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Abstract This paper presents the optimization performance of non-uniform linear antenna array with optimized inter-element spacing and excitation amplitude using Particle Swarm Optimization (PSO). The aim of the proposed...

Abstract This work introduces a metaheuristic (MH) optimization method, which is inspired by the red-tailed hawks’ predatory behavior is Improved Red-tailed Hawk (IRTHA) Algorithm. The algorithm uses a dynamic adjustme...

ABSTRACT Background and Aims De novo drug design is the process of generating novel lead compounds that possess desirable pharmacological activities and optimal physicochemical properties for therapeutic development. In ...

Abstract        This work involves the use  some of Artificial intelligence techniques algorithms which are genetic algorithm and artificial immune system algorithm- clonal selection algorithm.        A comp...

Abstract While multi-access edge computing (MEC) enables flexible task offloading, the inherent dynamism and complexity of real-world environments, accompanied by various uncertainties, exacerbate the challenges in offlo...

This paper presents the solution of a real-world constrained bi-objective mechanical design problem in presence of a dynamic constraint by using the Modified Bacterial Foraging Optimization Algorithm. This algorithm, or...

The use of evolutionary and swarm intelligence algorithms, has become a very popular option to solve complex real-world optimization problems. However, in their original versions, these algorithms lack a mechanism to han...

Niche formation allows evolutionary algorithms to be used when the location and maintenance of multiple solutions appertaining to diverse areas of the phenotypic space is required. Consequently the application field can ...

Harvesting topical content is a process that can be done by formulating topic-relevant queries and submitting them to a search engine. The quality of the material collected through this process is highly dependant on the...

Abstract. Stochastic techniques have demonstrated rewarding performance in global optimization of highly multimodal unconstrained models. However, the formulation of a general framework for constraint handling in stochas...

A new issue for combinatorial optimization problems is to incorporate local search into the framework of evolutionary algorithms, leading to hybrid evolutionary algorithms. With the hybrid approach, evolutionary algorith...

Traditionally in Genetic Algorithms, the mutation probability parameter maintains a constant value during the search. However, an important difficulty is to determine a priori which probability value is the best suited f...

In this article we present an algorithm for solving bound constrained optimization problems without derivatives based on Powell's method for derivative-free optimization. First we consider the unconstrained optimization ...

In the restricted single-machine common due date problem, the goal is to find a schedule for the n jobs which jointly minimizes the sum of earliness and tardiness penalties. This problem, even in its simplest formulatio...

Niche formation allows evolutionary algorithms to be used when the location and maintenance of multiple solutions appertaining to diverse areas of the phenotypic space is required. Consequently the application field can ...

Evolutionary computation (EC) has been recently recognized as a research field, which studies a new type of algorithms: Evolutionary Algorithms (EAs). These algorithms process populations of solutions as opposed to most ...

Evolutionary computation (EC) has been recently recognized as a research field, which studies a new type of algorithms: Evolutionary Algorithms (EAs). These algorithms process populations of solutions as opposed to most ...

Evolutionary Algorithms (EAs) became a powerful tool for environments where an optimization is needed or where an adaptive behaviour of a system is necessary. Computer Systems have been evolving rapidly during the last ...

In this article we analyze two kinds of metaheuristic algorithms applied to wind farm optimization. The basic idea is to utilize CHC (a sort of GA) and GPSO (a sort of PSO) algorithms to obtain an acceptable configurati...

The choice of a search algorithm can play a vital role in the success of a scheduling application. Evolutionary algorithms (EAs) can be used to solve this kind of combinatorial optimization problems. Compared to conventi...

Evolutionary algorithms (EAs) have been successfully applied to scheduling problems. Current improvements towards convergence issues in EAs include incest prevention and multiplicity features. A multiplicity feature all...

Genetic algorithms (GAs) are stochastic adaptive algorithms whose search method is based on simulation of natural genetic inheritance and Darwinian strive for survival. They can be used to find approximate solutions to n...

The Estimation Distribution Algorithms (EDAs) compose an evolutionary metaheuristic whose main characteristic is the construction of solutions in randomly form, using a distribution of probabilities that evolves during t...

Large bandwidth on hand in WDM networks is the best choice for increasing tra c demand; although, routing and wavelength assignment (RWA) problems still remain a challenge. This work proposes a novel method to solve mult...