In existing meta-heuristic algorithms, population initialization forms a huge part towards
problem optimization. These calculations can impact variety and combination to locate a …

A situation where the set of initial solutions lies near the position of the true optimality (most
favourable or desirable solution) by chance can increase the probability of finding the true …

Exact optimization algorithms are not able to provide an appropriate solution in solving
optimization problems with a high-dimensional search space. In these problems, the search …

Abstract In Artificial Intelligence, numerical optimization is an instantly rising research
domain. Swarm Intelligence (SI) and Evolutionary Algorithm (EA) are widely used to answer …

In this paper, a novel swarm intelligent algorithm is proposed, known as the fitness
dependent optimizer (FDO). The bee swarming the reproductive process and their collective …

Particle Swarm Optimization (PSO) is a well-known extensively utilized algorithm for a
distinct type of optimization problem. In meta-heuristic algorithms, population initialization …

Initialization of the population in Evolutionary Computation algorithms is an issue of ongoing
research. Proper initialization may help the algorithm to explore the search space more …

Companies are constantly changing in their organization and the way they treat information.
In this sense, relevant data analysis processes arise for decision makers. Similarly, to …

Particle swarm optimization (PSO) simulates social behavior, such as birds flocking or fish
schooling. It is an emerging population-based meta-heuristic and a population-based …

This paper presents a hybridization of particle swarm optimization (PSO) and artificial bee
colony (ABC) approaches, based on recombination procedure. The PSO and ABC are …