DocumentCode
2527754
Title
An EOQ Model for Multi-Item and Multi-Storehouse Based on New Hybrid Genetic Algorithm
Author
Zhao, Peixin ; Wang, Hong
Author_Institution
Sch. of Manage., Shandong Univ., Jinan
Volume
3
fYear
2006
fDate
Aug. 30 2006-Sept. 1 2006
Firstpage
657
Lastpage
660
Abstract
A new economic order quantity model is developed for multi-item and multi-storehouse with limited funds, limited storage capacity and stochastic demand. The model is proved to be a nonlinear convex programming. For finding the optimal replenishment schedule, we design a new hybrid genetic algorithm that combines self-adapting crossover and stochastic mutation operators. Comparing with the basic genetic algorithm, this improved algorithm adequately utilizes the adaptability information of current individuals, it has better convergence efficiency and higher solution precision. A numerical example is presented to illustrate the validity and efficiency of the new hybrid genetic algorithm
Keywords
convex programming; genetic algorithms; industrial economics; inventory management; stochastic processes; economic order quantity model; genetic algorithm; multiitem multistorehouse model; nonlinear convex programming; optimal replenishment schedule; self-adapting crossover; stochastic demand; stochastic mutation operator; Capacity planning; Costs; Educational institutions; Finance; Financial management; Genetic algorithms; Genetic mutations; Industrial economics; Mathematical model; Stochastic processes;
fLanguage
English
Publisher
ieee
Conference_Titel
Innovative Computing, Information and Control, 2006. ICICIC '06. First International Conference on
Conference_Location
Beijing
Print_ISBN
0-7695-2616-0
Type
conf
DOI
10.1109/ICICIC.2006.413
Filename
1692262
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