In the real world, there are a number of optimization problems whose search space is
restricted to take binary values; however, there are many continuous metaheuristics with …

Genetic Programming (GP) is an intelligence technique whereby computer programs are
encoded as a set of genes which are evolved utilizing a Genetic Algorithm (GA). In other …

Estimation of distribution algorithms (EDAs) are stochastic optimization techniques that
explore the space of potential solutions by building and sampling explicit probabilistic …

Estimation of distribution algorithms (EDA s) guide the search for the optimum by building
and sampling explicit probabilistic models of promising candidate solutions. However, EDA …

In the last three decades, the field of computational intelligence has seen a profusion of
population‐based metaheuristics applied to a variety of problems, where they achieved …

Many real-world optimization problems are subjected to uncertainties that may be
characterized by the presence of noise in the objective functions. The estimation of …

A robust deployment of the airship platforms is crucial to the performance of the Near Space
Communication System (NSCS) in the dynamic environment. In this paper, a multiobjective …

Memetic algorithms with an appropriate trade-off between the exploration and exploitation
can obtain very good results in continuous optimisation. That implies the evolutionary …

Estimation of distribution algorithms (EDAs) guide the search for the optimum by building
and sampling explicit probabilistic models of promising candidate solutions. However, EDAs …

Abstract Genetic algorithms [1, 2] are stochastic optimization methods inspired by natural
evolution and genetics. Over the last few decades, genetic algorithms have been …