Comparative Study of Krill Herd, Firefly and Cuckoo Search Algorithms for Unimodal and Multimodal Optimization
Journal Title: International Journal of Intelligent Systems and Applications in Engineering - Year 2014, Vol 2, Issue 3
Abstract
Today, in computer science, a computational challenge exists in finding a globally optimized solution from an enormously large search space. Various metaheuristic methods can be used for finding the solution in a large search space.These methods can be explained as iterative search processes that efficiently perform the exploration and exploitation in the solution space. In this context, three such nature inspired metaheuristic algorithms namely Krill Herd Algorithm (KH), Firefly Algorithm (FA) and Cuckoo search Algorithm (CS) can be used to find optimal solutions of various mathematical optimization problems. In this paper, the proposed algorithms were used to find the optimal solution of fifteen unimodal and multimodal benchmark test functions commonly used in the field of optimization and then compare their performances on the basis of efficiency, convergence, time and conclude that for both unimodal and multimodal optimization Cuckoo Search Algorithm via Lévy flight has outperformed others and for multimodal optimization Krill Herd algorithm is superior than Firefly algorithm but for unimodal optimization Firefly is superior than Krill Herd algorithm.
Authors and Affiliations
Gobind Preet Singh*, Abhay Singh
Keywords
Related Articles
- EP ID EP751
- DOI -
- Views 421
- Downloads 22
The Classification of Eye State by Using kNN and MLP Classification Models According to the EEG Signals
What is widely used for classification of eye state to detect human’s cognition state is electroencephalography (EEG). In this study, the usage of EEG signals for online eye state detection method was proposed. In this s...
Intrusion Detection Forecasting Using Time Series for Improving Cyber Defence
The strength of time series modeling is generally not used in almost all current intrusion detection and prevention systems. By having time series models, system administrators will be able to better plan resource alloca...
The Control of A Non-Linear Chaotic System Using Genetic and Particle Swarm Based On Optimization Algorithms
In this study, the control of a non-linear system was realized by using a linear system control strategy. According to the strategy and by using the controller coefficients, system outputs were controlled for all referen...
A simple Mathematical Fuzzy Model of Brain Emotional Learning to Predict Kp Geomagnetic Index
In this paper, we propose fuzzy mathematical model of brain limbic system (LS) which is responsible for emotional stimuli. Here the proposed model is utilized to predict the chaotic activity of the earth’s magnetosphere....
Using Word Embeddings for Ontology Enrichment
Word embeddings, distributed word representations in a reduced linear space, show a lot of promise for accomplishing Natural Language Processing (NLP) tasks in an unsupervised manner. In this study, we investigate if the...