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Borg: An Auto-Adaptive Many-Objective Evolutionary Computing Framework
Asynchronous Master-Slave Parallelization of Differential Evolution for Multi-Objective Optimization
No Free Lunch and Benchmarks
Evolution by Adapting Surrogates
Integrating Iterative Crossover Capability in Orthogonal Neighborhoods for Scheduling Resource-Constrained Projects
Issues
Borg: An Auto-Adaptive Many-Objective Evolutionary Computing FrameworkBorg: An Auto-Adaptive MOEA FrameworkD. Hadka and P. Reed
Evolutionary Computation (2013) 21 (2): 231–259.
Asynchronous Master-Slave Parallelization of Differential Evolution for Multi-Objective OptimizationAMS Parallelization of DEMOM. Depolli, R. Trobec, and B. Filipič
Evolutionary Computation (2013) 21 (2): 261–291.
No Free Lunch and BenchmarksNo Free Lunch and BenchmarksE. A. Duéñez-Guzmán and M. D. Vose
Evolutionary Computation (2013) 21 (2): 293–312.
Evolution by Adapting SurrogatesEvolution by Adapting SurrogatesM. N. Le, Y. S. Ong, S. Menzel, Y. Jin, and B. Sendhoff
Evolutionary Computation (2013) 21 (2): 313–340.
Integrating Iterative Crossover Capability in Orthogonal Neighborhoods for Scheduling Resource-Constrained ProjectsRCPSP: Crossover in Orthogonal NeighborhoodsR. Zamani
Evolutionary Computation (2013) 21 (2): 341–360.
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