New knowledge-based genetic algorithm for excavator boom structural optimization

Modeling and Simulation of Production of Metallothionein and Red Fluorescent Fusion Protein by Recombinant Escherichia Coli Using LabVIEW

“…1. Genetic algorithm is a search heuristic that mimics the process of natural evolution,which is proved useful in solving sophisticated optimization problems as well as in optimization of biological model parameters.A standard GA is used in the optimization,which has the operations of coding,initialization,mutation,hybridization,decoding,fitne ss,calculation,selection,and reproduction procedures exerted on individuals(or chromosomes) in a population [10].The potential solution(individual) is coded as a binary vector,called a chromosome,the elements of which were called genes and situated in predefined positions,indicated as alleles [11].One gene codes for one model parameter.The gene number n of one chromosome equals to the number of model parameters,so that each chromosome codes for all parameters of the model and enable to calculate the model prediction error with the set of model parameters coded by the chromosome.In GA,one population contains m individuals (or chromosomes) so that m model prediction errors can be calculated for the m chromosomes,and the fitness of each chromosome can then be calculated and used for the selection procedure.In this study,one gene is coded by a binary string of 10 bits.Then,n parameters are represented by a binary string of 10  n bits.The population of m chromosomes can be…”