Test Problems for Large-Scale Multiobjective and Many-Objective Optimization
By Ran Cheng, Yaochu Jin, Markus Olhofer, Bernhard Sendhoff. IEEE Transactions on Cybernetics, 2017
351 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computational Theory and Mathematics
View Paper: https://www.semanticscholar.org/paper/1ee2cd6a19b6e18686a86b20e7099466a3de0616
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Citations in the corpus
- Efficient Large-Scale Multiobjective Optimization Based on a Competitive Swarm Optimizer (2020, methodology): “3) To verify the effectiveness of the proposed LMOCSO in solving large-scale MOPs, it is compared with four state-of-the-art MOEAs on the large-scale multi-objective test suite LSMOP [28].”
- A benchmark test suite for evolutionary many-objective optimization (2017, background): “Recently, researchers have also designed/presented some problem suites specially for many-objective optimization [11–16].”
- PlatEMO: A MATLAB Platform for Evolutionary Multi-Objective Optimization [Educational Forum] (2017, methodology): “A/D-M2M [19] 2014 The test problems designed for MOEA/D-M2M F1–F10 for IM-MOEA [67] 2015 The test problems designed for IM-MOEA BT1–BT9 [83] 2016 Multi-objective test problems with bias LSMOP1–LSMOP9 [84] 2016 Large-scale multi-objective test problems II. In addition, there are a lot of performance ”
- Evolutionary Large-Scale Multi-Objective Optimization: A Survey (2021, background): “In particular, (1) is generally called an LSMOP if the number of decision variables d is equal to or larger than 100 [23, 26].”
- An Evolutionary Algorithm for Large-Scale Sparse Multiobjective Optimization Problems (2020, background): “As for other test suites with complicated Pareto sets [61], [62], few MOPs in them have sparse Pareto optimal solutions.”
- Benchmark Problems and Performance Indicators for Search of Knee Points in Multiobjective Optimization (2020, methodology): “…multi-objective benchmark problems with a complex knee structure in terms of symmetry, differentiability, scalability and degeneration of the PoF, while still considering other complexities in problem structures [48], [52] such as multi-modality, non-uniformity, scalability of PoF and separability.”