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Advanced Modeling for Discrete Optimization
  • Level Professional
  • Duration 47 hours
  • Course by The University of Melbourne
  • Offered by

About

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 who have completed Basic Modelling for Discrete Optimization. In this course you will learn much more about solving challenging discrete optimization 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 course will focus on debugging and improving models, encapsulating parts of models in predicates, and tackling advanced scheduling and packing problems. As you master this advanced technology, you will be able to tackle problems that were inconceivable to solve previously. Watch the course promotional video here: https://www.youtube.com/watch?v=hc3cBvtrem0&t=8s

Modules

Course Preliminaries

    • 1 Videos
    • 3 Readings
Show info about module content

1 Videos

  • Welcome to Advanced Modeling for Discrete Optimization

3 Readings

  • Course Overview
  • Start of Course Survey
  • “Building Decision Support Systems using MiniZinc” by Professor Mark Wallace

Debugging and Improving Models

    • 7 Videos
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7 Videos

  • 2.1.1 Model Debugging
  • 2.1.2 Tracing Models
  • 2.1.3 Relational Semantics
  • 2.1.4 Too Many Solutions
  • 2.1.5 Missing Solutions
  • 2.1.6 Basic Model Improvement
  • 2.1.7 Module 1 Summary

Activities

    • 3 Videos
    • 2 Readings
    • 1 Programming
Show info about module content

1 Programming

  • Escape to Jing Province

3 Videos

  • Workshop 5 Solution
  • Assignment Submission - IDE
  • Assignment Submission - CLI

2 Readings

  • Getting MiniZinc
  • Workshop 5: Poetry Challenge

Reference Material (Optional)

    • 11 Videos
    • 1 Readings
Show info about module content

11 Videos

  • Reference 1: Basic Features
  • Reference 2: Booleans Expressions
  • Reference 3: Sets, Arrays and Comprehensions
  • Reference 4: Enumerated Types
  • Reference 5: Strings and Output
  • Reference 6: Option Types
  • Reference 7: Predicates
  • Reference 8: Flattening
  • Reference 9: Transforming Data
  • Reference 10: User Defined Functions
  • Reference 11: Command Line Interface

1 Readings

  • About the Reference Material

Predicates

    • 5 Videos
Show info about module content

5 Videos

  • 2.2.1 Predicates
  • 2.2.2 The let-in Construct
  • 2.2.3 Using Predicates
  • 2.2.4 Contexts
  • 2.2.5 Module 2 Summary

Activities

    • 1 Videos
    • 1 Readings
    • 1 Programming
Show info about module content

1 Programming

  • Weighing the Elephant

1 Videos

  • Workshop 6 Solution

1 Readings

  • Workshop 6: Weighing an Elephant: Part 1

Scheduling

    • 6 Videos
Show info about module content

6 Videos

  • 2.3.1 Basic Scheduling
  • 2.3.2 Disjunctive Scheduling
  • 2.3.3 Cumulative Scheduling
  • 2.3.4 Sequence Dependent Scheduling 1
  • 2.3.5 Sequence Dependent Scheduling 2
  • 2.3.6 Module 3 Summary

Activities

    • 1 Videos
    • 1 Readings
    • 1 Programming
Show info about module content

1 Programming

  • Suitor Schedule

1 Videos

  • Workshop 7 Solution

1 Readings

  • Workshop 7: Visiting Zhuge Liang

Packing

    • 3 Videos
Show info about module content

3 Videos

  • 2.4.1 Square Packing
  • 2.4.2 Rectilinear Packing without Rotation
  • 2.4.3 Rectilinear Packing with Rotation

Symmetry and Dominance

    • 5 Videos
    • 1 Readings
Show info about module content

5 Videos

  • 2.5.1 Symmetries and LexLeader
  • 2.5.2 Matrix Model Symmetries
  • 2.5.3 Value Symmetries
  • 2.5.4 Dominance
  • 2.5.5 Module 4 & 5 Summary

1 Readings

  • Where to from here?

Activities

    • 1 Videos
    • 2 Readings
    • 1 Programming
Show info about module content

1 Programming

  • To Borrow Arrows from Thatched Boats

1 Videos

  • Workshop 8 Solution

2 Readings

  • Workshop 8: The Dieda Plasters
  • End of Course Survey

Auto Summary

Advanced Modeling for Discrete Optimization, offered by Coursera, is perfect for IT and computer science professionals looking to enhance their problem-solving skills. This course teaches advanced techniques in high-level modeling languages for discrete optimization, focusing on debugging, model improvement, and solving complex scheduling and packing problems. Led by expert instructors, the course spans 2820 minutes and is available through Starter and Professional subscription options. Ideal for those who have completed Basic Modeling for Discrete Optimization and want to tackle previously unsolvable challenges. Join to elevate your decision-making and optimization capabilities.

Prof. Jimmy Ho Man Lee
Instructors

Prof. Jimmy Ho Man Lee

Prof. Peter James Stuckey
Instructors

Prof. Peter James Stuckey