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- W4297367352 abstract "The development, assessment, and comparison of randomized search algorithms heavily rely on benchmarking. Regarding the domain of constrained optimization, the number of currently available benchmark environments bears no relation to the number of distinct problem features. The present paper advances a proposal of a scalable linear constrained optimization problem that is suitable for benchmarking Evolutionary Algorithms. By comparing two recent EA variants, the linear benchmarking environment is demonstrated." @default.
- W4297367352 created "2022-09-28" @default.
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- W4297367352 date "2018-07-26" @default.
- W4297367352 modified "2023-09-23" @default.
- W4297367352 title "A Linear Constrained Optimization Benchmark For Probabilistic Search Algorithms: The Rotated Klee-Minty Problem" @default.
- W4297367352 doi "https://doi.org/10.48550/arxiv.1807.10068" @default.
- W4297367352 hasPublicationYear "2018" @default.
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