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S. Yang, M. Li, X. Liu, and J. Zheng. A grid-based evolutionary algorithm for many-objective optimization. IEEE Transactions on Evolutionary Computation, 17(5): 721-736, 2013. [PDF] [supplement] [C code] [C++ code in OTL]
S. Yang, M. Li, X. Liu, and J. Zheng. A grid-based evolutionary algorithm for many-objective optimization. IEEE Transactions on Evolutionary Computation, 17(5): 721-736, 2013. [PDF] [supplement] [C code] [C++ code in OTL]
M. Li, J. Zheng, R. Shen, K. Li, and Q. Yuan. A grid-based fitness strategy for evolutionary many-objective optimization. Genetic and Evolutionary Computation Conference, 463-470, 2010. (Nominated to the Best Paper Award). [C code]
M. Li, J. Zheng, R. Shen, K. Li, and Q. Yuan. A grid-based fitness strategy for evolutionary many-objective optimization. Genetic and Evolutionary Computation Conference, 463-470, 2010. (Nominated to the Best Paper Award). [C code]
Brief:
Brief:
Exploit the potential of grid-based fitness and selection criteria to strengthen the selection pressure towards the optimal direction while maintaining an extensive and uniform distribution among solutions.
Exploit the potential of grid-based fitness and selection criteria to strengthen the selection pressure towards the optimal direction while maintaining an extensive and uniform distribution among solutions.
Results:
Results:
The solution sets of GrEA and other five multi-/many-object algorithms on the 8-objective DTLZ3 problem.
The solution sets of GrEA and other five multi-/many-object algorithms on the 10-objective DTLZ7 problem.
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