Journal ArticleDOI
A novel numerical optimization algorithm inspired from weed colonization
Ali Reza Mehrabian,Caro Lucas +1 more
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A novel numerical stochastic optimization algorithm inspired from colonizing weeds to mimic robustness, adaptation and randomness of Colonizing weeds in a simple but effective optimizing algorithm designated as Invasive Weed Optimization (IWO).About:
This article is published in Ecological Informatics.The article was published on 2006-12-01. It has received 1183 citations till now. The article focuses on the topics: Metaheuristic & Simulated annealing.read more
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Nature-Inspired Optimization Algorithms
TL;DR: This book can serve as an introductory book for graduates, doctoral students and lecturers in computer science, engineering and natural sciences, and researchers and engineers as well as experienced experts will also find it a handy reference.
Journal ArticleDOI
Manta ray foraging optimization: An effective bio-inspired optimizer for engineering applications
TL;DR: The comparison results on the benchmark functions suggest that MRFO is far superior to its competitors, and the real-world engineering applications show the merits of this algorithm in tackling challenging problems in terms of computational cost and solution precision.
Posted Content
A Brief Review of Nature-Inspired Algorithms for Optimization
TL;DR: A relatively comprehensive list of all the algorithms based on swarm intelligence, bio-inspired, physics-based and chemistry-based, depending on the sources of inspiration, that have become popular tools for solving real-world problems.
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Lion Optimization Algorithm (LOA): A nature-inspired metaheuristic algorithm
Maziar Yazdani,Fariborz Jolai +1 more
TL;DR: A new population based algorithm, the Lion Optimization Algorithm (LOA), is introduced, special lifestyle of lions and their cooperation characteristics has been the basic motivation for development of this optimization algorithm.
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A survey on nature inspired metaheuristic algorithms for partitional clustering
TL;DR: An up-to-date review of all major nature inspired metaheuristic algorithms employed till date for partitional clustering and key issues involved during formulation of various metaheuristics as a clustering problem and major application areas are discussed.
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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.
Book
Adaptation in natural and artificial systems
TL;DR: Names of founding work in the area of Adaptation and modiication, which aims to mimic biological optimization, and some (Non-GA) branches of AI.
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Particle swarm optimization
TL;DR: A snapshot of particle swarming from the authors’ perspective, including variations in the algorithm, current and ongoing research, applications and open problems, is included.
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Ant system: optimization by a colony of cooperating agents
TL;DR: It is shown how the ant system (AS) can be applied to other optimization problems like the asymmetric traveling salesman, the quadratic assignment and the job-shop scheduling, and the salient characteristics-global data structure revision, distributed communication and probabilistic transitions of the AS.