Constraint-handling in genetic algorithms through the use of dominance-based tournament selection

By Carlos Artemio Coello Coello, Efrén Mezura-Montes. Advanced Engineering Informatics, 2002

846 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Theory and Mathematics

View Paper: https://www.semanticscholar.org/paper/c6e9abf60aacc0242f50fbd27be81de05a2ca8e1

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Citations in the corpus

Hybrid Nelder-Mead simplex search and particle swarm optimization for constrained engineering design problems (2009, methodology): “…that have been obtained by GA based on a co-evolution model (GA1) (Coello, 2000), GA with a feasibility based tournament selection scheme (GA2) (Coello & Montes, 2002), the evolutionary programming (EP) (Coello & Becerra, 2004), co-evolutionary particle swarm optimization (CPSO) (He & Wang,…”
Slime mould algorithm: A new method for stochastic optimization (2020, neutral): “= 30 × 1 psi, = 12 × 10 psi ma = 13600psi, σma = 30000psi In this problem, SMA was compared with MFO[23], SSA[52], Random[70], Siddall[71], Ragsdell[70], Coello and Montes[72], GWO[21], WOA[50], GSA, Simplex[70] and David[70].”
An effective co-evolutionary differential evolution for constrained optimization (2007, methodology): “Table 6 Comparison of the best solution for Example 9 found by different methods Design variables CDE Sandgren [25] Kannan [24] Deb [23] Coello [4] Coello and Montes [8] CPSO [6]”
A Multiobjective Optimization-Based Evolutionary Algorithm for Constrained Optimization (2006, methodology): “In order to evaluate the capabilities of a set of constrainthandling methods based on multiobjective optimization techniques, Mezura and Coello [28] presented a comprehensive experimental study, in particular, focusing on four of this kind of methods.”
Tuna Swarm Optimization: A Novel Swarm-Based Metaheuristic Algorithm for Global Optimization (2021, background): “Algorithm Optimal values for variables Optimal cost x1 x2 x3 GA3 [59] 0.”
Harris hawks optimization: Algorithm and applications (2019, neutral): “The results of HHO are compared to those of GWO [55], GA [73], HPSO [83], G-QPSO [84], WEO [79], IACO [85], BA [80], MFO [56], CSS [86], ESs [81], CPSO [76], BIANCA [87], MDDE [88], DELC [77], WOA [18], GA3 [74], Lagrangian multiplier (Kannan) [18], and Branch-bound (Sandgren) [18].”