New inspirations in swarm intelligence: a survey

By Rafael Stubs Parpinelli, Heitor Silvério Lopes. International Journal of Bio-Inspired Computation (IJBIC), 2011

377 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Biomedical Engineering

View Paper: https://www.semanticscholar.org/paper/4548c49d7e75f7bac860d2aea3ac7445056d3178

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Citations in the corpus

Firefly Algorithm: Recent Advances and Applications (2013, background): “In the last two decades, more than a dozen new algorithms such as particle swarm optimisation, diﬀerential evolution, bat algorithm, ﬁreﬂy algorithm and cuckoo search have appeared and they have shown great potential in solving tough engineering optimisation problems [32, 5, 16, 27, 34, 35, 17].”
A survey of swarm intelligence for dynamic optimization: Algorithms and applications (2017, background): “Their differences, apart from their behaviour inspiration, lie in the way the search space is explored and exploited by the “agents” [89].”
Swarm Robotic Behaviors and Current Applications (2020, methodology): “Biological swarm behaviors from which a number of computational algorithms were developed are also discussed by Parpinelli and Lopes (2011).”
Bio-inspired computation: Where we stand and what's next (2019, background): “This section may provide the reader with a general overview of bio-inspired computation, but the literature focused on this field is immense, with thorough bibliographic compendiums already contributed in the form of exhaustive surveys [42, 43, 44, 45].”
A social spider algorithm for global optimization (2015, background): “A possible reason for this is that a majority of the spiders observed are solitary [5], which means that they spend most of their lives without interacting with others of their species.”
Swarm Intelligence Algorithms for Feature Selection: A Review (2018, background): “In recent years, a considerable number of new swarm-inspired algorithms have emerged, as can be seen in the scope of surveys (e.g., [9,10]).”
An improved discrete bat algorithm for symmetric and asymmetric Traveling Salesman Problems (2016, methodology): “As can be read in several surveys ([Yang & He(2013), Parpinelli & Lopes(2011)]), since its proposal the BA has been successfully applied to different optimization fields and problems.”
SCA: A Sine Cosine Algorithm for solving optimization problems (2016, background): “Two main classifications are based on he inspiration of an algorithm (swarm intelligence-based [8], evoutionary [9], physics-based [10], etc.”
Prairie Dog Optimization Algorithm (2022, background): “The GA is one of the most popular algorithms in this category; others include evolutionary programming [31], differential evolution [32], and evolution strategy [33, 34].”
A comprehensive review of firefly algorithms (2013, background): “Parpinelli, in his survey ‘New inspirations in swarm intelligence’ [37], explained the foundations that inspire developers of the new nature-inspired swarm intelligence algorithms.”
Bat algorithm: literature review and applications (2013, background): “Case studies include pressure vessel design, car side design, spring and beam design, truss systems, tower and tall building design and others.”