Given a set of sparsely distributed sensors in the Euclidean plane, a mobile robot is required
to visit all sensors to download the data and finally return to its base. The effective range of …

This paper targets the identification of outlying sensors (that is, outlying reading sensors)
and the detection of the reach of events in sensor networks. Typical applications include the …

Global optimization process can often be divided into two subprocesses: exploration and
exploitation. The tradeoff between exploration and exploitation (T: Er&Ei) is crucial in search …

Optimization problems are ubiquitous in every field, and they are becoming more and more
complex, which greatly challenges the effectiveness of existing optimization methods. To …

Since estimation of distribution algorithms (EDAs) were proposed, many attempts have been
made to improve EDAs' performance in the context of global optimization. So far, the studies …

Traditional estimation of distribution algorithms (EDAs) often use Gaussian densities to
optimize continuous functions, such as the estimation of Gaussian network algorithms …

As a typical model-based evolutionary algorithm, estimation of distribution algorithm (EDA)
possesses unique characteristics and has been widely applied in global optimization …

Evolutionary algorithms are biologically inspired meta-heuristics. They perform randomized
search with the help of genetic operators. The success of evolutionary search is often a …

We describe a parameter-free estimation-of-distribution algorithm (EDA) called the adapted
maximum-likelihood Gaussian model iterated density-estimation evolutionary algorithm …

It has previously been shown analytically and experimentally that continuous Estimation of
Distribution Algorithms (EDAs) based on the normal pdf can easily suffer from premature …