Clustering Driven Iterated Hybrid Search for Vertex Bisection Minimization - Université de Picardie Jules Verne
Article Dans Une Revue IEEE Transactions on Computers Année : 2022

Clustering Driven Iterated Hybrid Search for Vertex Bisection Minimization

Yan Jin
Bowen Xiong

Résumé

The Vertex Bisection Minimization Problem (VBMP) is a relevant graph partitioning model with a variety of practical applications. This work introduces a clustering driven iterated hybrid search algorithm (CLUHS), which is the first approach that applies clustering to reinforce iterated local search for solving VBMP. The proposed CLUHS uses hierarchical clustering to build an initial solution, guide local search process and perform search diversification. Experimental studies on 137 benchmark instances show the high competitiveness of the proposed approach compared to the state-of-the-art methods. In particular, CLUHS finds new record-breaking solutions for 18 instances.
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Dates et versions

hal-04012413 , version 1 (02-03-2023)

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Yan Jin, Bowen Xiong, Kun He, Jin-Kao Hao, Chu-Min Li, et al.. Clustering Driven Iterated Hybrid Search for Vertex Bisection Minimization. IEEE Transactions on Computers, 2022, 71 (10), pp.2370-2380. ⟨10.1109/TC.2021.3128504⟩. ⟨hal-04012413⟩
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