BACKGROUND Offering patients in oncology trials the opportunity to cross over to active treatment at disease progression is a common strategy to address ethical issues associated with placebo controls but may lead to statistical challenges in the analysis of overall survival and cost-effectiveness because crossover leads to information loss and dilution of comparative clinical efficacy. OBJEC...

Differential Evolution (DE) is arguably one of the most powerful stochastic real parameter optimization algorithms in current use. DE operates through the similar computational steps as employed by a standard Evolutionary Algorithm (EA). However, unlike the traditional EAs, the DEvariants perturb the current-generation population members with the scaled differences of randomly selected and dist...

Genetic Algorithm (GAs) is used to solve optimization problems. It is depended on the selection operator, crossover and mutation rates. In this paper Roulette Wheel Selection (RWS) operator with different crossover and mutation probabilities, is used to solve well known optimization problem Traveling Salesmen Problem (TSP). We have compared the results of RWS with another selection method Stoch...

We introduce anisotropic bond percolation in which there exist different occupation probabilities for bonds placed in different coordinate directions. We study in detail a d-dimensional hypercubical lattice, with probabilities p I for bonds within (d 1)-dimensional layers perpendicular to the z direction, and p11= Rp, for bonds parallel to z . For this model, we calculate low-density series for...

Crossover operator plays a crucial role in the efficiency of genetic algorithm (GA). Several crossover operators have been proposed for solving the travelling salesman problem (TSP) in the literature. These operators have paid less attention to the characteristics of the traveling salesman problem, and majority of these operators can only generate feasible solutions. In this paper, a crossover ...

Genetic Algorithms (GAs) application in the field of water resources engineering is of recent origin. Genetic Algorithms is one of the tools, which handles nonlinear optimization problems in an efficient manner. Optimal reservoir operation of reservoir for hydropower production involves constrained nonlinear optimization. The constrained problem is converted into unconstrained problem by using ...

This paper is the second part of a two-part paper which introduces a general schema theory for genetic programming (GP) with subtree-swapping crossover (Part I (Poli and McPhee, 2003)). Like other recent GP schema theory results, the theory gives an exact formulation (rather than a lower bound) for the expected number of instances of a schema at the next generation. The theory is based on a Car...

real coded genetic algorithm, rcga, is the type of ga which operates on chromosomes with real valued parameters. different mutation and crossover operations are defined for rcga. one usable crossover for this kind of ga is to consider its chromosomes simply as bit strings and utilize the same operations as binary coded ga. in this paper, we attempt to show that this kind of crossover can not ha...

Because of the use of growing information, web mining has become a primary necessity of world. Due to this, research on web mining has received a lot of interest from both industry and academia. Mining and prediction of user’s web browsing behaviors and deducing the actual content in a web document is one of the active subjects. The information on web is dirty. Apart from useful information, it...