DocumentCode :
2799586
Title :
Research on the order picking optimization problem of the automated warehouse
Author :
Shuhua, Ma ; Yanzhu, Hao
Author_Institution :
Northeastern Univ. at Qinhuangdao, Qinhuangdao, China
fYear :
2009
fDate :
17-19 June 2009
Firstpage :
990
Lastpage :
993
Abstract :
The increased use of automated storage and retrieval systems (AS/RS) is creating the need for computerized control algorithms to support the scheduling and picking decisions. This research addresses an order picking problem in a multi-aisle automated warehouse, in which a stack crane performs storage and retrieval operations, and each item can be found in several storage locations. Our objective is to propose algorithms that minimize the total time traveled by the stack crane to complete the retrieval process of orders. The traveling salesman problem (TSP) can calculate the shortest distance between cities, order picking problem of the automated warehouse and the TSP are similar. In this paper, we use recursive algorithm to solve order picking problem. The experiment proved that the order picking optimization of the stacker systems will be of great significance for the RS to improve its efficiency. Finally, the recursive algorithm has been applied to practice.
Keywords :
computerised control; cranes; order picking; scheduling; storage automation; travelling salesman problems; automated storage and retrieval system; computerized control algorithm; multiaisle automated warehouse; order picking optimization; picking decision; recursive algorithm; scheduling; stack crane; storage location; traveling salesman problem; Automatic control; Cities and towns; Control systems; Cranes; Job shop scheduling; Optimized production technology; Processor scheduling; Scheduling algorithm; Storage automation; Traveling salesman problems; AS/ RS; Picking Optimization; Recursive Algorithm; Stack Crane; TSP;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control and Decision Conference, 2009. CCDC '09. Chinese
Conference_Location :
Guilin
Print_ISBN :
978-1-4244-2722-2
Electronic_ISBN :
978-1-4244-2723-9
Type :
conf
DOI :
10.1109/CCDC.2009.5192816
Filename :
5192816
Link To Document :
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