This paper presents some theoretical convergence characteristics of Keep-Best Reproduction (KBR), a selection strategy for genetic algorithms (GAs). We have previously introduced KBR and reported encouraging results in the traveling salesman domain (Wie98a) where KBR was compared with the standard replacement strategy of replacing the two parents by their two children (STDS). Here we demonstrat...

Particle Swarm Optimization (PSO) algorithm is a new optimization approach, which has been widely used to solve various and complex optimization problems. However, there are still some imperfections, such as premature convergence and low accuracy. To address such defects, an improved PSO is proposed in this paper. The improved PSO algorithm introduces a uniform search strategy that makes partic...

abstract background: parent–infant attachment is an important factor in accepting parenting role, accelerating infant survival, and adjusting to the environment outside the uterus. since family supportive interventions can strengthen the parent–infant caring relationship, this study sought to investigate the relationship between mother–infant attachment and satisfaction of the mothers with the ...

Genetic Algorithm (GA), which borrows the idea of Darwinian principle of natural selection, is a powerful global search and optimization method. This paper presents a SPMD(Single Program Multiple Data) algorithm which combines GA with local searching algorithm – uphill. The hybrid parallel method not only improves the convergence of GA but also accelerates the convergence speed of GA. Approxima...

In view of the slowness and the locality of convergence for Simple Genetic Algorithm (SGA) in solving complex optimization problems, we propose an improved genetic algorithm named Multi-Stage Composite Genetic Algorithm (MSC-GA) through reducing the optimization-search range gradually, and the structure and implementation steps ofMSC-GA is also discussed. Then, we consider its global convergenc...

This paper presents a modification of tlte panicle swarm optimization algorithm (PSO) intended to combat the problem ofpremature convergence observed in many applications of PSO. The proposed new algorithm moves particles towards neorby particles of higher fitness, instead of amacting each panicle towards just the best position discovered so far by any particle. This is accomplished by using th...

Aiming at the phenomenon of slow convergence rate and low accuracy of bat algorithm, a novel bat algorithm based on differential operator and Lévy flights trajectory is proposed. In this paper, a differential operator is introduced to accelerate the convergence speed of proposed algorithm, which is similar to mutation strategy "DE/best/2" in differential algorithm. Lévy flights trajectory can e...

Population diversity is one of the most important factors that influence the convergence speed and evolution efficiency of gene expression programming (GEP) algorithm. In this paper, the population diversity strategy of GEP (GEP-PDS) is presented, inheriting the advantage of superior population producing strategy and various population strategy, to increase population average fitness and decrea...

This paper proposes a self-organizing genetic algorithm (SOGA) with good global search properties and a high convergence speed. First, we introduce a new dominant selection operator that enhances the action of the dominant individuals, along with a cyclical mutation operator that periodically varies the mutation probability in accordance with evolution generation found in biological evolutionar...

In terms of the concepts of state and state transition, a new heuristic random search algorithm named state transition algorithm is proposed. For continuous function optimization problems, four special transformation operators called rotation, translation, expansion and axesion are designed. Adjusting measures of the transformations are mainly studied to keep the balance of exploration and expl...