DocumentCode
2066836
Title
Novel model and algorithm of stochastic joint inventory control for virtual logistics
Author
Jiang Da-li ; Xin-guang, Zhao
Author_Institution
Inst. of Modern Logistics, Logistical Eng. Univ., Chongqing, China
fYear
2011
fDate
16-18 Dec. 2011
Firstpage
166
Lastpage
169
Abstract
This exhaustive research was made on the joint inventory control problem of stochastic demand in virtual logistics. The demand for each warehouse follows Poisson distribution. An optimal joint inventory control model is proposed to minimize the whole inventory control cost comprising ordering cost, storage cost and shortage cost. The (T, S, s) model is constructed by using and adjusting the (T, S) model which is used successfully in the joint inventory control problem of single warehouse with multiple kinds of goods. Due to the NP-hard property of (T, S, s) model, this paper designs and programs a genetic algorithm with GA tool box of Matlab. Results of experiment shows the joint inventory strategy deduced by our (T, S, s) model and genetic algorithm can reduce the total storage cost of virtual logistics enterprise greatly, and it exceeds the (T, S) strategy.
Keywords
Poisson distribution; cost optimal control; genetic algorithms; logistics; stochastic processes; stock control; virtual enterprises; (T,S,s) model; GA tool box; Matlab; NP-hard property; Poisson distribution; genetic algorithm; inventory control cost minimization; optimal joint inventory control model; ordering cost; shortage cost; stochastic demand; stochastic joint inventory control algorithm; stochastic joint inventory control model; storage cost; virtual logistics enterprise; Genetic algorithms; Inventory control; Joints; Logistics; Mathematical model; Silicon; Stochastic processes; joint inventory control; stochastic demand; virtual logistics;
fLanguage
English
Publisher
ieee
Conference_Titel
Transportation, Mechanical, and Electrical Engineering (TMEE), 2011 International Conference on
Conference_Location
Changchun
Print_ISBN
978-1-4577-1700-0
Type
conf
DOI
10.1109/TMEE.2011.6199171
Filename
6199171
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