DocumentCode
2688650
Title
Model and algorithm for inventory-transportation integrated optimization problem—in view of many-one distribution network
Author
Liu, Lihui ; Ye, Chunming
Author_Institution
Bus. Sch., Univ. of Shanghai for Sci. & Technol., Shanghai, China
fYear
2009
fDate
8-10 June 2009
Firstpage
498
Lastpage
503
Abstract
VMI (vendor managed inventory) policy coordinates effectively the antinomy between the inventory and the transportation within logistics distribution system. Under VMI mode, integrating inventory and transportation of the supplier and the demander as a whole is vital to achieve the optimization of total distribution cost. In view of typical many-one distribution network in the modern distribution logistics system, the mathematic model on the inventory-transportation integrated optimization problem with stochastic demand and many products is established by using a bi-level programming method; and an improved heuristic algorithm is designed to solve the problem; at last, by some mathematic examples, the validity of the models and the algorithm is proved. And then, the mathematic description and the heuristic algorithm to the massive practice of the modern distribution logistics system are realized.
Keywords
inventory management; logistics; optimisation; transportation; bi-level programming method; heuristic algorithm; inventory-transportation integrated optimization problem; logistics distribution system; stochastic demand; vendor managed inventory policy; Cost function; Design optimization; Heuristic algorithms; Inventory management; Logistics; Mathematical model; Mathematical programming; Mathematics; Stochastic systems; Transportation; bi-level programming method; improved heuristic algorithm; inventory and transportation; many-one distribution system; system optimization;
fLanguage
English
Publisher
ieee
Conference_Titel
Service Systems and Service Management, 2009. ICSSSM '09. 6th International Conference on
Conference_Location
Xiamen
Print_ISBN
978-1-4244-3661-3
Electronic_ISBN
978-1-4244-3662-0
Type
conf
DOI
10.1109/ICSSSM.2009.5174935
Filename
5174935
Link To Document