An improved differential evolution algorithm using efficient adapted surrogate model for numerical optimization
Contemporary real-world optimization benchmarks are subject to many constraints and are often high-dimensional problems. Typically, such problems are expensive in terms of computational time and cost. Conventional constraint-based solvers that are used to tackle such problems require a considerable...
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Main Authors: | , , , |
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Other Authors: | |
Format: | Article |
Language: | English |
Published: |
2020
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Subjects: | |
Online Access: | https://hdl.handle.net/10356/142645 |
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Institution: | Nanyang Technological University |
Language: | English |