The DOI matches its Crossref record.
Finding approximate solutions of NP-hard optimization and TSP problems using elephant search algorithm
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Solving multiobjective problems is a huge challenge as demonstrated in robotics, bioinformatics, energy and power.
“Despite the merits of bioinspired optimizers, solving multiobjective problems is a huge challenge as demonstrated in different application domains (e.g. robotics [66], bioinformatics [67], energy and power [68]).”
From Applications and Challenges of Artificial Intelligence in Space Missions (2024) · cites this paper as [66]
Citations
Cites
No references could be resolved yet.
Research works printed but not linked: 13
- Reynolds CW (1987) Flocks, herds and schools: a distributed behavioral model. Comput Graph 21(4):25–34 · DOI · Paper page
- Jarraya B, Bouri A (2012) Metaheuristic optimization backgrounds: a literature review. Int J Contemp Bus Stud 3(12):31–44
- Hoang DT (2008) Metaheuristics for NP-hard combinatorial optimization problems. PhD Thesis, Electrical and Computer Engineering, National University of Singapore
- Yang XS (2010) Engineering optimization: an introduction with metaheuristic applications. Wiley, Hoboken, NJ p 347 · DOI
- Yang XS (2010) A new metaheuristic bat-inspired algorithm. In: Nature inspired cooperative strategies for optimization (NICSO), Series Studies in Computational Intelligence, vol 284, pp 65–74 · DOI
- Yang XS (2009) Firefly algorithms for multimodal optimization. Stochastic algorithms: foundations and applications, SAGA 2009. Lecture Notes in Computer Sciences 5792:169–178 · DOI
- Kennedy J, Eberhart R (1995) Particle swarm optimization. In: Proceedings of IEEE international conference on neural networks IV, pp 1942–1948 · DOI · Paper page
- Fong S, Deb S, Yang X-S (2015) A heuristic optimization methodinspired by wolf preying behavior. Neural Comput Applic 26:1725–1738 · DOI
- Phelps S, McBurney P, Parsons S (2010) Evolutionary mechanism design: a review. Auton Agent Multi-Agent Syst 21:237–264 · DOI
- Yang XS, Deb S, Fong S (2014) Metaheuristic algorithms: optimal balance of intensification and diversification. Appl Math Inf Sci 8(3):977–983 · DOI
- Vidya TNC, Sukumar R (2005) Social and reproductive behaviour in elephants. Curr Sci 89(7):1200–1207
- Fong S, Wong R, Pichappan P (2015) Debunking the designs of contemporary nature-inspired computing algorithms: from moving particles to roaming elephants. In: The fourth international conference on future generation communication technology (FGCT), IEEE Press, 29–31 July, pp 1–11 · DOI
- Deb S, Fong S, Tian ZH (2015) Elephant search algorithm for optimization problems. In: 2015 tenth international conference on digital information management (ICDIM) (Oct.) IEEE, Jeju · DOI
Cited by
Sorted by citations
Applications and Challenges of Artificial Intelligence in Space Missions
Oche, P. A., Ewa, G. A., & Ibekwe, N. (2024) · IEEE Access · doi:10.1109/access.2021.3132500 · Cited by 68
“…behavior of cats. h. Moth Flame Optimization (MFO) is a novel nature-inspired optimization paradigm inspired by the navigation method of moths in nature called transverse orientation [64]. i. Elephant Search Algorithm (ESA) [65], was inspired by the behavioral characteristics of elephant herds and.”
Method
Metadata
- Authors
- Deb, S., Fong, S., Tian, Z., Wong, R. K., Mohammed, S., & Fiaidhi, J.
- Affiliations
- University of Macau (MO)
- UNSW Sydney (AU)
- Lakehead University (CA)
- Corresponding author
- Fong, Simon
- Venue
- The Journal of Supercomputing
- Published
- 2016-05-24
- Volume
- 72
- Issue
- 10
- Pages
- 3960-3992
- ISSN
- 0920-8542 (ISSN-L)
- 1573-0484
- OpenAlex
- W2399372960
- Cited by
- 25
- References
- 0
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 3 · 2023: 2 · 2021: 4 · 2020: 2 · 2019: 4 · 2018: 5 · 2017: 2 · 2016: 1
- FWCI
- 3.30
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- The Journal of Supercomputing (publishedVersion)
- Funders
- Universidade de Macau (MYRG2015-00128-FST)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Metaheuristic Optimization Algorithms Research
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Immune Systems Applications
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Antenna Design and Optimization
- Keywords
- traveling salesman problem, NP-hard optimization, bio-inspired metaheuristics, approximate solutions, exploration-exploitation balance, swarm intelligence
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