-In this paper we present a genetic algorithm-based optimization technique for edge detection. The problem of edge detection is formulated as one of choosing a minimum cost edge configuration. The edge configurations are viewed as two-dimensional chromosomes with fitness values inversely proportional to their costs. The design of the crossover and the mutation operators in the context of the tw...

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...

| Delta coding is an iterative genetic search strategy that sustains search by periodically re-initializing the population. This helps to avoid premature convergence during genetic search. Delta coding also remaps hyper-space with each iteration in an attempt to locate \easier" search spaces with respect to genetic search. Here, the optimization ability of delta coding is compared against the C...

The shipboard power system (SPS) supply energy to sophisticated systems for weapons, communications, navigation and operation. So when the system is damaged, the faults should be isolated and restored immediately to ensure the system survivability. Currently the genetic algorithm (GA) is successfully used to SPS fault restoration and the superiority over the other methods is proved, but the sim...

Aiming to the problems of slow convergence speed and being easily early-maturing etc. in existing network based on standard particle swarm algorithm, this paper proposes a wireless sensor network coverage optimization algorithm based on the genetic particle swarm optimization (PSO). The wireless sensor maximum coverage is regarded as the objective function, the genetic algorithm with adaptive c...

Genetic Algorithms (GAs) are the search algorithms and optimization techniques based on the mechanics of natural selection and natural genetics. They sort out interesting areas of a space quickly but without guaranteeing more convergence. So GA may be mixed with various local problem-specific search techniques to form a hybrid that will combine the globality and parallelism of GA with more conv...

Known as an NP-Complete problem, the channel routing problem is very important in the automatic layout design of VLSI circuit and printed circuit boards. A distributed hybrid algorithm for this channel routing problem is presented in MPI environments. This system is implemented on a network of personal computers running Linux operating system connected via 100Mbps Ethernet. Each slave processor...

The optimization by genetic algorithms often comes along with premature convergence bias, especially in the multimodal problems. In the paper, we propose and test two mechanisms to avoid the premature convergence of genetic algorithms by preserving the population diversity in two different manners. These are the dynamic application of many genetic operators, based on the average progress, and t...

the forecasting of hydrological variables, such as streamflow, plays an important role in water resource planning and management. recently, the development of stochastic models is regarded as a major step for this purpose. streamflow forecasting using the arima model can be conducted when unknown parameters are estimated correctly because parameter estimation is one of the crucial steps in mode...