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A novel pheromone-based evolutionary algorithm for solving degree-constrained minimum spanning tree problem

Authors
Huang, Xiao-MaGong, Yue-JiaoZhang, Jun
Issue Date
Jul-2013
Publisher
ACM
Keywords
Degree-constrained minimum spanning tree; Evolutionary algorithms; Network design; Pheromone; Tree modification
Citation
GECCO '13 Companion: Proceedings of the 15th annual conference companion on Genetic and evolutionary computation, pp 121 - 122
Pages
2
Indexed
SCOPUS
Journal Title
GECCO '13 Companion: Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
Start Page
121
End Page
122
URI
https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/117931
DOI
10.1145/2464576.2464636
Abstract
The degree-constrained minimum spanning tree problem (dc- MSTP) is crucial in the design of networks and it is proved to be NP-hard. The recently developed evolutionary algorithm utilizing node-depth-degree representation (EANDD) has successfully enabled the dc-MSTP solvable by generating new spanning trees in average time complexity O(√ n) , which is the fastest in the literature. However, as the generic operation of EANDD is to change two edges that are randomly selected from the entire tree, the efficiency of EANDD still has potential to be further improved. In this paper, we propose a novel pheromone-based tree modification method (PTMM) to improve the efficiency of EANDD. For each edge, a pheromone value is defined based on the historical contribution of the edge to the fitness of the spanning tree. Then, PTMM considers the pheromone value on each edge as a desirability measure for selecting the edge to construct the spanning tree. In this way, the more promising edge is more likely to be selected and therefore the efficiency of the tree modification operation in EANDD can be improved. The effectiveness and effieciency of PTMM is demonstrated on a set of benchmark instances in comparison with the original EANDD.
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ERICA 공학대학 (SCHOOL OF ELECTRICAL ENGINEERING)
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