TY - JOUR
T1 - An improved optimization method for materials distribution based on spatiotemporal clustering in automobile assembly lines
AU - Qu, Sheng
AU - Hu, Yaoguang
AU - Zhang, Lixiang
AU - Lu, Shan
N1 - Publisher Copyright:
© 2020 Elsevier B.V.. All rights reserved.
PY - 2020
Y1 - 2020
N2 - The development of smart factories has put forward more flexible logistics needs for automobile assembly system, and efficient scheduling strategies to meet these requirements still demand prompt solution. Thus, this paper focuses on the problem of materials distribution with automated guided vehicles (AGVs) in automobile assembly lines. The mathematical model is established in the light of actual situation with mixed time windows and an improved genetic algorithm (GA) is developed. Considering the demand characteristics both in time and space, material demand points are clustered based on their spatiotemporal distance to generate the initial population. Then, selection, crossover and mutation operators of GA are also ameliorated as necessary to minimize the total travel cost. Finally, practical examples are carried out to demonstrate the effectiveness of this methodology.
AB - The development of smart factories has put forward more flexible logistics needs for automobile assembly system, and efficient scheduling strategies to meet these requirements still demand prompt solution. Thus, this paper focuses on the problem of materials distribution with automated guided vehicles (AGVs) in automobile assembly lines. The mathematical model is established in the light of actual situation with mixed time windows and an improved genetic algorithm (GA) is developed. Considering the demand characteristics both in time and space, material demand points are clustered based on their spatiotemporal distance to generate the initial population. Then, selection, crossover and mutation operators of GA are also ameliorated as necessary to minimize the total travel cost. Finally, practical examples are carried out to demonstrate the effectiveness of this methodology.
KW - Automobile assembly lines
KW - Genetic algorithm
KW - Materials distribution
KW - Mixed time window
KW - Spatiotemporal distance
UR - http://www.scopus.com/inward/record.url?scp=85100836346&partnerID=8YFLogxK
U2 - 10.1016/j.procir.2020.05.232
DO - 10.1016/j.procir.2020.05.232
M3 - Conference article
AN - SCOPUS:85100836346
SN - 2212-8271
VL - 97
SP - 241
EP - 246
JO - Procedia CIRP
JF - Procedia CIRP
T2 - 8th CIRP Conference of Assembly Technology and Systems, CATS 2020
Y2 - 29 September 2020 through 1 October 2020
ER -