A Modified Ant Colony Optimization Algorithm for Network Coding Resource Minimization

Wang, Zhaoyuan; Xing, Huanlai; Li, Tianrui; Yang, Yan; Qu, Rong; Pan, Yi

Abstract

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.

Citation

Wang, Z., Xing, H., Li, T., Yang, Y., Qu, R., & Pan, Y. (2016). A Modified Ant Colony Optimization Algorithm for Network Coding Resource Minimization. IEEE Transactions on Evolutionary Computation, 20(3), 325-342. https://doi.org/10.1109/TEVC.2015.2457437

• Journal Article Type: Article
• Online Publication Date: Jul 17, 2015
• Publication Date: Jun 1, 2016
• Deposit Date: Dec 14, 2015
• Publicly Available Date: Dec 14, 2015
• Journal: IEEE Transactions on Evolutionary Computation
• Print ISSN: 1089-778X
• Electronic ISSN: 1941-0026
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Volume: 20
• Issue: 3
• Pages: 325-342
• DOI: https://doi.org/10.1109/TEVC.2015.2457437
• Keywords: Ant colony optimization, Network coding,Combinatorial optimization
• Public URL: https://nottingham-repository.worktribe.com/output/756748
• Publisher URL: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7161342
• Additional Information: © 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.