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Under construction. This area is a framework being built: most courses have no teaching material yet, and things may change or break. Private self-study. Not an official programme and not recognised by any ministry or school. No qualification, mark or document is issued, and “years 1 to 3” and “advanced” are names of study paths only.

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E33 Evolutionary and swarm optimization

Years 1 to 3 pathE: Proposed extensionsplannedabout 100 h (planning estimate)

Planned: syllabus only, no teaching material yet. Nothing on this page can be studied; it describes what the course would cover.

Named in: Years 1 to 3 pathway

Why this course

Metaheuristics are common in applications; the mathematics of why and when they work is rarely taught.

Prerequisites

Required
B05 Discrete mathematics, B11 Probability I, B20 Optimization I
Recommended
none
Can be taken at the same time
none
Everything required, transitively (11 courses)
B01, B02, B03, B04, B05, B06, B08, B11, B20, F01, F02
Courses that require this one
none

Concept-level units

Units follow the syllabus order, as a recommended sequence rather than a gate.

  1. Black-box optimization and the no-free-lunch theorems
  2. Genetic algorithms and schema theory
  3. Evolution strategies and CMA-ES
  4. Particle swarm optimization and convergence analysis
  5. Ant colony optimization
  6. Simulated annealing and Markov-chain analysis
  7. Multi-objective optimization and Pareto fronts
  8. Benchmarking fairly

Assessable outcome

Run, analyse and honestly compare two metaheuristics on a benchmark, with a convergence argument for one.

Assessment design

  • topic exercises
  • mixed problem sets
  • unseen proof or derivation problems
  • cumulative examination

cumulative; uses spaced retrieval

Resources

Every title here is candidate, unverified unless marked verified. Titles were suggested while planning. Nobody has checked that they exist, what they cost or how they are licensed.

  • Eiben and Smith · Introduction to Evolutionary Computing
  • Kennedy and Eberhart · Particle swarm optimization (paper)
  • Hansen · The CMA Evolution Strategy: A Tutorial (free)

Content record

Version
0.0.0
Review
no review of any kind
Provenance
PROPOSED by the assistant on 4 Nov 2026 so that a person with a mathematics degree can read AI articles fluently; not in the owner's brief; APPROVED by the owner on 4 Nov 2026 as an elective; still needs a curriculum reviewer
Known issues
  • Approved as an elective on 4 Nov 2026; syllabus only, no lessons, candidate resources unverified, needs a curriculum reviewer.
Type
course

Bridges and laboratories

No bridge or laboratory is attached to this course yet.

You and this course

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