Genetic Algorithms with Variable Length Chromosomes for High Constraint Problems in Spatial Data

Constraint handling is the main task in constrained optimization problems. Variable length chromosomes in the genetic algorithm has been used widely for faster computation, but in this study it was used to handle the constraint as well. This method uses the characteristic of the genetic algorithm with bit-strings conversion from real numbers. By the bit-strings format, the population of the candidates can be limited only in the study area where it is impossible when the real number format is used. Therefore, it will reduce the searching area and make the optimization process faster. Variable length chromosomes method can also be integrated with another constraint handling, i.e. the death penalty method. The results showed that the proposed method was able to optimize land use in Bekasi City, Indonesia, as a case study.