Fully informed artificial bee colony algorithm
The Gbest-guided artificial bee colony (GABC) algorithm is a latest swarm intelligence-
based approach to solve optimisation problem. In GABC, the individuals update their …
based approach to solve optimisation problem. In GABC, the individuals update their …
Greedy particle swarm and biogeography-based optimization algorithm
J Ababneh - International Journal of Intelligent Computing and …, 2015 - emerald.com
Purpose–The purpose of this paper is to propose an algorithm that combines the particle
swarm optimization (PSO) with the biogeography-based optimization (BBO) algorithm …
swarm optimization (PSO) with the biogeography-based optimization (BBO) algorithm …
A heuristic method to generate better initial population for evolutionary methods
E Khaji, AS Mohammadi - arXiv preprint arXiv:1406.4518, 2014 - arxiv.org
Initial population plays an important role in heuristic algorithms such as GA as it help to
decrease the time those algorithms need to achieve an acceptable result. Furthermore, it …
decrease the time those algorithms need to achieve an acceptable result. Furthermore, it …
An adaptive artificial bee colony algorithm for global optimization
A Yurtkuran, E Emel - Applied Mathematics and Computation, 2015 - Elsevier
Artificial bee colony algorithm (ABC) is a recently introduced swarm based meta-heuristic
algorithm. ABC mimics the foraging behavior of honey bee swarms. Original ABC algorithm …
algorithm. ABC mimics the foraging behavior of honey bee swarms. Original ABC algorithm …
Various swarm optimization algorithms: Review, challenges, and opportunities
In various research areas there is a requirement for optimized results in various research-
oriented parameters. In steganography, the important task is to find out the areas, where we …
oriented parameters. In steganography, the important task is to find out the areas, where we …
Enhanced flower pollination algorithm on data clustering
Nature-inspired algorithms are emerging as most compatible algorithms in obtaining near-
optimal solution to complex problems. The ability of meta-heuristic algorithm to obtain global …
optimal solution to complex problems. The ability of meta-heuristic algorithm to obtain global …
Comparative analysis of low discrepancy sequence-based initialization approaches using population-based algorithms for solving the global optimization problems
Metaheuristic algorithms have been widely used to solve diverse kinds of optimization
problems. For an optimization problem, population initialization plays a significant role in …
problems. For an optimization problem, population initialization plays a significant role in …
A species-based flower pollination algorithm with increased selection pressure in abiotic local pollination and enhanced intensification
FB Ozsoydan, A Baykasoglu - Knowledge-Based Systems, 2021 - Elsevier
Abstract Flower Pollination Algorithm (FPA) is a bio-inspired metaheuristic that simulates
pollination behavior of flowers. FPA is introduced to solve global optimization problems …
pollination behavior of flowers. FPA is introduced to solve global optimization problems …
[PDF][PDF] Search optimization using hybrid particle sub-swarms and evolutionary algorithms
Particle Swarm Optimization (PSO) technique proved its ability to deal with very complicated
optimization and search problems. Several variants of the original algorithm have been …
optimization and search problems. Several variants of the original algorithm have been …