详细信息
Approximation Algorithms for Some Min-Max and Minimum Stacker Crane Cover Problems ( EI收录)
文献类型:期刊文献
英文题名:Approximation Algorithms for Some Min-Max and Minimum Stacker Crane Cover Problems
作者:Sun, Yuhui[1]; Yu, Wei[1]; Liu, Zhaohui[1]
机构:[1] School of Mathematics, East China University of Science and Technology, Shanghai, 200237, China
年份:2021
卷号:13135 LNCS
起止页码:400
外文期刊名:Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
收录:EI(收录号:20215211403362)
基金:Acknowledgement. This research is supported by the National Natural Science Foundation of China under grant numbers 11671135, 11871213 and the Natural Science Foundation of Shanghai under grant number 19ZR1411800.
语种:英文
外文关键词:Cranes - Approximation algorithms - Graph theory
摘要:We study two stacker crane cover problems and their variants. Given a mixed graph G= (V, E, A) with vertex set V, edge set E and arc set A. Each edge or arc is associated with a nonnegative weight. The Min-Max Stacker Crane Cover Problem (SCC) aims to find at most k closed walks covering all the arcs in A such that the maximum weight of the closed walks is minimum. The Minimum Stacker Crane Cover Problem (MSCC) is to cover all the arcs in A by a minimum number of closed walks of length at most λ. The Min-Max Stacker Crane Walk Cover Problem (SCWC)/Minimum Stacker Crane Walk Cover Problem (MSCWC) is a variant of the SCC/MSCC problem with closed walks replaced by (open) walks. For the SCC problem with symmetric arc weights, i.e. for every arc there is a parallel edge of no greater weight, we obtain a 33/5-approximation algorithm. This improves on the previous 37/5-approximation algorithm for a restricted case of the SCC problem with symmetric arc weights. If the arc weights are symmetric, we devise the first constant-factor approximation algorithms for the SCWC problem, the MSCC problem and the MSCWC problem with ratios 5, 5 and 7/2, respectively. Finally, for the (general) MSCWC problem we first propose a 4-approximation algorithm. ? 2021, Springer Nature Switzerland AG.
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