Swarm Intelligence and Bio-Inspired Computation

By Xin-She Yang, Mehmet Karamanoglu. 2013

328 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Biomedical Engineering

View Paper: https://www.semanticscholar.org/paper/f53cf2e56f226c00024384df432d30a6247b1bbd

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

In Biomedical Engineering

Citations in the corpus

SCA: A Sine Cosine Algorithm for solving optimization problems (2016, background): “e s t t a a c p of this paper is on the theory, the applications are not discussed further and interested readers are referred to [11,12].”
Bio-inspired computation: Where we stand and what's next (2019, background): “Different empirical observations and numerical simulations have elucidated that bio-inspired algorithms can work surprisingly well in practice, but in most cases we rarely understand why they work under the given conditions for a given type of problem [424,425].”
A Tutorial On the design, experimentation and application of metaheuristic algorithms to real-World optimization problems (2021, background): “In the last two decades, a myriad of bio-inspired approaches have been applied to diﬀerent problems, some of which have shown remarkable performance.”
Artificial intelligence in supply chain management: A systematic literature review (2021, unknown): “Over the past 20 years, such a technique has attracted considerable attention in almost every area of engineering, science and industry (Yang and Karamanoglu, 2013).”
A Brief Review of Nature-Inspired Algorithms for Optimization (2013, background): “In essence, researchers try to look for some efﬁcient formulas as summarized by Yang [73] as the following generic scheme: ( p 1 , p 2 , ..., p k ); ( w 1 , w 2 , ..., w m ) , which attempts to generate better solutions (a population of n solutions) at iteration t + 1 from the current iteration t…”
A new metaheuristic for numerical function optimization: Vortex Search algorithm (2015, background): “, Beale, Colville), it will fail when applied to these types of problems [45].”
Bio inspired computing - A review of algorithms and scope of applications (2016, methodology): “The flower pollination algorithm (Yang, 2012; Yang et al., 2013) is based on the mechanisms of pollination of flowers.”
Fitness Function in ABC Algorithm for Uncapacitated Facility Location Problem (2015, methodology): “The method of simulating swarm intelligence is inspired by the movement and foraging behavior in herd animals [10].”