The DOI matches its Crossref record; 44 of the 44 references it cites were found in a registry or an index.
Grasshopper optimization algorithm for multi-objective optimization problems
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Citations
Cites
A fast and elitist multiobjective genetic algorithm: NSGA-II
Deb, K., Pratap, A., Agarwal, S., & Meyarivan, T. (2002) · IEEE Transactions on Evolutionary Computation · doi:10.1109/4235.996017 · Cited by 50,053
Storn, R., & Price, K. (1997) · Journal of Global Optimization · doi:10.1023/a:1008202821328 · Cited by 29,569
Multi-Objective Optimization Using Evolutionary Algorithms
Deb, K., & Kalyanmoy, D. (2001) · Andalas University Repository (Andalas University) · Cited by 14,918
No free lunch theorems for optimization
Wolpert, D. H., & Macready, W. G. (1997) · IEEE Transactions on Evolutionary Computation · doi:10.1109/4235.585893 · Cited by 14,237
Muiltiobjective Optimization Using Nondominated Sorting in Genetic Algorithms
Srinivas, N., & Deb, K. (1994) · Evolutionary Computation · doi:10.1162/evco.1994.2.3.221 · Cited by 6,935
(2007) · Handbook of Approximation Algorithms and Metaheuristics · doi:10.1201/9781420010749-33 · Cited by 6,607
Comparison of Multiobjective Evolutionary Algorithms: Empirical Results
Zitzler, E., Deb, K., & Thiele, L. (2000) · Evolutionary Computation · doi:10.1162/106365600568202 · Cited by 5,697
Survey of multi-objective optimization methods for engineering
Marler, R. T., & Arora, J. S. (2004) · Structural and Multidisciplinary Optimization · doi:10.1007/s00158-003-0368-6 · Cited by 4,710
Kennedy, J. (2011) · Encyclopedia of Machine Learning · doi:10.1007/978-0-387-30164-8_630 · Cited by 2,989
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Self-citation
Research works printed but not linked: 10
- Padhye N, Bhardawaj P, Deb K (2010) Improving differential evolution by altering steps in EC. In: Asia-Pacific conference on simulated evolution and learning, pp 146–155
- Padhye N, Zuo L, Mohan CK, Varshney PK (2009) Dynamic and evolutionary multi-objective optimization for sensor selection In sensor networks for target tracking. In: Proceedings of the international joint conference on computational intelligence - volume 1: ICEC, (IJCCI 2009). ScitePress, INSTICC, pp 160–167. doi: 10.5220/0002324901600167 , ISBN: 978-989-674-014-6 · doi:10.5220/0002324901600167
- Padhye N, Zuo L, Mohan CK, Varshney P (2009) Dynamic and evolutionary multi-objective optimization for sensor selection in sensor networks for target tracking. In: IJCCI, pp 160–167
- Padhye N, Deb K (2010) Evolutionary multi-objective optimization and decision making for selective laser sintering. In: Proceedings of the 12th annual conference on genetic and evolutionary computation, pp 1259–1266 · doi:10.1145/1830483.1830709
- Padhye N (2008) Topology optimization of compliant mechanism using multi-objective particle swarm optimization. In: Proceedings of the 10th annual conference companion on genetic and evolutionary computation, pp 1831–1834 · doi:10.1145/1388969.1388983
- Deb K, Padhye N, Neema G (2007) Multiobjective evolutionary optimization-interplanetary trajectory optimization with swing-bys using evolutionary multi-objective optimization. Lect Notes Comput Sci 4683:26–35 · doi:10.1007/978-3-540-74581-5_3
- Kollat JB, Reed P (2007) A framework for visually interactive decision-making and design using evolutionary multi-objective optimization (VIDEO). Environ Model Softw 22:1691– 1704 · doi:10.1016/j.envsoft.2007.02.001
- Topaz CM, Bernoff AJ, Logan S, Toolson W (2008) A model for rolling swarms of locusts. Eur Phys J Special Topics 157:93– 109 · doi:10.1140/epjst/e2008-00633-y
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- Zitzler E, Laumanns M, Thiele L, Zitzler E, Zitzler E, Thiele L et al (2001) SPEA2: Improving the strength Pareto evolutionary algorithm, ed: Eidgenössische Technische Hochschule Zürich (ETH). In: Institut für Technische Informatik und Kommunikationsnetze (TIK)
Cited by
RUN beyond the metaphor: An efficient optimization algorithm based on Runge Kutta method
Ahmadianfar, I., Heidari, A. A., Gandomi, A. H., Chu, X., & Chen, H. (2021) · Expert Systems with Applications · doi:10.1016/j.eswa.2021.115079 · Cited by 1,115
Yuvaraj, T., Devabalaji, K. R., Kumar, J. A., Thanikanti, S. B., & Nwulu, N. I. (2024) · IEEE Access · doi:10.1109/access.2023.3349274 · Cited by 249
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
“Recently Grasshopper Optimization Algorithm (GOA) was proposed and it has been proven to show very fast convergence speed toward the optimal solutions [75].”
Background
Metadata
- Authors
- Mirjalili, S. Z., Mirjalili, S., Saremi, S., Faris, H., & Aljarah, I.
- Venue
- Applied Intelligence
- Published
- 2017-08-04
- Volume
- 48
- Issue
- 4
- Pages
- 805-820
- ISSN
- 0924-669X (ISSN-L)
- 1573-7497
- OpenAlex
- W2742961367
- Cited by
- 758
- References
- 44
- FWCI
- 33.50
- Type
- journal article
- Language
- en
- Open access
- green
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- Mirjalili, S. Z., Mirjalili, S., Saremi, S., Faris, H., & Aljarah, I. (2018). Grasshopper optimization algorithm for multi-objective optimization problems. Applied Intelligence. https://doi.org/10.1007/s10489-017-1019-8
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