The Ant Lion Optimizer
By Seyed Mohammad Mirjalili. Advances in Engineering Software, 2015
3,051 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computational Theory and Mathematics
View Paper: https://www.semanticscholar.org/paper/5f49a22c1b36aa04c67e287fbd494b636ae005aa
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Tansel Dökeroğlu
- Ali Asghar Heidari
- Seyedali Mirjalili
- Ayça Deniz
- Hakan Ezgi Kiziloz
- Amir H. Gandomi
- Huiling Chen
- Laith Mohammad Abualigah
In Computational Theory and Mathematics
- Tansel Dökeroğlu
- Ali Asghar Heidari
- Seyedali Mirjalili
- Ayça Deniz
- Hakan Ezgi Kiziloz
- Amir H. Gandomi
- Hossam Faris
- Ibrahim Aljarah
Citations in the corpus
- A survey on new generation metaheuristic algorithms (2019, background): “Mirjalili (2015b) proposes Moth-Flame Optimization (MFO) algorithm.”
- Dragonfly algorithm: a new meta-heuristic optimization technique for solving single-objective, discrete, and multi-objective problems (2015, background): “Despite the significant number of recent publications in this field [21–29], there are still other swarming behaviours in nature that have not gained deserved attention.”
- Multi-objective ant lion optimizer: a multi-objective optimization algorithm for solving engineering problems (2016, background): “In order to propose the multi-objective version of the ALO algorithm [38], the fundamentals of this algorithm should be discussed first.”
- An exhaustive review of the metaheuristic algorithms for search and optimization: taxonomy, applications, and open challenges (2023, background): “(2017) 327 Monkey Search (MS) Mucherino and Seref (2007) 328 Mosquito Flying Optimization (MFO) Alauddin (2016) 329 Moth Flame Optimization Algorithm (MFO) Mirjalili (2015b) 330 Moth Search Algorithm (MSA) Wang (2018) 331 Mouth Breeding Fish Algorithm (MBF) Jahani and Chizari (2018) 332 Mox Optimiza”
- Coronavirus herd immunity optimizer (CHIO) (2020, background): “…swarm optimization (PSO) [10], ant colony optimization (ACO) [11], cuckoo search (CS) [19], bat algorithm (BA) [20], ant lion optimizer (ALO) [21], butterfly optimization algorithm (BOA) [22], dragonfly algorithm (DA) [23], fruit fly optimization algorithm (FOA) [24], grey wolf optimizer (GWO)…”
- An efficient binary Salp Swarm Algorithm with crossover scheme for feature selection problems (2018, methodology): “The Ant Lion Optimizer (ALO) [39] has been employed as a search strategy in a wrapper FS method in [40].”
- Red fox optimization algorithm (2021, methodology): “BA CSA DA FA FPA MFO RFO WWO 𝑥1 57.53212 55.46532 51.65482 51.98541 54.36485 48.32162 52.1581 57.26512 𝑥2 19.75461 16.23612 17.65231 25.65891 23.65232 18.62531 23.01251 23.56412 𝑥3 19.32561 22.31521 22.63215 14.65912 18.65231 20.4121 16.1401 15.65423 𝑥4 44.65231 45.92531 51.02643 46.95641 56.124”
- Northern Goshawk Optimization: A New Swarm-Based Algorithm for Solving Optimization Problems (2021, background): “The time-consuming process of solving complex problems, high-dimensional problems, non-convex problems, problems for non-differentiable objective functions, problems with random or unknown search space are other issues that challenge deterministic methods [2].”
- Optimal distributed generation planning in active distribution networks considering integration of energy storage (2018, methodology): “After consuming the prey, ant lions throw the leftovers outside the pit and prepare the pit for the next hunt [38].”
- An efficient modified grey wolf optimizer with Lévy flight for optimization tasks (2017, methodology): “These classic benchmark functions have been employed by various researchers to assess their algorithms [23, 61-64].”