A Numerical Evaluation of Several Stochastic Algorithms on Selected Continuous Global Optimization Test Problems

By M. Montaz Ali, Charoenchai Khompatraporn, Zelda B. Zabinsky. Journal of Global Optimization, 2005

594 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Theory and Mathematics, Numerical Analysis

View Paper: https://www.semanticscholar.org/paper/d0206eb6a43e51253590504f6d42e0bed16227ae

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Citations in the corpus

Opposition-Based Differential Evolution (2008, background): “For more information about these functions, see [31].”
A particle swarm pattern search method for bound constrained global optimization (2007, methodology): “[2], the following scaled performance profile measure tp,s = f̄p,s − f ∗ p fp,w − f ∗ p (10)”
Benchmarking Derivative-Free Optimization Algorithms (2009, methodology): “This is a convenient unit that can be easily translated into function evaluations.”
Theory and Use of the EM Algorithm (2011, background): “For more on state-of-the-art global optimization, see for example [1, 23, 24, 28, 38, 46].”
Spider Monkey Optimization algorithm for numerical optimization (2014, background): “Test problems f1 − f19 and f24 − f26 are taken from [1] and test problems f20 − f23 are taken from [36] with the associated offset values.”
Dynamically dimensioned search algorithm for computationally efficient watershed model calibration (2007, methodology): “Since it is typical in global optimization to compare average algorithm performance [Ali et al., 2005], average algorithm convergence in terms of the best solution found is plotted against the number of objective function evaluations for each algorithm. In other words, for a particular algorithm, th”
A novel population initialization method for accelerating evolutionary algorithms (2007, background): “The value of a and c are given in [17].”
Rosenbrock artificial bee colony algorithm for accurate global optimization of numerical functions (2011, methodology): “[4,9,20,35,40,44,50,53,55,71,72], was used to test the performance of the proposed approach.”
A review of recent advances in global optimization (2009, methodology): “They applied their method on a wastewater treatment plant model (Alex et al. 1999) and the Tennessee Eastman Process (Downs and Vogel 1993).”
A literature survey of benchmark functions for global optimisation problems (2013, background): “Box-Betts Quadratic Sum Function [4] (Continuous, Diﬀerentiable, Non-Separable, Non-Scalable, Multimodal) where 22.”