An Evolutionary Approach To Space Layout Planning Using Genetic Algorithm

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An Evolutionary Approach To Space Layout Planning
Using Genetic Algorithm

• By Hoda Homayouni

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Introduction to Space Layout Planning

• What is Space Layout Planning?
• Motivation
• Challenges
• Solving ill defined problems
• Addressing qualitative constraints
• Having creativity
• Compatibility with architects

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Introduction to Genetic Algorithm

• Computer Algorithm that resides on principles of
  genetic and evolution.

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Why Genetic Algorithm?

• Hill climbing

global
local
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Why Genetic Algorithm?

• Multi-climbers

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Why Genetic Algorithm?

• Genetic algorithm

I am at the top Height is ...
I am not at the top. My high is better!
I will continue
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Why Genetic Algorithm?

• Genetic algorithm
• few microseconds after

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Encoding Chromosomes

• The chromosome should in some way contain
  information about solution which it represents

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Crossover

• Crossover selects genes from parent chromosomes
  and creates a new offspring

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Mutation

• This is to prevent falling all solutions in
  population into a local optimum of solved problem

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Fitness Function

• Fitness function is evaluation function,that
  determines what solutions are better than others.
• Fitness is computed for each individual.
• Fitness function is application depended.

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Algorithmic Phases
Initialize the population
Select individuals for the mating pool
Perform crossover
Perform mutation
Insert offspring into the population
Stop?
no
yes
The End
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Genetic Engineering Approach

• An object can be described by the location of
  units and can be grown by locating a required
  number of such units, one at a time in sequence.

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Genetic Engineering
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Evolving Complex Design Genes Using a
Hierarchical Growth Approach
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Generating Units
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Crossover at Room Level
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Crossover at Room Level
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Crossover at Site Level
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Initial Living Zone Population
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Evolved Population
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Initial House population
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Evolved Population
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Discussion

• More Fitness Functions
• Architects Role?

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References

• Rosenman, M.A. (1997). The Generation of form
  using evolutionary approach. Evolutionary
  algorithms in Engineering Applications. Springer,
  1997.
• Rosenman, M.A. and Gero, J.S. (1999) Evolutionary
  designs by generating useful complex gene
  structures. Evolutionary Design by Computers,
  Morgan Kaufmann, San Francisco, pp.345-364.
• http//galeb.etf.bg.ac.yu/vm/GenAlgo.ppt