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Firefly algorithm is a nature-inspired optimization algorithm and there have been significant developments since its appearance about ten years ago. This chapter summarizes the latest developments about the firefly algorithm and its…

Neural and Evolutionary Computing · Computer Science 2018-06-06 Xin-She Yang , Xingshi He

Nature-inspired algorithms such as Particle Swarm Optimization and Firefly Algorithm are among the most powerful algorithms for optimization. In this paper, we intend to formulate a new metaheuristic algorithm by combining Levy flights with…

Optimization and Control · Mathematics 2010-03-09 Xin-She Yang

Firefly algorithm is a swarm based metaheuristic algorithm inspired by the flashing behavior of fireflies. It is an effective and an easy to implement algorithm. It has been tested on different problems from different disciplines and found…

Neural and Evolutionary Computing · Computer Science 2016-02-26 Surafel Luleseged Tilahun , Jean Medard T Ngnotchouye

Nature-inspired algorithms are among the most powerful algorithms for optimization. This paper intends to provide a detailed description of a new Firefly Algorithm (FA) for multimodal optimization applications. We will compare the proposed…

Optimization and Control · Mathematics 2010-03-09 Xin-She Yang

The firefly algorithm has become an increasingly important tool of Swarm Intelligence that has been applied in almost all areas of optimization, as well as engineering practice. Many problems from various areas have been successfully solved…

Neural and Evolutionary Computing · Computer Science 2013-12-24 Iztok Fister , Iztok Fister , Xin-She Yang , Janez Brest

Swarm intelligence has becoming a powerful technique in solving design and scheduling tasks. Metaheuristic algorithms are an integrated part of this paradigm, and particle swarm optimization is often viewed as an important landmark. The…

Optimization and Control · Mathematics 2013-03-27 Xin-She Yang

Optimization algorithms are normally influenced by meta-heuristic approach. In recent years several hybrid methods for optimization are developed to find out a better solution. The proposed work using meta-heuristic Nature Inspired…

Artificial Intelligence · Computer Science 2012-06-26 Sudarshan Nandy , Partha Pratim Sarkar , Achintya Das

Metaheuristic algorithms such as particle swarm optimization, firefly algorithm and harmony search are now becoming powerful methods for solving many tough optimization problems. In this paper, we propose a new metaheuristic method, the Bat…

Optimization and Control · Mathematics 2010-07-29 Xin-She Yang

Metaheuristic algorithms are becoming an important part of modern optimization. A wide range of metaheuristic algorithms have emerged over the last two decades, and many metaheuristics such as particle swarm optimization are becoming…

Optimization and Control · Mathematics 2012-12-04 Xin-She Yang

Increasing nature-inspired metaheuristic algorithms are applied to solving the real-world optimization problems, as they have some advantages over the classical methods of numerical optimization. This paper has proposed a new…

Neural and Evolutionary Computing · Computer Science 2017-08-10 Bing Zeng , Liang Gao , Xinyu Li

Swarm intelligence and bio-inspired algorithms form a hot topic in the developments of new algorithms inspired by nature. These nature-inspired metaheuristic algorithms can be based on swarm intelligence, biological systems, physical and…

Neural and Evolutionary Computing · Computer Science 2013-07-17 Iztok Fister , Xin-She Yang , Iztok Fister , Janez Brest , Dušan Fister

In recent years, a plethora of new metaheuristic algorithms have explored different sources of inspiration within the biological and natural worlds. This nature-inspired approach to algorithm design has been widely criticised. A notable…

Neural and Evolutionary Computing · Computer Science 2020-03-26 Michael Adam Lones

The dragonfly algorithm was developed in 2016. It is one of the algorithms used by researchers to optimize an extensive series of uses and applications in various areas. At times, it offers superior performance compared to the most…

Neural and Evolutionary Computing · Computer Science 2021-08-31 Chnoor M. Rahman , Tarik A. Rashid , Abeer Alsadoon , Nebojsa Bacanin , Polla Fattah , Seyedali Mirjalili

Firefly algorithms belong to modern meta-heuristic algorithms inspired by nature that can be successfully applied to continuous optimization problems. In this paper, we have been applied the firefly algorithm, hybridized with local search…

Optimization and Control · Mathematics 2012-05-14 Iztok Fister , Xin-She Yang , Iztok Fister , Janez Brest

The efficiency of any metaheuristic algorithm largely depends on the way of balancing local intensive exploitation and global diverse exploration. Studies show that bat algorithm can provide a good balance between these two key components…

Optimization and Control · Mathematics 2014-08-25 Xin-She Yang , Suash Deb , Simon Fong

Modern optimisation algorithms are often metaheuristic, and they are very promising in solving NP-hard optimization problems. In this paper, we show how to use the recently developed Firefly Algorithm to solve nonlinear design problems. For…

Optimization and Control · Mathematics 2012-03-30 Xin-She Yang

Several real-world optimization problems involve mixed-variable search spaces, where continuous, ordinal, and categorical decision variables coexist. However, most population-based metaheuristic algorithms are designed for either continuous…

Neural and Evolutionary Computing · Computer Science 2026-04-07 Ousmane Tom Bechir , Adán José-García , Zaineb Chelly Garcia , Vincent Sobanski , Clarisse Dhaenens

One of the most recently developed heuristic optimization algorithms is dragonfly by Mirjalili. Dragonfly algorithm has shown its ability to optimizing different real world problems. It has three variants. In this work, an overview of the…

Neural and Evolutionary Computing · Computer Science 2020-01-09 Chnoor M. Rahman , Tarik A. Rashid

Fireworks algorithm is a new type of intelligent optimization algorithm. Because of its fast convergence speed, easy implementation, explosiveness, diversity, simplicity and randomness, it has attracted more and more attention in many…

Neural and Evolutionary Computing · Computer Science 2022-08-16 Zhao Zhigang , Li Zhimei , Mo Haimiao , Zeng Min

This paper presents the Firefighter Optimization (FFO) algorithm as a new hybrid metaheuristic for optimization problems. This algorithm stems inspiration from the collaborative strategies often deployed by firefighters in firefighting…

Neural and Evolutionary Computing · Computer Science 2024-06-04 M. Z. Naser , A. Z. Naser
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