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- Publisher Website: 10.1145/3067695.3082054
- Scopus: eid_2-s2.0-85026890209
- WOS: WOS:000625865500201
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Conference Paper: Design Of An Efficient Hyper-heuristic Algorithm Cma-vns For Combinatorial Black-box Optimization Problems
Title | Design Of An Efficient Hyper-heuristic Algorithm Cma-vns For Combinatorial Black-box Optimization Problems |
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Authors | |
Keywords | CMA-VNS Combinatorial black-box optimization Hyperheuristics NK-model |
Issue Date | 2017 |
Publisher | Association for Computing Machinery. |
Citation | The Genetic and Evolutionary Computation Conference (GECCO), Berlin, Germany, 15-19 July 2017. In Proceedings of the Genetic and Evolutionary Computation Conference Companion, p. 1157-1162 How to Cite? |
Abstract | We present a hyper-heuristic algorithm for solving combinatorial black-box optimization problems. The algorithm named CMA-VNS stands for a hybrid of variants of Covariance Matrix Adaptation Evolution Strategy (CMA-ES) and Variable Neighborhood Search (VNS). The framework design and the design profiles of variants of CMA-VNS are introduced to enhance the intensification of searching for conventional CMA-ES solvers. We explain the parameter configuration details, the heuristic profile selection, and the rationale of incorporating machine learning methods during the study. Experimental tests and the results of the first and the second Combinatorial Black-Box Optimization Competitions (CB-BOC 2015, 2016) confirmed that CMA-VNS is a competitive hyper-heuristic algorithm. |
Persistent Identifier | http://hdl.handle.net/10722/241820 |
ISBN | |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Xue, F | - |
dc.contributor.author | Shen, G | - |
dc.date.accessioned | 2017-06-20T01:49:00Z | - |
dc.date.available | 2017-06-20T01:49:00Z | - |
dc.date.issued | 2017 | - |
dc.identifier.citation | The Genetic and Evolutionary Computation Conference (GECCO), Berlin, Germany, 15-19 July 2017. In Proceedings of the Genetic and Evolutionary Computation Conference Companion, p. 1157-1162 | - |
dc.identifier.isbn | 978-1-4503-4939-0 | - |
dc.identifier.uri | http://hdl.handle.net/10722/241820 | - |
dc.description.abstract | We present a hyper-heuristic algorithm for solving combinatorial black-box optimization problems. The algorithm named CMA-VNS stands for a hybrid of variants of Covariance Matrix Adaptation Evolution Strategy (CMA-ES) and Variable Neighborhood Search (VNS). The framework design and the design profiles of variants of CMA-VNS are introduced to enhance the intensification of searching for conventional CMA-ES solvers. We explain the parameter configuration details, the heuristic profile selection, and the rationale of incorporating machine learning methods during the study. Experimental tests and the results of the first and the second Combinatorial Black-Box Optimization Competitions (CB-BOC 2015, 2016) confirmed that CMA-VNS is a competitive hyper-heuristic algorithm. | - |
dc.language | eng | - |
dc.publisher | Association for Computing Machinery. | - |
dc.relation.ispartof | Genetic and Evolutionary Computation Conference (GECCO) | - |
dc.rights | Genetic and Evolutionary Computation Conference (GECCO). Copyright © Association for Computing Machinery. | - |
dc.subject | CMA-VNS | - |
dc.subject | Combinatorial black-box optimization | - |
dc.subject | Hyperheuristics | - |
dc.subject | NK-model | - |
dc.title | Design Of An Efficient Hyper-heuristic Algorithm Cma-vns For Combinatorial Black-box Optimization Problems | - |
dc.type | Conference_Paper | - |
dc.identifier.email | Xue, F: xuef@hku.hk | - |
dc.identifier.authority | Xue, F=rp02189 | - |
dc.identifier.doi | 10.1145/3067695.3082054 | - |
dc.identifier.scopus | eid_2-s2.0-85026890209 | - |
dc.identifier.hkuros | 272519 | - |
dc.identifier.spage | 1157 | - |
dc.identifier.epage | 1162 | - |
dc.identifier.isi | WOS:000625865500201 | - |
dc.publisher.place | United States | - |