详细信息

Scheduling Reclaimer Operations in the Stockyard to Minimize Makespan    

文献类型:期刊文献

中文题名:Scheduling Reclaimer Operations in the Stockyard to Minimize Makespan

英文题名:Scheduling Reclaimer Operations in the Stockyard to Minimize Makespan

作者:Chao WANG[1];Xi-wen LU[1];René SITTERS[2]

机构:[1]East China University of Science and Technology, 200237, Shanghai, China;[2]VU University Amsterdam, De Boelelaan 1105, 1081 HV Amsterdam, The Netherlands

年份:2018

卷号:34

期号:3

起止页码:597

中文期刊名:Acta Mathematicae Applicatae Sinica

外文期刊名:应用数学学报(英文版)

收录:CSTPCD;;Scopus;CSCD:【CSCD2017_2018】;

基金:Supported by the National Natural Science Foundation of China(No.11371137 and No.71431004)

语种:英文

中文关键词:scheduling approximation;algorithm performance ratio;numerical simulation

外文关键词:scheduling approximation;algorithm performance ratio;numerical simulation

摘要:This paper considers a reclaimer scheduling problem in which one has to collect bulk material from stockpiles in the quay in such a way that the time used is minimized. When reclaimers are allowed to work on the same stockpile simultaneously, a fully polynomial time approximation scheme(FPTAS) is designed. Further,we present a 2-approximation algorithm in the case that any stockpile can be handled by only one reclaimer at a time. When the number of reclaimers is two, we give a 3/2-approximation algorithm. Numerical experiments show that the algorithms perform much better than our worst case analysis guarantees.
This paper considers a reclaimer scheduling problem in which one has to collect bulk material from stockpiles in the quay in such a way that the time used is minimized. When reclaimers are allowed to work on the same stockpile simultaneously, a fully polynomial time approximation scheme(FPTAS) is designed. Further,we present a 2-approximation algorithm in the case that any stockpile can be handled by only one reclaimer at a time. When the number of reclaimers is two, we give a 3/2-approximation algorithm. Numerical experiments show that the algorithms perform much better than our worst case analysis guarantees.

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