Influence of the number of individuals on the genetic algorithms performance

View other case studies


Case study 1: Parameter identification of an model of E. coli fed-batch cultivation process
Data contain results from parameter identification procedures using Genetic algorithm (GA) with 14 different values of parameter ‘number of individuals’ (nind) for 30 different runs of the 14 GAs. In this way, we obtain 14 index matrices with 30 objects O1, …, O30 :
• model parameters estimates (C1–C3),
GA outcomes – objective function value and computation time (C5 and C6),
where Ci are ‘criteria’ in terms of ICA.
Download

Data contain results from parameter identification procedures using Genetic algorithm (GA) with 14 different values of parameter ‘number of individuals’ (nind) for 30 different runs of the 14 GAs. Download

Data contain results from parameter identification procedures using Genetic algorithm (GA) with 14 different values of parameter ‘number of individuals’ (nind) for 30 different runs of the 14 GAs. In this way, we obtain 3 index matrices for each of the three model parameters with 30 objects Run1, …, Run30 and 14 GAs (GA5, GA10, GA20, …, GA100, GA110, GA150, GA200), Download

Comments are closed.