A modified ant colony optimization algorithm for network coding resource minimization
The paper presents a modified ant colony optimization approach for the network coding resource minimization problem. It is featured with several attractive mechanisms specially devised for solving the network coding resource minimization problem: 1) a multi-dimensional pheromone maintenance mechanis...
| Main Authors: | , , , , , |
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| Format: | Article |
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Institute of Electrical and Electronics Engineers
2015
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| Online Access: | https://eprints.nottingham.ac.uk/31073/ |
| _version_ | 1848794122657202176 |
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| author | Wang, Zhaoyuan Xing, Huanlai Li, Tianrui Yang, Yan Qu, Rong Pan, Yi |
| author_facet | Wang, Zhaoyuan Xing, Huanlai Li, Tianrui Yang, Yan Qu, Rong Pan, Yi |
| author_sort | Wang, Zhaoyuan |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | The paper presents a modified ant colony optimization approach for the network coding resource minimization problem. It is featured with several attractive mechanisms specially devised for solving the network coding resource minimization problem: 1) a multi-dimensional pheromone maintenance mechanism is put forward to address the issue of pheromone overlapping; 2) problem-specific heuristic information is employed to enhance the heuristic search (neighboring area search) capability; 3) a tabu-table based path construction method is devised to facilitate the construction of feasible (link-disjoint) paths from the source to each receiver; 4) a local pheromone updating rule is developed to guide ants to construct appropriate promising paths; 5) a solution reconstruction method is presented, with the aim of avoiding prematurity and improving the global search efficiency of proposed algorithm. Due to the way it works, the ant colony optimization can well exploit the global and local information of routing related problems during the solution construction phase. The simulation results on benchmark instances demonstrate that with the five extended mechanisms integrated, our algorithm outperforms a number of existing algorithms with respect to the best solutions obtained and the computational time. |
| first_indexed | 2025-11-14T19:11:11Z |
| format | Article |
| id | nottingham-31073 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T19:11:11Z |
| publishDate | 2015 |
| publisher | Institute of Electrical and Electronics Engineers |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-310732020-05-04T17:12:53Z https://eprints.nottingham.ac.uk/31073/ A modified ant colony optimization algorithm for network coding resource minimization Wang, Zhaoyuan Xing, Huanlai Li, Tianrui Yang, Yan Qu, Rong Pan, Yi The paper presents a modified ant colony optimization approach for the network coding resource minimization problem. It is featured with several attractive mechanisms specially devised for solving the network coding resource minimization problem: 1) a multi-dimensional pheromone maintenance mechanism is put forward to address the issue of pheromone overlapping; 2) problem-specific heuristic information is employed to enhance the heuristic search (neighboring area search) capability; 3) a tabu-table based path construction method is devised to facilitate the construction of feasible (link-disjoint) paths from the source to each receiver; 4) a local pheromone updating rule is developed to guide ants to construct appropriate promising paths; 5) a solution reconstruction method is presented, with the aim of avoiding prematurity and improving the global search efficiency of proposed algorithm. Due to the way it works, the ant colony optimization can well exploit the global and local information of routing related problems during the solution construction phase. The simulation results on benchmark instances demonstrate that with the five extended mechanisms integrated, our algorithm outperforms a number of existing algorithms with respect to the best solutions obtained and the computational time. Institute of Electrical and Electronics Engineers 2015-07-17 Article PeerReviewed Wang, Zhaoyuan, Xing, Huanlai, Li, Tianrui, Yang, Yan, Qu, Rong and Pan, Yi (2015) A modified ant colony optimization algorithm for network coding resource minimization. IEEE Transactions on Evolutionary Computation . ISSN 1089-778X Ant colony optimization Network coding Combinatorial optimization http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7161342 doi:10.1109/TEVC.2015.2457437 doi:10.1109/TEVC.2015.2457437 |
| spellingShingle | Ant colony optimization Network coding Combinatorial optimization Wang, Zhaoyuan Xing, Huanlai Li, Tianrui Yang, Yan Qu, Rong Pan, Yi A modified ant colony optimization algorithm for network coding resource minimization |
| title | A modified ant colony optimization algorithm for network coding resource minimization |
| title_full | A modified ant colony optimization algorithm for network coding resource minimization |
| title_fullStr | A modified ant colony optimization algorithm for network coding resource minimization |
| title_full_unstemmed | A modified ant colony optimization algorithm for network coding resource minimization |
| title_short | A modified ant colony optimization algorithm for network coding resource minimization |
| title_sort | modified ant colony optimization algorithm for network coding resource minimization |
| topic | Ant colony optimization Network coding Combinatorial optimization |
| url | https://eprints.nottingham.ac.uk/31073/ https://eprints.nottingham.ac.uk/31073/ https://eprints.nottingham.ac.uk/31073/ |