Concept Design Mutations
The Research focus here will be how to build upon the foundations of evolutionary computation capabilities to move from optimized design to actually design the optimization.
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You can make an endless bubble diagram as an initial thought for your final design solution. We are usually the ones iterating over a design decision in order to evaluate its effectiveness. If we could abstract the forces which guide a design decision, then we could potentially utilize Evolutionary computation, and specifically Genetic Algorithms, to assist us in finding optimal solutions given a number of design criteria.
For this to work, we must know the design task very well. It’s parameters must be well defined into a ‘solution space’ bound by the ranges of our parameters. This is a space where good and bad solutions exist, and the Evolutionary Solver will search through it to find the best solutions.
Defining the total constructed site area is 700 sqm and space area proportions according to functions:
Genetic algorithm design solutions: Bubble Diagrams connectivity preferences.
Spatial Analysis: Depth of Connectivity.
Evolving Design Mutations:
Here it combines all functions space area together and then fits the total area volume and floors parameter and creating a mass as the fittest solution.