Solving the tension/compression spring design problem by an improved firefly algorithm
Küçük Resim Yok
Tarih
2018
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
CEUR-WS
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Since the 1970s, nature inspired meta-heuristic algorithms have become increasingly popular. These algorithms include a set of algorithmic concepts that can be used to identify heuristic methods that are used for a wide range of different tasks. The use of meta-heuristics greatly increases the possibility of finding a qualitative solution for complex, combinatorial optimization problems in a reasonable time. The most popular nature inspired meta-heuristics are those methods representing successful animal and micro-organism swarm behaviors. Firefly Algorithm (FA) is a recent one of such meta-heuristic algorithms It is based on a swarm intelligence and inspired by the social behaviors of fireflies. In this paper, we adapt the neighborhood method to FA and propose an improved firefly algorithm (IFA) to solve a well-known engineering problem, the so-called Tension/Compression Spring Design. We test the proposed IFA on this problem and compare the results with those obtained by some other meta-heuristics. The experimental modeling shows that the proposed IFA is competitive and improves the quality of solutions for the aforementioned engineering design problem. © 2018 CEUR-WS. All Rights Reserved.
Açıklama
1st International Workshop on Informatics and Data-Driven Medicine, IDDM 2018 -- 28 November 2018 through 30 November 2018 -- Lviv -- 142381
Anahtar Kelimeler
Firefly Algorithm (FA), Metaheuristic, Swarm Intelligence, Tension/Compression Spring Design
Kaynak
CEUR Workshop Proceedings
WoS Q Değeri
Scopus Q Değeri
N/A
Cilt
2255
