Simple Genetic Algorithm (SGA) as feature selector, route optimization for home care service with SGA and semantic segmentation using Multiobjective Genetic Algorithm (MOGA)
Figure out where the crossover point should be. Now it is set to 0.5 (at the middle, floored). It should be somewhere in the range of 1-(size_individual-1). Meaning, cannot be the first or last element in the array, but somewhere in-between.
Basically: crossover_point: (0, size_individual) -> [1, size_individual-2]
Figure out where the crossover point should be. Now it is set to 0.5 (at the middle, floored). It should be somewhere in the range of 1-(size_individual-1). Meaning, cannot be the first or last element in the array, but somewhere in-between. Basically:
crossover_point: (0, size_individual) -> [1, size_individual-2]