Chaotic fruit fly optimization algorithm
Апстракт
Fruit fly optimization algorithm (FOA) is recently presented metaheuristic technique that is inspired by the behavior of fruit flies. This paper improves the standard FOA by introducing the novel parameter integrated with chaos. The performance of developed chaotic fruit fly algorithm (CFOA) is investigated in details on ten well known benchmark problems using fourteen different chaotic maps. Moreover, we performed comparison studies with basic FOA, FOA with Levy flight distribution, and other recently published chaotic algorithms. Statistical results on every optimization task indicate that the chaotic fruit fly algorithm (CFOA) has a very fast convergence rate. In addition, CFOA is compared with recently developed chaos enhanced algorithms such as chaotic bat algorithm, chaotic accelerated particle swarm optimization, chaotic firefly algorithm, chaotic artificial bee colony algorithm, and chaotic cuckoo search. Overall research findings show that FOA with Chebyshev map show superiori...ty in terms of reliability of global optimality and algorithm success rate.
Кључне речи:
Optimization / Metaheuristic technique / Fruit fly optimization algorithm / ChaosИзвор:
Knowledge-Based Systems, 2015, 89, 446-458Издавач:
- Elsevier, Amsterdam
Финансирање / пројекти:
- Иновативни приступ у примени интелигентних технолошких система за производњу делова од лима заснован на еколошким принципима (RS-MESTD-Technological Development (TD or TR)-35004)
Напомена:
- This is the peer-reviewed version of the article: Mitić, M.; Vuković, N.; Petrović, M.; Miljković, Z. Chaotic Fruit Fly Optimization Algorithm. Knowledge-Based Systems 2015, 89, 446–458. https://doi.org/10.1016/j.knosys.2015.08.010
DOI: 10.1016/j.knosys.2015.08.010
ISSN: 0950-7051
WoS: 000364249800032
Scopus: 2-s2.0-84944319429
Институција/група
Mašinski fakultetTY - JOUR AU - Mitić, Marko AU - Vuković, Najdan AU - Petrović, Milica AU - Miljković, Zoran PY - 2015 UR - https://machinery.mas.bg.ac.rs/handle/123456789/3929 AB - Fruit fly optimization algorithm (FOA) is recently presented metaheuristic technique that is inspired by the behavior of fruit flies. This paper improves the standard FOA by introducing the novel parameter integrated with chaos. The performance of developed chaotic fruit fly algorithm (CFOA) is investigated in details on ten well known benchmark problems using fourteen different chaotic maps. Moreover, we performed comparison studies with basic FOA, FOA with Levy flight distribution, and other recently published chaotic algorithms. Statistical results on every optimization task indicate that the chaotic fruit fly algorithm (CFOA) has a very fast convergence rate. In addition, CFOA is compared with recently developed chaos enhanced algorithms such as chaotic bat algorithm, chaotic accelerated particle swarm optimization, chaotic firefly algorithm, chaotic artificial bee colony algorithm, and chaotic cuckoo search. Overall research findings show that FOA with Chebyshev map show superiority in terms of reliability of global optimality and algorithm success rate. PB - Elsevier, Amsterdam T2 - Knowledge-Based Systems T1 - Chaotic fruit fly optimization algorithm EP - 458 SP - 446 VL - 89 DO - 10.1016/j.knosys.2015.08.010 ER -
@article{ author = "Mitić, Marko and Vuković, Najdan and Petrović, Milica and Miljković, Zoran", year = "2015", abstract = "Fruit fly optimization algorithm (FOA) is recently presented metaheuristic technique that is inspired by the behavior of fruit flies. This paper improves the standard FOA by introducing the novel parameter integrated with chaos. The performance of developed chaotic fruit fly algorithm (CFOA) is investigated in details on ten well known benchmark problems using fourteen different chaotic maps. Moreover, we performed comparison studies with basic FOA, FOA with Levy flight distribution, and other recently published chaotic algorithms. Statistical results on every optimization task indicate that the chaotic fruit fly algorithm (CFOA) has a very fast convergence rate. In addition, CFOA is compared with recently developed chaos enhanced algorithms such as chaotic bat algorithm, chaotic accelerated particle swarm optimization, chaotic firefly algorithm, chaotic artificial bee colony algorithm, and chaotic cuckoo search. Overall research findings show that FOA with Chebyshev map show superiority in terms of reliability of global optimality and algorithm success rate.", publisher = "Elsevier, Amsterdam", journal = "Knowledge-Based Systems", title = "Chaotic fruit fly optimization algorithm", pages = "458-446", volume = "89", doi = "10.1016/j.knosys.2015.08.010" }
Mitić, M., Vuković, N., Petrović, M.,& Miljković, Z.. (2015). Chaotic fruit fly optimization algorithm. in Knowledge-Based Systems Elsevier, Amsterdam., 89, 446-458. https://doi.org/10.1016/j.knosys.2015.08.010
Mitić M, Vuković N, Petrović M, Miljković Z. Chaotic fruit fly optimization algorithm. in Knowledge-Based Systems. 2015;89:446-458. doi:10.1016/j.knosys.2015.08.010 .
Mitić, Marko, Vuković, Najdan, Petrović, Milica, Miljković, Zoran, "Chaotic fruit fly optimization algorithm" in Knowledge-Based Systems, 89 (2015):446-458, https://doi.org/10.1016/j.knosys.2015.08.010 . .