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Table 1 Operation description and related parameter in GA cycle

From: Liquefaction maps in Babol City, Iran through probabilistic and deterministic approaches

Operation Description Related Parameters Parameter description
Population GA starts with choice of some individuals (potential answers for the problem) generated using a random generator. The set of chosen values are called population and the first set is referred to as ‘initial population’. Members of the population are chosen to act as parents to produce children for next generation (next set of potential answers). Npop The size of the population is the number of the members that constitute the population. It is shown usually by parameter ‘Npop’. The number of initial population is a matter of concern and is usually adopted based on the sensitivity analysis. In this study, it is selected as Npop =50 after sensitivity analysis.
Generation In each cycle in GA, when the number of the produced children (new potential answers) is equal to the size of population(Np), then one generation is formed. MaxGen Maximum number of generation ‘MaxGen’ is a predefined number which is a criterion that checks the termination process. When MaxGen is reached, the GA process is terminated even if the convergence criterion is not satisfied.
Crossover Operates on two chromosomes and swaps some of their genes which creates two new chromosomes representing two new individuals. In GA context, these new individuals may be considered as new potential answers. Pc Crossover operation is carried in a probabilistic manner and hence a probability number is assigned to it which is referred to as ‘crossover probability’ or ‘Pc’. Similar to Npop, sensitivity analysis may be carried to select the best value for Pc or it may be adopted based on some other inference.
Mutation This operator occasionally changes the produced children (new potential answers) based on probabilistic principles by exchanging some of their genes and preserves the diversity of the population (set of potential answers) by introducing new members and also prevents the local optimums. Pm Mutation occurs probabilistically according to a chosen rate which, again, may be adopted based on sensitivity analysis. It implies on the probability for the mutation of a gene usually indexed by binary numbers ‘0’ and ‘1’ in the chromosomes’ string. If the total number of handled genes is assumed to be n, then Pm × n genes are mutated.