Searching for the optimal coding in genetic algorithms
M. Coli, Paolo Palazzari · 1995
Genetic Algorithms convergence depends on the qrialig of the building blocks present in the population (building block hypothesis). We formallj define the building blocks and the coding function and we demonstrate that building blocks present in a population depend on the used coding function; by assuming the building block hypothesis to be true, the convergence of GAS depends on the used codingfunction. We present a method which finds a coding function allowing meaningful building blocks to be obtained and improving GAS convergence. We give a quantitative criteriorr to measure the 'quality' of each coding function: the research for the optimal coding is formalized as a minimization problem which is solved through GAS. coding resulting from the use of the method described in the paper. We present some examples which demonstrate the improvement in GAS convergence obtained through the