Proceedings Article10.1109/SIELA.2016.7543010
Extended firefly algorithm for multimodal optimization
Andreas Hackl,Christian Magele,Werner Renhart +2 more
- 15 Aug 2016
pp 1-4
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TL;DR: This extended FFA will be used to solve the well known Rastrigin test function and an electromagnetic field problems, the optimal design of a magneto-rheologic clutch, respectively.
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Abstract: Many real world optimization problems have to be treated as multi-objective optimization problems. The Firefly Algorithm (FFA), a stochastic optimization method mimics the behavior of fireflies, which use a kind of flashing light to communicate with other members of their species. FFA is implicitly able to detect good local solutions on its way to the best solution. This disposition is successfully boosted by identifying clusters of fireflies which gather around promising local solutions. Subsequently, the update rules used for finding the new positions of the fireflies are applied among members of the particular clusters only. This extended FFA will be used to solve the well known Rastrigin test function and an electromagnetic field problems, the optimal design of a magneto-rheologic clutch, respectively.
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Citations
PEEC-based multi-objective synthesis of non-uniformly spaced linear antenna arrays
Thomas Bauernfeind,Paul Baumgartner,Oszkar Biro,Christian Magele,Kurt Preis,Andreas Hackl,Piergiorgio Alotto,Riccardo Torchio +7 more
- 01 Nov 2016
TL;DR: An antenna array arrangement with non-uniformly spacing between the array elements is synthesized in the multi-objective sense and the optimization relies on the firefly algorithm and the PEEC method.
16
Multi-Objective Synthesis of NFC-Transponder Systems Based on PEEC Method
Thomas Bauernfeind,Paul Baumgartner,Oszkar Biro,Andreas Hackl,Christian Magele,Werner Renhart,Riccardo Torchio +6 more
TL;DR: The partial-element electric circuit (PEEC) method is applied to carry out the needed field computation in the so-called NFC operating volume and an extended version of the general FFA is applied.
13
A Proposal for the Organisational Measure in Intelligent Systems
TL;DR: In this paper, the authors define swarm systems as intelligent systems that show collaboration within the system; moreover, some models, such as multiple ant colonies, show the collaboration of several systems to achieve a global goal.
4
Self-organizing map based differential evolution with dynamic selection strategy for multimodal optimization problems.
TL;DR: A self-organizing map based differential evolution with dynamic selection strategy (SOMDE-DS) is proposed to improve the performance of differential evolution (DE) in solving MMOPs and is compared with several widely used multimodal optimization algorithms.
3
•Dissertation
An improved firefly algorithm for optimal microgrid operation with renewable energy
Shukur Saleh
- 01 Jul 2017
TL;DR: The Improved Firefly Algorithm (IFA), which is a improvement of classical Firefly Al algorithm technique using characteristic approach of Levy flights to solve the optimal microgrid operation, shows that the IFA obtained better results in terms of operating costs compared to FA, Differential Evolution (DE), Particle Swarm Optimization (PSO) and Cuckoo Search Al algorithm (CSA).
References
Firefly algorithms for multimodal optimization
Xin-She Yang
- 26 Oct 2009
TL;DR: In this article, a new Firefly Algorithm (FA) was proposed for multimodal optimization applications. And the proposed FA was compared with other metaheuristic algorithms such as particle swarm optimization (PSO).
Evolution strategy and hierarchical clustering
Oswin Aichholzer,Franz Aurenhammer,Bernhard Brandstätter,Th. Ebner,Hannes Krasser,Ch. Magele,M. Muhlmann,Werner Renhart +7 more
TL;DR: A clustering algorithm has been implemented into an extended higher order evolution strategy andMultimodal two-dimensional test problems, namely, Rastrigin's function and the 4-parameter die mold press benchmark problem, are solved using this approach.
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