COMPX556-22B (HAM)

Metaheuristic Algorithms

15 Points

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Division of Health Engineering Computing & Science
School of Computing and Mathematical Sciences
Department of Computer Science

Staff

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Convenor(s)

Michael Mayo

Michael Mayo
4403
G.2.24
See Moodle
michael.mayo@waikato.ac.nz

Lecturer(s)

Administrator(s)

: buddhika.subasinghe@waikato.ac.nz

Placement/WIL Coordinator(s)

Tutor(s)

Student Representative(s)

Lab Technician(s)

Librarian(s)

: alistair.lamb@waikato.ac.nz

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Paper Description

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This paper explores common metaheuristic algorithms such as variable neighbourhood search and mimetic algorithms, and their application in areas such as science, engineering and health informatics.

The learning outcomes for this paper are linked to Washington Accord graduate attributes WA1-WA11. Explanation of the graduate attributes can be found at: https://www.ieagreements.org/

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Paper Structure

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The paper involves involves a mixture of online videos and in person or opportunities for discussion.
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Learning Outcomes

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Students who successfully complete the paper should be able to:

  • Apply metaheuristic algorithms for solving difficult optimisation problems (WA1,WA2,WA3)
    Linked to the following assessments:
  • Communicate the results of a experimental algorithmic investigation in writing (WA3,WA4,WA9)
    Linked to the following assessments:
  • Collaborate with peers to solve open ended algorithmic challenge problems (WA8,WA9,WA10)
    Linked to the following assessments:
  • Be familiar with the broad landscape of metaheuristic algorithms and recognise when to use them in the wider engineering context (WA11)
    Linked to the following assessments:
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Assessment

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This paper is 100% internal assessment.

If you are enrolled in a BE(Hons), samples of your work may be required as part of the Engineering New Zealand accreditation process for BE(Hons) degrees. Any samples taken will have the student name and ID redacted. If you do not want samples of your work collected then please email the engineering administrator, Natalie Shaw (natalie.shaw@waikato.ac.nz), to opt out.

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Assessment Components

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The internal assessment/exam ratio (as stated in the University Calendar) is 100:0. There is no final exam. The final exam makes up 0% of the overall mark.

The internal assessment/exam ratio (as stated in the University Calendar) is 100:0 or 0:0, whichever is more favourable for the student. The final exam makes up either 0% or 0% of the overall mark.

Component DescriptionDue Date TimePercentage of overall markSubmission MethodCompulsory
1. Assignment 1
8 Aug 2022
12:00 AM
25
  • Online: Submit through Moodle
2. Assignment 2
22 Aug 2022
12:00 AM
25
  • Online: Submit through Moodle
3. Project
31 Oct 2022
12:00 AM
50
  • Online: Submit through Moodle
✔
Assessment Total:     100    
Failing to complete a compulsory assessment component of a paper will result in an IC grade
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Required and Recommended Readings

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Required Readings

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Handbook of Metaheuristics, 3rd Edition, currently available for free via the library

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Recommended Readings

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Additional readings will be supplied on Moodle.
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Other Resources

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In addition to the readings, students should be familiar with the parallel programming capabilities of at least one programming language.
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Online Support

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Lectures for this course will be in the form on online videos. Moodle and email will be available for discussions and questions. Students will be able to interact with the lecturer both online and in person.
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Workload

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The expected workload is about 10 hours per week for the 15 teaching weeks of the semester.
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Linkages to Other Papers

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Prerequisite(s)

Prerequisite papers: COMPX301 and a further 30 points at 300 level in Computer Science

Corequisite(s)

Equivalent(s)

Restriction(s)

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