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Artifical bee colony algorithm using problem-specific neighborhood strategies for the tree t-spanner problem
Affiliation:1. Artificial Intelligence Research Institute (IIIA-CSIC), Campus UAB, Bellaterra, Spain;2. Computer Science Department, Universitat Politècnica de Catalunya – BarcelonaTech, Barcelona, Spain;1. Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur, Malaysia;2. Faculty of Engineering, Tunku Abdul Rahman University College, Kuala Lumpur, Malaysia;3. Faculty of Engineering, Computing and Science, Swinburne University of Technology (Sarawak Campus), Malaysia;1. School of Management, Huazhong University of Science and Technology, No. 1037, Luoyu Road, Wuhan, China;2. School of Computer Science, Huazhong University of Science and Technology, No. 1037, Luoyu Road, Wuhan, China;3. LERIA, Université d’Angers, 2 Boulevard Lavoisier, 49045 Angers, France;4. Institut Universitaire de France, 1 Rue Descartes, 75231 Paris, France;1. Opole University, pl. Kopernika 11a, 45-040 Opole, Poland;2. Wrocław University of Economics, Komandorska 118/120, 53-345 Wrocław, Poland;1. Universidade Federal Rural de Pernambuco, Unidade Acadêmica de Garanhuns, PE, Brazil;2. Universidade Federal de Pernambuco, Centro de Informática, Recife, PE, Brazil;3. University of Antwerp, IMEC – Vision Lab, Antwerp, Belgium;4. Nokia, Antwerp, Belgium;1. Dpt. of Computer Architecture and Communications, University of Extremadura, Spain;2. Dpt. of Computer Architecture and Automation, Complutense University of Madrid, Spain;3. Dpt. of Computer Science, King Juan Carlos University, Spain
Abstract:
Keywords:Tree spanner  Weighted graph  Problem-specific knowledge  Swarm intelligence  Artificial bee colony algorithm
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