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• W2934689541 abstract "A number of important applications related to complex network analysis require finding small vertex covers in massive graphs. This paper proposes an effective stochastic local search algorithm called DTS_MVC to fulfill this task. Relying on a fast vertex-based search strategy, DTS_MVC effectively explores the search space by alternating between a thresholding search phase during which the algorithm accepts both improving and non-improving solutions that satisfy a dynamically changing quality threshold, and a conditional improving phase where only improving solutions are accepted. A novel non-parametric operation-prohibiting mechanism is introduced to avoid search cycling. Computational experiments on 86 massive real-world benchmark graphs indicate that DTS_MVC performs remarkably well by discovering 7 improved best known results (new upper bounds). Additional experiments are conducted to shed light on the key ingredients of DTS_MVC." @default.
• W2934689541 created "2019-04-11" @default.
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• W2934689541 date "2019-06-01" @default.
• W2934689541 modified "2023-10-10" @default.
• W2934689541 title "Dynamic thresholding search for minimum vertex cover in massive sparse graphs" @default.
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• W2934689541 doi "https://doi.org/10.1016/j.engappai.2019.03.015" @default.
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