Genetic Programming often uses excessive computational resources because the population size and the maximum number of generations per run are not optimized. We have developed a technique called Virtual Ramping which eliminates the need to find an optimal value for these parameters and allows GP to be applied effectively to more difficult problems. Virtual Ramping continuously increases the siz...

To exploit an evolutionary algorithm’s performance to the full extent, the selection scheme should be chosen carefully. Empirically, it is commonly acknowledged that low selection pressure can prevent an evolutionary algorithm from premature convergence, and is thereby more suitable for wide-gap problems. However, there are few theoretical time complexity studies that actually give the conditio...

Nowadays Traditional Genetic Algorithm has already been applied in a good many domains as a kind of nonnumeric vale calculation optimum method. But this algorithm self has deficiencies that “premature convergence”, low ability of local searching, no norms in encoding, and failing to express constraint conditions of problem, which have limited to its application. So Partheno-Genetic Algorithm (P...

Competitive fitness is the assessment of an individual’s fitness in the context of competition with other individuals in the evolutionary system. This commonly takes one of two forms: one-population competitive fitness, where competition is solely between individuals in the same population; and N-population competitive fitness, often termed competitive coevolution. In this paper we discuss comm...

Abstract Aiming at the premature convergence problem of particle swarm optimization (PSO) due to loss population diversity in late stage search, this paper improves traditional PSO and proposes elite mean deviation induction strategy, which speed accuracy PSO. The experimental results show that improved are improved. effectiveness algorithm is proved.

Nephron progenitor cells differentiate to form nephrons during embryonic kidney development. In contrast, self-renewal maintains progenitor numbers and premature depletion leads to impaired kidney function. Here we analyze the PI3K pathway as a point of convergence for the multiple pathways that are known to control self-renewal in the kidney. We demonstrate that a reduction in PI3K signaling t...

Software test is usually costly and vital in software development lifecycle. Though genetic algorithms have the globally searching capability, premature convergence and weak local optimization are two key problems existing in the conventional genetic algorithm. This paper introduces particle swarm optimization into genetic algorithm to breed software test data automatically. The GPSMA (Genetic-...

the travelling salesmen problem (tsp) is one of the most important and famous combinational optimization problems that aim to find the shortest tour. in this problem, the salesman starts to move from an arbitrary place called depot and after visiting all nodes, finally comes back to depot. solving this problem seems hard because program statement is simple and leads this problem belonging to np...

In this paper, a genetic algorithm with minimum description length (GAWMDL) is proposed for grammatical inference. The primary challenge of identifying a language of infinite cardinality from a finite set of examples should know when to generalize and specialize the training data. The minimum description length principle that has been incorporated addresses this issue is discussed in this paper...