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It's not really clear in MGO, there is no declared step for fitness computation.
The step is embeded in elitism() function call during evolution, perhaps there is a better way to create a real function assignFitness() somewhere in the program.
The fitness step need to create a real value attached to each individual, because in many algorithms there are multiple real value fitness computed for each individual. For example, in MOGA or NSGA1 there is no elitism, and selection mechanism operate on full population.
Some examples :
For nsga 2 the real fitness assigned after NDS with elitism for each individual equal the front number.
For Nsga 1 one of the real fitness assigned after NDS without elitism for each individual equal the front number, then after a total fitness is computed using this fitness + niche count (another fitness)
For MOGA, one of real fitness assigned after paretoRanking for each individuals in population = number of dominated + 1
It seems we can cumulate multiple fitness for one individual, so we need a clear way to operate and cumulate this fitness.
The text was updated successfully, but these errors were encountered:
I don't know. Remark about elitism() function is cleary obsolete, but we need to check how the elitism is computed for the canonical algorithms NSGA1/2/MOGA.
It's not really clear in MGO, there is no declared step for fitness computation.
The step is embeded in elitism() function call during evolution, perhaps there is a better way to create a real function assignFitness() somewhere in the program.
The fitness step need to create a real value attached to each individual, because in many algorithms there are multiple real value fitness computed for each individual. For example, in MOGA or NSGA1 there is no elitism, and selection mechanism operate on full population.
Some examples :
It seems we can cumulate multiple fitness for one individual, so we need a clear way to operate and cumulate this fitness.
The text was updated successfully, but these errors were encountered: