We empirically investigate the use of relocation operator as a local search operator, in combination with genetic search, in a Tree Adjoining Grammar Guided Genetic Programming system (TAG3P). The results show that, on all the problems we tried, the use of the relocation operator as a local search operator in TAG3P outperforms TAG3P using purely crossover and mutation, and also outperforms stan...

In this paper, we study the conditions in which the (1+1)-EA compares favorably to other evolutionary algorithms (EAs) in terms of tness distribution function at given iteration and the average optimization time. Our approach is applicable when the reproduction operator of an evolutionary algorithm is dominated by the mutation operator of the (1+1)-EA. In this case one can extend the lower boun...

In this paper, we study the conditions in which the (1+1)-EA compares favorably to other evolutionary algorithms (EAs) in terms of fitness function distribution at given iteration and with respect to the average optimization time. Our approach is applicable when the reproduction operator of an evolutionary algorithm is dominated by the mutation operator of the (1+1)-EA. In this case one can ext...

The problem of teacher placement in a school is faced by Magelang Regency. success determined the minimum total distance between and school, with aim that performance maintained. In computer science this an NP-hard takes very long time to achieve optimal results when done conventional methods. Another approach solve use heuristic algorithms, one which using genetic algorithms. To further improv...

In this paper we present two sets of empirical data evaluating the performance of a new Cleanup operator for evolutionary approaches to the travelling salesman problem (TSP). For raw data we have used standard road mileage charts of the USA, Great Britain and Ireland, which enable us to generate a reference table with appropriate city to city distances. A wide variety of standard genetic parame...

Estimation of distribution algorithms (EDAs) constitute a new branch of evolutionary optimization algorithms that were developed as a natural alternative to genetic algorithms (GAs). Several studies have demonstrated that the heuristic scheme of EDAs is effective and efficient for many optimization problems. Recently, it has been reported that the incorporation of mutation into EDAs increases t...

Using recursion formulas for vertex operator algebra higher genus characters with formal parameters identified local coordinates around marked points on a Riemann surface of arbitrary genus, we introduce the notion cluster structure. Cluster elements and mutation rules are explicitly defined, simplest example is presented.

The performance of the evolutionary algorithms depends strongly upon the combined eeect of the operators (e.g. mutation) and the mappings from genotype to phenotype space and phenotype to t-ness space. We demonstrate, with the example of the canonical Genetic Algorithm (cGA) for parameter optimization, that the right choice of the mutation operator should depend on the genom position and we sho...

Evolution strategy (ES) and particle swarm optimization (PSO) are two of the most popular research topics for tackling real-parameter optimization problems in evolutionary computation. Both of them have strengths and weaknesses for their different search behaviors and methodologies. In ES, mutation, as the main operator, tries to find good solutions around each individual. While in PSO, particl...

Proper coloring of the vertices of a graph with minimum number of colors has always been of great interest of researchers in the field of soft computing. Genetic Algorithm (GA) and its application as the solution method to the Graph Coloring problem have been appreciated and worked upon by the scientists almost for the last two decades. Various genetic operators such as crossover and mutation h...