Problem Deflnitions and Evaluation Criteria for the CEC 2006 Special Session on Constrained Real-Parameter Optimization

By Jing J. Liang, Thomas Philip Runarsson, Efrén Mezura-Montes, Maurice Clerc, Ponnuthurai Nagaratnam Suganthan, Carlos Artemio Coello Coello, Kalyanmoy Deb. 2006

669 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/c8360687b24fba42bd284e0887807497433e4d39

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Citations in the corpus

Handling Constrained Multiobjective Optimization Problems With Constraints in Both the Decision and Objective Spaces (2019, methodology): “In DOC, we borrow the decision constraints from [41] based on the following two considerations: 1) the decision constraints in [41] have been well-studied during the past 12 years and we have already carried out a series of work to ascertain their properties [42]–[44] and 2) the minimum value of g…”
Constraint-handling in nature-inspired numerical optimization: Past, present and future (2011, background): “This version obtained the best overall results in a competition on constrained real-parameter optimization in 2006, in which a set of 24 test problems were solved [139].”
Constrained Optimization by the ε Constrained Differential Evolution with Gradient-Based Mutation and Feasible Elites (2006, background): “Twenty four benchmark problems and format for reporting results are specified in “Problem Definitions and Evaluation Criteria for the CEC 2006 Special Session on Constrained Real-Parameter Optimization” [28].”
Differential evolution with dynamic stochastic selection for constrained optimization (2008, methodology): “Moreover, although 24 benchmark functions are defined in [ 34 ], two of the functions are not used to evaluate our algorithm DSS-MDE because no feasible optimal solutions ever been found for these two problems (g20 and g22) so far.”
Cultured differential evolution for constrained optimization (2006, background): “The selection criteria are detailed in Section III. features can be found in [ 17 ].”
Jaya: A simple and new optimization algorithm for solving constrained and unconstrained optimization problems (2016, unknown): “The number of design variables and their ranges are different for each problem (Liang et al., 2006; Karaboga and Basturk, 2007; Karaboga and Akay, 2011).”
Differential Evolution: A Survey of the State-of-the-Art (2011, methodology): “The εDE algorithm of Takahama and Sakai [97] uses a dynamic control of the allowable constraint violation specified by the ε-level and it achieved the first rank in the CEC 2006 competition on the constrained real-parameter optimization [47].”