1. Introduction The Harris hawks optimization (HHO) algorithm is a new swarm intelligence optimization paradigm proposed by Ali Asghar Heidari et al. in 2019, which is inspired by the team behaviors and chasing patterns of Harris’s hawk in nature called surprise pounce [1] The Harris’s hawk is notable for its behavior of hunting cooperatively […]
Tag: computer science
Honey Bee Mating Optimization (HBMO) Algorithm: Propelled Behavior of Bees Mating for Solving Optimization Problems
1. Introduction A new optimization algorithm based on honey bee mating, first proposed by Afshar et al. (2007), has been used to solve difficult optimization problems such as optimal reservoir operation (Haddad et al, 2007) and clustering (Fathian et al. 2007) [1]. Honey Bee mating Optimization Algorithm (HBMO) under different context by various researchers […]
Continue ReadingFlower Pollination Algorithm (FPA): A Novel Method Motivated from the Behavior of Flowers for Optimal Solution
1. Introduction Flower Pollination Algorithm (FPA) is a nature inspired population based algorithm proposed by Xin-She Yang (2012). The main objective of the flower pollination is to produce the optimal reproduction of plants by surviving the fittest flowers in the flowering plants. In fact this is an optimization process of plants in species. FPA […]
Continue ReadingDolphin Echolocation Algorithm (DEA): A Novel Method Motivated from the Behavior of Dolphin for Optimal Solution
1. Introduction Dolphin Echolocation Algorithm is mimics strategies used by dolphins for their hunting process. Dolphins produce a kind of voice called sonar to locate the target, doing this dolphin change sonar to modify the target and its location. In order to implement the optimization task an improved dolphin echolocation meta-heuristic algorithm is proposed. […]
Continue ReadingSailfish Optimizer (SFO): A Novel Method Motivated from the Behavior of Sailfish for Optimal Solution
1. Introduction Optimization can be used essentially in a variety of fields from engineering design to economics or holiday planning to Internet routing. Metaheuristic algorithms can provide appropriate technique to solve optimization problems through mathematical modeling of social political evolution. These algorithms are using methods that find solutions close to the optimum with an […]
Continue ReadingCuttlefish Algorithm (CFA): Propelled from Color Changing Behavior of Cuttlefishes for Solving Optimization Problems
1. Introduction Optimization algorithm which is called Cuttlefish Algorithm (CFA). The algorithm mimics the mechanism of color changing behavior of the cuttlefish to solve numerical global optimization problems [1]. The colors and patterns of the cuttlefish are produced by reflected light from three different layers of cells. Evolutionary algorithms are a part of artificial […]
Continue ReadingA Novel Numerical Optimization Algorithm Inspired from Salps: Salp Swarm Optimization Algorithm
1. Introduction Inspiration analysis Salp Swarm Algorithm (SSA) is one of meta-heuristic algorithms recently proposed by Mirjalili in 2017. A novel optimization algorithm called Salp Swarm Optimizer (SSA) is proposed. Multi-objective Salp Swarm Algorithm (MSSA) is proposed to solve multi-objective problems [1]. Swarm intelligence techniques mimic the intelligence of swarms, herds, schools, or flocks […]
Continue ReadingKrill Herd (KH) Algorithm to solve Numerical Optimization Problem
1. Introduction Based on the simulation of the herding behavior of krill individuals, Gandomi and Alavi proposed the krill herd algorithm (KH) in 2012. And KH algorithm is a novel biologically inspired algorithm to solve the optimization problems [1]. In KH algorithm, the objective function for the krill movement is determined by the minimum […]
Continue ReadingOwl Search Algorithm: A Novel Nature Inspired Metaheuristic Method
1. Introduction The metaheuristic optimization techniques have gained significant attention of researchers due to successful application of these techniques in a variety of complex optimization problems. These techniques are found more effective than conventional methods which use derivative information of function [1]. Two eminent features of any metaheuristic technique are exploration and exploitation. Exploration […]
Continue ReadingBehavior of Mouth Brooding Fish Algorithm (MBF) using Meta-heuristics method
1. Introduction In the past few decades, nature-inspired computation has attracted more attention. Many real-world engineering optimization problems are substantially very complicated and quite difficult to solve [1]. However, nature serves as a fertile source of concepts, principles, and mechanisms for designing artificial computation systems to tackle complicated computational problems. In nature, mouth brooding […]
Continue Reading