Fitness distance correlation has been proposed as an analysis tool for the fitness function landscape of genetic algorithms. It has been shown that it works in some cases, but there are also counterexamples. We studied the fitness distance correlation and the optimal population size by two fitness functions with a translational minimum and with a meta-genetic algorithm. We discovered that the f...

This paper describes a genetic algorithm application to the DNA sequence assembly problem. The genetic algorithm uses a sorted order representation for representing the orderings of fragments. Two different fitness functions, both based on pairwise overlap strengths between fragments, are tested. The paper concludes that the genetic algorithm is a promising method for fragment assembly problems...

The evolution scheme phase, in which the genetic algorithms select individuals that will form new population, had an important impact on these algorithms. Many approaches exist literature. However, consider only value of fitness function to differenciate best solutions from worst ones. This article introduces parenting fitness, a novel parameter, defines capacity individual produce fittest offs...

in practice, obtaining the global optimum for the economic dispatch {bf (ed)}problem with ramp rate limits and prohibited operating zones is presents difficulties. this paper presents a new andefficient method for solving the economic dispatch problem with non-smooth cost functions using afuzzy adaptive genetic algorithm (faga). the proposed algorithm  deals  with the issue ofcontrolling the ex...

This paper is concerned with the determination of optimal sensor locations for structural modal identification in a strap-braced cold formed steel frame based on an improved genetic algorithm (IGA). Six different optimal sensor placement performance indices have been taken as the fitness functions two based on modal assurance criterion (MAC), two based on maximization of the determinant of a Fi...

This paper presents a Genetic algorithm based association rule mining in which multi fitness functions are used. Genetic algorithm is used for performing global search. This proposed algorithm generates intersecting association rules from dataset. A fitness function with parameter support is defined for generating frequent itemsets and then other parameters like confidence, lift, leverage etc a...

This paper presents a Genetic algorithm based association rule mining in which multi fitness functions are used. Genetic algorithm is used for performing global search. This proposed algorithm generates intersecting association rules from dataset. A fitness function with parameter support is defined for generating frequent itemsets and then other parameters like confidence, lift, leverage etc a...