Novel composition test functions for numerical global optimization

By Jing J. Liang, Ponnuthurai Nagaratnam Suganthan, Kalyanmoy Deb. Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005., 2005

464 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Theory and Mathematics

View Paper: https://www.semanticscholar.org/paper/2004e25c7239c71b18b8fa3a0fea78721f6ca69e

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Citations in the corpus

Dynamic multi-swarm particle swarm optimizer (2005, methodology): “1 ( ) cos( ) 1 4000 i f x = + ∏ In order to avoid some problems existing in the benchmark functions as we have analyzed in [11], we shifted the global optimum points and rotated the test functions according to Salomon’s method [12] except sphere function since sphere is still a sphere after…”
Comprehensive learning particle swarm optimizer for global optimization of multimodal functions (2006, methodology): “16) Composition function 5 (CF5) in [38]: (CF2) is composed using ten different benchmark functions: two rotated Rastrigin’s functions, two rotated Weier-strass functions, two rotated Griewank’s functions, two rotated Ackley’s functions, and two sphere functions.”
Frankenstein's PSO: A Composite Particle Swarm Optimization Algorithm (2009, unknown): “Since most of these functions have their global optimum located at the origin, we shifted it to avoid any possible search bias as suggested by Liang et al. [18].”
Moth-flame optimization algorithm: A novel nature-inspired heuristic paradigm (2015, background): “Note that the composite test functions are taken from CEC 2005 special session [52,53].”
Self-adaptive learning based particle swarm optimization (2011, background): “As discussed in [29,43,53], there exist two major problems in the test functions used in previous literatures [64]: (1) the global optimum is”
The Ant Lion Optimizer (2015, unknown): “The last group of test functions, composite functions, are mostly the combined, rotated, shifted, and biased version of other uni-modal and multi-modal test functions [59,60].”
Improving the shuffled complex evolution scheme for optimization of complex nonlinear hydrological systems: Application to the calibration of the Sacramento soil‐moisture accounting model (2010, methodology): “[28] We employed a composition benchmark function designed by Liang et al. [2005] to demonstrate how easily this nonfigurative phenomenon will occur in high‐dimensional cases and the fatal consequences.”
Equilibrium optimizer: A novel optimization algorithm (2020, unknown): “More details about the composition function can be found in CEC 2005 technical report [26].”
An efficient modified grey wolf optimizer with Lévy flight for optimization tasks (2017, unknown): “For this purpose, 29 unconstrained problems including a set of composition test cases from CEC 2005 are evaluated [65].”
A New Metaheuristic Bat-Inspired Algorithm (2010, methodology): “In addition, we have also used other standard test functions for numerical global optimization [10] such as Ackley’s function In our implementation, we use n = 25 to 50 virtual bats, and α = 0 .”
A Self-Learning Particle Swarm Optimizer for Global Optimization Problems (2012, methodology): “H Com f13(~x) =Hybrid Composition function (CF4) in [26] [-5, 5] 0”
Multi-Verse Optimizer: a nature-inspired algorithm for global optimization (2015, background): “F 19, are six composite benchmark functions provided by CEC 2005 special session [24, 25].”