TY - JOUR
T1 - New solution algorithms for asymmetric traffic assignment model
AU - Chen, Huey Kuo
AU - Wang, Chung Yung
AU - Boyce, David E.
N1 - Funding Information:
We thank the National Science Council, R.O.C. (grant NSC82-0410-E008-053) for support.
PY - 1995/4
Y1 - 1995/4
N2 - The asymmetric traffic assignment model can improve the traditional traffic assignment model by adopting detailed network representation and more realistic asymmetric cost functions. The diagonalization, streamlined diagonalization, and projection methods are three widely mentioned solution algorithms for solving asymmetric traffic assignment models. The diagonalization and streamlined diagonalization methods have the advantage of requiring less computer memory but typically require greater computational time. The projection method has the advantage of convening more rapidly but requires a large computer memory. In order to balance computer memory and computational time, we propose two new algorithms; i.e., hybrid and streamlined hybrid methods. According to our case study, the proposed algorithms show their superiority over the diagonalization and streamlined diagonalization methods in terms of computational time, and over the projection method in terms of computer memory Both new algorithms can handle small or medium networks sized asymmetric traffic assignment problems on personal computers.
AB - The asymmetric traffic assignment model can improve the traditional traffic assignment model by adopting detailed network representation and more realistic asymmetric cost functions. The diagonalization, streamlined diagonalization, and projection methods are three widely mentioned solution algorithms for solving asymmetric traffic assignment models. The diagonalization and streamlined diagonalization methods have the advantage of requiring less computer memory but typically require greater computational time. The projection method has the advantage of convening more rapidly but requires a large computer memory. In order to balance computer memory and computational time, we propose two new algorithms; i.e., hybrid and streamlined hybrid methods. According to our case study, the proposed algorithms show their superiority over the diagonalization and streamlined diagonalization methods in terms of computational time, and over the projection method in terms of computer memory Both new algorithms can handle small or medium networks sized asymmetric traffic assignment problems on personal computers.
KW - Asymmetric traffic assignment
KW - Contraction operator
KW - Diagonalization
KW - Hybrid
KW - Multicommodity flow problem
KW - Projection
UR - http://www.scopus.com/inward/record.url?scp=84948030031&partnerID=8YFLogxK
U2 - 10.1080/02533839.1995.9677704
DO - 10.1080/02533839.1995.9677704
M3 - 期刊論文
AN - SCOPUS:84948030031
SN - 0253-3839
VL - 18
SP - 411
EP - 426
JO - Journal of the Chinese Institute of Engineers, Transactions of the Chinese Institute of Engineers,Series A/Chung-kuo Kung Ch'eng Hsuch K'an
JF - Journal of the Chinese Institute of Engineers, Transactions of the Chinese Institute of Engineers,Series A/Chung-kuo Kung Ch'eng Hsuch K'an
IS - 3
ER -