A novel heuristic optimization method: charged system search

By Ali Kaveh, Siamak Talatahari. 2010

1,358 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Theory and Mathematics

View Paper: https://www.semanticscholar.org/paper/dc907f6cad84606d14019eccc6fada1733a08b4b

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Citations in the corpus

A new optimization method: Dolphin echolocation (2013, methodology): “One of the most recent meta-heuristic algorithms is the Charged System Search (CSS) proposed by Kaveh and Talatahari [16] that uses the electric laws of physics and the Newtonian laws of mechanics to guide the Charged Particles (CPs) to explore the locations of the optimum.”
Coronavirus herd immunity optimizer (CHIO) (2020, neutral): “…water cycle algorithm (WCA) [37], electromagnetism-like mechanism (EM) [38], gravitational search algorithm (GSA) [39], charged system search (CSS) [40], big bang–big crunch (BBBC) [41], and Henry gas solubility optimization (HGSO) [42] Human-Based Fireworks algorithm (FA) [15], harmony search…”
Fire Hawk Optimizer: a novel metaheuristic algorithm (2022, methodology): “Table 25 Optimum design sections of the 15-story benchmark structure HPSACO Hybrid algorithm based on particle swarm, ant colony and harmony search algorithms, HBB– BC Hybrid big bang-big crunch and particle swarm optimization algorithms, ICA Imperialist Competitive Algorithm, DE Differential Evolut”
Binary bat algorithm (2013, background): “Some of them are particle swarm optimization (PSO) [1], genetic algorithm (GA) [2], simulated annealing (SA) [3], ant colony optimization (ACO) [4], gravitational search algorithm [5], charged system search [6], magnetic charged system search [7], ray optimization [8], and dolphin echolocation [9].”
Feature selection via a novel chaotic crow search algorithm (2017, methodology): “Some of these algorithms are gradient descent algorithm [10], discrete particle swarm optimization (DPSO) [46], tabu search [56], elephant herding optimization (EHO) [11], firefly algorithm (FA) [12], harmony search (HS) [14], charged system search (CSS) [25], bird swarm algorithm (BSA) [32], animal”
Equilibrium optimizer: A novel optimization algorithm (2020, neutral): “Charged System Search [18] takes advantage of combining rules of physics (Coulomb’s law of electrostatics) and mechanics (Newtonian laws of mechanics) to perform the optimization.”
Spider wasp optimizer: a novel meta-heuristic optimization algorithm (2023, methodology): “1983), charged system search (Kaveh and Talatahari 2010), big-bang bigcrunch (Erol and Eksin 2006), central force optimization (Formato 2007), curved space optimization (Moghaddam et al.”
Seagull optimization algorithm: Theory and its applications for large-scale industrial engineering problems (2019, methodology): “Some of the other popular algorithms are: Big-Bang Big-Crunch (BBBC) [23], Charged System Search (CSS) [24], Black Hole (BH) [25] algorithm, Central Force Optimization (CFO) [26], Small-World Optimization Algorithm (SWOA) [27], and Ray Optimization (RO) algorithm [28].”
Firefly algorithm with chaos (2013, background): “These techniques attempt to reproduce social behavior [2] or natural phenomena [3].”
Bat algorithm: a novel approach for global engineering optimization (2012, background): “For example, particle swarm optimization was developed based on the swarm behavior of birds and fish (Kennedy and Eberhart 1995) or charged system search inspired from physical processes (Kaveh and Talatahari 2010).”
An improved grey wolf optimizer for solving engineering problems (2021, background): “Some popular algorithms in this category are big bang-big crunch (BB-BC) (Erol et al., 2006), gravitational search algorithm (GSA) (Rashedi et al., 2009), charged system search (CSS) (Kaveh et al., 2010), ray optimization (RO) (Kaveh et al., 2012), black hole (BH) (Hatamlou, 2013), atom search optim”
Geometry and topology optimization of geodesic domes using charged system search (2011, methodology): “Recently, the authors proposed a new optimization approach, so-called Charged System Search ( Kaveh and Talatahari 2010c, d), which utilizes a number of Charged Particle (CP).”
Grasshopper Optimisation Algorithm: Theory and application (2017, positive): “Solving structural design problems using stochastic optimisation techniques has been a popular research direction in the literature [46-54].”
Nature-Inspired Optimization Algorithms: Challenges and Open Problems (2020, background): “• Other Algorithms: There are many other nature-inspired algorithms, such as simulated annealing [31], bacteria foraging optimization [32], biogeographybased optimization [33], gravitational search [34], charged particle system [35], black-hole algorithm [36], krill herd algorithm [37], eagle strate”