can use LP models for various decisions, including production, inventory, personnel scheduling, etc.

What's included

15 videos1 assignment

15 videosTotal 129 minutes

2-0: Opening. 5 minutes
2-1: Introduction.3 minutes
2-2: Elements of a mathematical program (1).9 minutes
2-3: Elements of a mathematical program (2).13 minutes
2-4: Linear programming.7 minutes
2-5: Graphical approach.13 minutes
2-6: Three types of LPs.7 minutes
2-7: Simple LP formulation - Product mix.13 minutes
2-8: Simple LP formulation - Production and inventory.14 minutes
2-9: Simple LP formulation - Personnel scheduling.8 minutes
2-10: Compact LP formulation - Production and Inventory.11 minutes
2-11: Compact LP formulation – Product mix.8 minutes
2-12: Computers – The Solver add-in and Example 1 – producing desks and tables. 9 minutes
2-13: Computers – Example 2: personnel scheduling.4 minutes
2-14: Closing remarks.6 minutes

1 assignmentTotal 20 minutes

Quiz for Week 220 minutes

In many practical areas, some of the optimization problems occur with integrality constraints imposed on some of the variables. Facility location, machine scheduling, and vehicle routing are some examples. Integer Programming (IP) provides a mathematical way to solve these problems.

What's included

15 videos1 assignment

15 videosTotal 128 minutes

3-0: Opening.6 minutes
3-1: Introduction.8 minutes
3-2: IP formulation (1).11 minutes
3-3: IP formulation (2).9 minutes
3-4: Facility location – Overview.5 minutes
3-5: Facility location – Covering.10 minutes
3-6: Facility location - UFL.9 minutes
3-7: Machine scheduling - Overview.8 minutes
3-8: Machine scheduling - Completion time minimization.12 minutes
3-9: Machine scheduling - Makespan minimization.7 minutes
3-10: Traveling salesperson problem - Basics.11 minutes
3-11: Traveling salesperson problem - Subtour elimination.13 minutes
3-12: Computers – Example 1 – personnel scheduling.4 minutes
3-13: Computers – Example 2 – facility location.6 minutes
3-14: Closing remarks. 8 minutes

1 assignmentTotal 20 minutes

Quiz for Week 320 minutes

In the real life, many problems involve nonlinearities. Examples include pricing, inventory, and portfolio optimization. For such problems, we may use Nonlinear Programming (NLP) to formulate them into models and solve them.

What's included

15 videos1 assignment

15 videosTotal 114 minutes

4-0: Opening.5 minutes
4-1: Introduction.12 minutes
4-2: The EOQ problem.9 minutes
4-3: Formulating the EOQ model.9 minutes
4-4: The portfolio optimization problem.8 minutes
4-5: Portfolio optimization.9 minutes
4-6: Linearizing an absolute value function.10 minutes
4-7: Linearizing max_min functions.11 minutes
4-8: Linearizing products 1A.6 minutes
4-9: Linearizing products 1B 1C and 1D.8 minutes
4-10: Linearizing products 2A.5 minutes
4-11: Linearizing products 2B, 2C, and 2D. 10 minutes
4-12: Remarks - why linearization.3 minutes
4-13: Computers – Portfolio optimization problem. 5 minutes
4-14: Closing remarks.2 minutes

1 assignmentTotal 20 minutes

Quiz for Week 420 minutes

In this lecture, we introduce a real business case that has been solved with Operations Research by the instructor. The problem is for a company to schedule its customer service representatives to minimize the total amount of staff shortage. We will demonstrate the problem, process of conducting an OR study, integer programming formulation, and result.

What's included

9 videos1 assignment

9 videosTotal 69 minutes

5-0: Opening.4 minutes
5-1: Background and motivation.6 minutes
5-2: Research objective.8 minutes
5-3: Problem description - objective.9 minutes
5-4: Problem description - constraints.8 minutes
5-5: Model formulation - objective.11 minutes
5-6: Model formulation - constraints.11 minutes
5-7: Results.9 minutes
5-8: Closing remarks.3 minutes

1 assignmentTotal 20 minutes

Quiz for Week 520 minutes

In the final lecture of this course, we will summarize what we have learned. We will also preview what we may learn in future courses.

What's included

3 videos1 assignment

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Instructor

Instructor ratings

(213 ratings)

孔令傑 (Ling-Chieh Kung)

National Taiwan University

9 Courses112,311 learners

Offered by

National Taiwan University

Learner reviews

5 stars
86.66%
4 stars
11.96%
3 stars
0.51%
2 stars
0%
1 star
0.85%

Showing 3 of 584

Reviewed on Jun 25, 2021

great course for beginners, got new insights about how to formulate a model for practical issues

Reviewed on Jul 13, 2022

Nice course but content is mainly forcused on theory. In some points I wondered what is the logic behind these theories

Reviewed on Sep 28, 2022

This course just opened my eyes to real value of mathematical operation in different business and now I am much more competent for jobs which need high knowledge of operational research.

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