The Firefly Optimization Algorithm: Convergence Analysis and Parameter Selection
نویسندگان
چکیده
The bio-inspired optimization techniques have obtained great attention in recent years due to its robustness, simplicity and efficiency to solve complex optimization problems. The firefly Optimization (FA or FFA) algorithm is an optimization method with these features. The algorithm is inspired by the flashing behavior of fireflies. In the algorithm, randomly generated solutions will be considered as fireflies, and brightness is assigned depending on their performance on the objective function. The algorithm is analyzed on basis of performance and success rate using five standard benchmark functions by which guidelines of parameter selection are derived. The tradeoff between exploration and exploitation is illustrated and discussed. General Terms Optimization, metaheuristic, firefly algorithm, analysis, convergence, parameter selection, performance.
منابع مشابه
A Hybrid Grey based Two Steps Clustering and Firefly Algorithm for Portfolio Selection
Considering the concept of clustering, the main idea of the present study is based on the fact that all stocks for choosing and ranking will not be necessarily in one cluster. Taking the mentioned point into account, this study aims at offering a new methodology for making decisions concerning the formation of a portfolio of stocks in the stock market. To meet this end, Multiple-Criteria Decisi...
متن کاملProcess Parameter Optimization In Multi-Pass Turning Operation Using Hybrid Firefly Swarm Algorithm
Evolutionary algorithms are the choice of many researchers for optimizing machining parameters. Even though evolutionary algorithms are commonly used for solving constrained optimization problems, however in practice sometimes they deliver only insignificant performance. The difficulty with evolutionary algorithms is that they start with random initial population and all its populations become ...
متن کاملA CELLULAR AUTOMATA BASED FIREFLY ALGORITHM FOR LAYOUT OPTIMIZAION OF TRUSS STRUCTURES
In this study an efficient meta-heuristic is proposed for layout optimization of truss structures by combining cellular automata (CA) and firefly algorithm (FA). In the proposed meta-heuristic, called here as cellular automata firefly algorithm (CAFA), a new equation is presented for position updating of fireflies based on the concept of CA. Two benchmark examples of truss structures are presen...
متن کاملAutomatic generation control using two degree of freedom fractional order PID controller
In this paper, Two-Degree-of-Freedom-Fractional Order PID (2-DOF-FOPID) controller is proposed for automatic generation control (AGC) of power systems. Proposed controller is tested for the first time on a three unequal area thermal systems considering reheat turbines and appropriate generation rate constraints (GRCs). The simultaneous optimization of several parameters of the controllers and s...
متن کاملDetermination of Suitable Operating Conditions of Fluid Catalytic Cracking Process by Application of Artificial Neural Network and Firefly Algorithm
Fluid Catalytic Cracking (FCC) process is a vital unit to produce gasoline. In this research, a feed forward ANN model was developed and trained with industrial data to investigate the effect of operating variables containing reactor temperature feed flow rate, the temperature of the top of the main column and the temperature of the bottom of the debutanizer tower on quality and quantity of...
متن کامل