A Modified Genetic Algorithm to Optimize A Multi-item Inventory System with Random Demands and Stochastic Lead Time

Author

Lu, Hou-qing ; Wu, Zhi-min ; Yu, Qin ; Han, Rui-xin ; Wu, Feng-li

Author_Institution

Eng. Inst. of Eng. Corps, PLA Univ. Sci. & Tech., Nanjing

Volume

1

fYear

0

fDate

0-0 0

Firstpage

3366

Lastpage

3370

Abstract

Multi-item inventory systems with stochastic demands and lead time are studied to reduce operation costs and use resources effectively. In order to reach minimal costs in the long run, a (s ,S) model based on stochastic demands and lead time is advanced, A modified genetic algorithm based on minimal gene segment coding, two generations competition and adaptive selection was developed to solve the problem, a M-C statistical testing method was presented to compute adaptive values, which significantly improve warehouse and capital management. The result of the modified genetic algorithm shows that over 7% operation costs is saved compared with the result of random generated

Keywords

cost reduction; genetic algorithms; lead time reduction; random processes; statistical testing; stochastic processes; stock control; genetic algorithm; minimal gene segment coding; multiitem inventory system; random demands; statistical testing method; stochastic lead time; Costs; Educational institutions; Genetic algorithms; Intelligent control; Lead time reduction; Meteorology; Programmable logic arrays; Statistical analysis; Stochastic processes; Stochastic systems; Genetic Algorithm; Inventory; Multi-item; Stochastic demand; Stochastic lead time;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on

Conference_Location

Dalian

Print_ISBN

1-4244-0332-4

Type

conf

DOI

10.1109/WCICA.2006.1712992

Filename

1712992