Bat Algorithm: A Novel Approach for Global Engineering Optimization
Xin-She Yang,Amir H. Gandomi +1 more
Reads0
Chats0
TLDR
In this article, a new nature-inspired metaheuristic optimization algorithm, called bat algorithm (BA), is introduced for solving engineering optimization tasks, which is based on the echolocation behavior of bats.Abstract:
Nature-inspired algorithms are among the most powerful algorithms for optimization. In this study, a new nature-inspired metaheuristic optimization algorithm, called bat algorithm (BA), is introduced for solving engineering optimization tasks. The proposed BA is based on the echolocation behavior of bats. After a detailed formulation and explanation of its implementation, BA is verified using eight nonlinear engineering optimization problems reported in the specialized literature. BA has been carefully implemented and carried out optimization for eight well-known optimization tasks. Then, a comparison has been made between the proposed algorithm and other existing algorithms. The optimal solutions obtained by the proposed algorithm are better than the best solutions obtained by the existing methods. The unique search features used in BA are analyzed, and their implications for future research are also discussed in detail.read more
Citations
More filters
Journal ArticleDOI
Artificial hummingbird algorithm: A new bio-inspired optimizer with its engineering applications
TL;DR: In this article , a bio-inspired optimization algorithm called artificial hummingbird algorithm (AHA) is proposed to solve optimization problems, which simulates the special flight skills and intelligent foraging strategies of hummingbirds in nature.
Journal ArticleDOI
Snake Optimizer: A novel meta-heuristic optimization algorithm
TL;DR: In this paper , a novel nature-inspired metaheuristic algorithm named as snake optimizer (SO) is proposed to tackle a various set of optimization tasks which imitates the special mating behavior of snakes.
Journal ArticleDOI
Metaheuristic algorithms for PID controller parameters tuning: review, approaches and open problems
Stephen Bassi Joseph,Emmanuel Gbenga Dada,Afeez Abidemi,David Opeoluwa Oyewola,Ban Mohammed Khammas +4 more
TL;DR: A thorough review of state-of-the-art and classical strategies for PID controller parameters tuning using metaheuristic algorithms can be found in this article , where the primary objectives of PID control parameters are to achieve minimal overshoot in steady state response and lesser settling time.
Journal ArticleDOI
An enhanced hybrid arithmetic optimization algorithm for engineering applications
TL;DR: Wang et al. as mentioned in this paper proposed an enhanced hybrid arithmetic optimization algorithm (CSOAOA), integrated with point set strategy, optimal neighborhood learning strategy, and crisscross strategy, to solve complex engineering optimization problems.
Journal ArticleDOI
Beluga whale optimization: A novel nature-inspired metaheuristic algorithm
TL;DR: Zhang et al. as discussed by the authors proposed a swarm-based metaheuristic algorithm inspired from the behaviors of beluga whales, called Beluga Whale Optimization (BWO), to solve optimization problem.
References
More filters
Journal ArticleDOI
Optimization by Simulated Annealing
TL;DR: There is a deep and useful connection between statistical mechanics and multivariate or combinatorial optimization (finding the minimum of a given function depending on many parameters), and a detailed analogy with annealing in solids provides a framework for optimization of very large and complex systems.
Proceedings ArticleDOI
A modified particle swarm optimizer
Yuhui Shi,Russell C. Eberhart +1 more
TL;DR: A new parameter, called inertia weight, is introduced into the original particle swarm optimizer, which resembles a school of flying birds since it adjusts its flying according to its own flying experience and its companions' flying experience.
Journal ArticleDOI
A New Heuristic Optimization Algorithm: Harmony Search
TL;DR: A new heuristic algorithm, mimicking the improvisation of music players, has been developed and named Harmony Search (HS), which is illustrated with a traveling salesman problem (TSP), a specific academic optimization problem, and a least-cost pipe network design problem.
Book
Nature-Inspired Metaheuristic Algorithms
TL;DR: This book reviews and introduces the state-of-the-art nature-inspired metaheuristic algorithms in optimization, including genetic algorithms, bee algorithms, particle swarm optimization, simulated annealing, ant colony optimization, harmony search, and firefly algorithms.
Journal ArticleDOI
An efficient constraint handling method for genetic algorithms
TL;DR: GA's population-based approach and ability to make pair-wise comparison in tournament selection operator are exploited to devise a penalty function approach that does not require any penalty parameter to guide the search towards the constrained optimum.
Related Papers (5)
Bat algorithm: a novel approach for global engineering optimization
Xin-She Yang,Amir H. Gandomi +1 more