A Hybrid Framework Combining Genetic Algorithm with Iterated Local Search for the Dominating Tree Problem
School of Computer Science and Information Technology, Northeast Normal University, Changchun 130117, China
School of Management Science and Information Engineering, Jilin University of Finance and Economics, Changchun 130117, China
Authors to whom correspondence should be addressed.
Received: 29 March 2019 / Revised: 11 April 2019 / Accepted: 11 April 2019 / Published: 19 April 2019
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Given an undirected, connected and edge-weighted graph, the dominating tree problem consists of finding a tree with minimum total edge weight such that for each vertex is either in the tree or adjacent to a vertex in the tree. In this paper, we propose a hybrid framework combining genetic algorithm with iterated local search (GAITLS) for solving the dominating tree problem. The main components of our framework are as follows: (1) the score functions
applied in the initialization and local search phase; (2) the initialization procedure with restricted candidate list (RCL) by controlling the parameter to balance the greediness and randomness; (3) the iterated local search with three phases, which is used to intensify the individuals; (4) the mutation with high diversity proposed to perturb the population. The experimental results on the classical instances show that our method performs much better than the-state-of-art algorithms.
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MDPI and ACS Style
Hu, S.; Liu, H.; Wu, X.; Li, R.; Zhou, J.; Wang, J. A Hybrid Framework Combining Genetic Algorithm with Iterated Local Search for the Dominating Tree Problem. Mathematics 2019, 7, 359.
Hu S, Liu H, Wu X, Li R, Zhou J, Wang J. A Hybrid Framework Combining Genetic Algorithm with Iterated Local Search for the Dominating Tree Problem. Mathematics. 2019; 7(4):359.
Hu, Shuli; Liu, Huan; Wu, Xiaoli; Li, Ruizhi; Zhou, Junping; Wang, Jianan. 2019. "A Hybrid Framework Combining Genetic Algorithm with Iterated Local Search for the Dominating Tree Problem." Mathematics 7, no. 4: 359.
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