Combining max-min ant system with effective local search for solving the maximum set k-covering problem

2021 ◽  
pp. 108000
Author(s):  
Yupeng Zhou ◽  
Xiaofan Liu ◽  
Shuli Hu ◽  
Yiyuan Wang ◽  
Minghao Yin
Author(s):  
Fabrício Olivetti de França ◽  
Fernando J. Von Zuben ◽  
Leandro Nunes de Castro

2020 ◽  
Vol 34 (02) ◽  
pp. 1569-1576 ◽  
Author(s):  
Zhendong Lei ◽  
Shaowei Cai

The Set Covering Problem (SCP) and Dominating Set Problem (DSP) are NP-hard and have many real world applications. SCP and DSP can be encoded into Maximum Satisfiability (MaxSAT) naturally and the resulting instances share a special structure. In this paper, we develop an efficient local search solver for MaxSAT instances of this kind. Our algorithm contains three phrase: construction, local search and recovery. In construction phrase, we simplify the instance by three reduction rules and construct an initial solution by a greedy heuristic. The initial solution is improved during the local search phrase, which exploits the feature of such instances in the scoring function and the variable selection heuristic. Finally, the corresponding solution of original instance is recovered in the recovery phrase. Experiment results on a broad range of large scale instances of SCP and DSP show that our algorithm significantly outperforms state of the art solvers for SCP, DSP and MaxSAT.


2016 ◽  
Vol 23 (1) ◽  
pp. 127-134 ◽  
Author(s):  
Rafid Sagban ◽  
Ku Ruhana Ku-Mahamud ◽  
Muhamad Shahbani Abu Bakar
Keyword(s):  

2016 ◽  
Vol 29 (10) ◽  
pp. 755-765 ◽  
Author(s):  
Yiyuan Wang ◽  
Dantong Ouyang ◽  
Minghao Yin ◽  
Liming Zhang ◽  
Yonggang Zhang

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