Abstract
In this paper, we present a comprehensive investment planning model and its solution approach. The model takes a bilevel programming form and allows a variety of effects of the investments incorporated. The model is characterized by its ability to address the total social costs occurring in transportation networks and to estimate the equilibrium link volumes in multimodal networks. Two solution algorithms were proposed. Both algorithms handle the discrete optimization problem by exploiting the strings of binary digits of integer variables. In an illustrative example, we performed network design analyses for three scenarios in which 25, 50, and 75% of the total required capital is available. By applying the two solution algorithms to the example problem, the optimal network alternative for each scenario was found. If a cost/benefit analysis is coupled with the proposed model, the optimal investments and the optimal network configuration will be determined simultaneously.
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Notes
Korea Ministry of Construction and Transportation (1999) has suggested 3,045 Korean Won/pax-hr, for the public road travelers and 2,088 Korean Won/pax-hr for rail travelers.
Korea Research Institute for Human Settlements (1999) has suggested 97.054, 1,094.081, and −8.24×10−4 as the values of h 0, h 1, h 2, respectively.
Sur (1994) has suggested 24.4 Korean Won/pax-km.
a h , a r are estimated as 29.73 Korean Won/pax-km, 1.70 Korean Won/pax-km from the Annual Report of Transportation Statistics of Korea Ministry of Construction and Transportation (1999).
Dong-bu Engineering Co. (1997) estimated the costs of emission cleaning processes and suggested 12.58 Korean Won/pax-km, 5.08 Korean Won/pax-km for e h , e r .
Korea Development Institute (2000) suggested 1,170,000 Korean Won/day-km for four lane highways.
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Appendix
Appendix
1.1 Data File for the example
a. Existing Network Data
# of nodes | 9 | ||||||||
Highway Data | # of links | 12 | |||||||
from | To | distance | FF speed | capacity | |||||
1 | 2 | 70 | 100 | 4000 | |||||
1 | 4 | 50 | 100 | 2000 | |||||
2 | 3 | 70 | 100 | 2000 | |||||
2 | 5 | 50 | 100 | 4000 | |||||
3 | 6 | 50 | 100 | 2000 | |||||
4 | 5 | 80 | 100 | 2000 | |||||
4 | 7 | 100 | 100 | 2000 | |||||
5 | 6 | 80 | 100 | 2000 | |||||
5 | 8 | 50 | 100 | 4000 | |||||
6 | 9 | 100 | 100 | 2000 | |||||
7 | 8 | 70 | 100 | 2000 | |||||
8 | 9 | 70 | 100 | 4000 | |||||
Rail Data | # of links | 4 | |||||||
from | To | distance | FF speed | capacity | |||||
1 | 2 | 70 | 80 | 999999 | |||||
2 | 5 | 50 | 80 | 999999 | |||||
5 | 8 | 50 | 80 | 999999 | |||||
8 | 9 | 70 | 80 | 999999 |
b. OD Demand Data
O/D Data | # of O/D | 12 | |||
from | To | Demand | |||
1 | 3 | 3000 | |||
1 | 7 | 3000 | |||
1 | 9 | 4000 | |||
3 | 1 | 3000 | |||
3 | 7 | 2500 | |||
3 | 9 | 2500 | |||
7 | 1 | 3000 | |||
7 | 3 | 2500 | |||
7 | 9 | 3000 | |||
9 | 1 | 4000 | |||
9 | 3 | 2500 | |||
9 | 7 | 3000 |
c. Candidate Link Data
Candidate | Data | 9 | Total Invest | 1060 | |||||||
Highway | # of links | 4 | |||||||||
from | To | distance | FF speed | capacity | investments | ||||||
1 | 5 | 100 | 100 | 2000 | 100 | ||||||
5 | 9 | 150 | 100 | 2000 | 150 | ||||||
3 | 5 | 100 | 100 | 2000 | 100 | ||||||
5 | 7 | 150 | 100 | 2000 | 150 | ||||||
Rail | # of links | 4 | |||||||||
1 | 5 | 100 | 80 | 999999 | 110 | ||||||
5 | 9 | 150 | 80 | 999999 | 170 | ||||||
3 | 5 | 100 | 80 | 999999 | 110 | ||||||
5 | 7 | 150 | 80 | 999999 | 170 |
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Kim, B.J., Kim, W. An equilibrium network design model with a social cost function for multimodal networks. Ann Reg Sci 40, 473–491 (2006). https://doi.org/10.1007/s00168-005-0053-3
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DOI: https://doi.org/10.1007/s00168-005-0053-3