Evolutionary Algorithms and Design

Jonathan Byrne

Natural Computing Research and Applications Group

University College Dublin

Ireland

Evolutionary Algorithms (EA)

  • Population based optimiser
  • Inspired by biological evolution
  • Probabilistic Approach

Applications

  • Large scale optimisation algorithms
  • Transport and routing
  • Scheduling
  • Bioinformatics

Design Problems

  • Open ended
  • Use the computer as an active design tool

The Algorithm:

  • Select (fitness pressure)
  • Crossover (heredity)
  • Mutate (variation)
  • Repeat

Evolving a Vehicle

Car GA

Electricity Pylon Design

RIBA Competition

  • Royal Institute of British Architects design competition
  • Pre-specified loading conditions
  • Use structural analysis as fitness function

Loading Constraints

Example Loading

Wind Loading

Ice Loading

Wind and Ice Loading

Multi-objective Optimisation

  • Conflicting Objectives
  • Requires a trade off

Lift vs Drag

Initial Generation

Evolving the Pareto Front

Final Generation

Optimised Blended Wing Body Designs

Optimised Cessna 182 Designs

Applications

Shinkansen

Shinkansen

NASA Antenna

Fibre Optics

Collaborations

  • Bridge Design: Elizabeth Shotton
  • Truss Optimisation: Ciaran McNally