A model of investment planning for transportation networks is formulated. The model seeks to maximize expected system capacity subject to uncertainty that will occur in the future demand pattern and with a limited budget for investment. Simulated annealing is used to solve the investment planning problem. A case study of a simplified version of the western U.S. double-stack container network is included to illustrate the application of the model.
Get full access to this article
View all access options for this article.
References
1.
MagnantiT. L., and WongR. T.Network Design and Transportation Planning: Models and Algorithms. Transportation Science, Vol. 18, No. 1, 1984, pp. 1–55.
2.
YangH., and BellM. G. H.Models and Algorithms for Road Network Design: A Review and Some New Developments. Transport Reviews, Vol. 18, No. 3, 1998, pp. 257–278.
3.
ChenA., and YangC.Stochastic Transportation Network Design Problem with Spatial Equity Constraint. In Transportation Research Record: Journal of the Transportation Research Board, No. 1882, Transportation Research Board of the National Academies, Washington, D.C., 2004, pp. 97–104.
4.
MorlokE. K., and RiddleS. P.Estimating the Capacity of Freight Transportation Systems: A Model and Its Application in Transport Planning and Logistics. In Transportation Research Record: Journal of the Transportation Research Board, No. 1653, TRB, National Research Council, Washington, D.C., 1999, pp. 1–8.
5.
MorlokE. K., and ChangD. J.Measuring Capacity Flexibility of a Transportation System. Transportation Research, Vol. 38A, No. 4, 2004, pp. 405–420.
6.
SunY., TurnquistM. A., and NozickL. K.Estimating Freight Transportation System Capacity, Flexibility, and Degraded-Condition Performance. In Transportation Research Record: Journal of the Transportation Research Board, No. 1966, Transportation Research Board of the National Academies, Washington, D.C., 2006, pp. 80–87.
7.
Traffic Assignment Manual.Bureau of Public Roads, Urban Planning Division, U.S. Department of Commerce, 1964.
8.
AkcelikR.Travel Time Functions for Transport Planning Purposes: Davidson's Function, Its Time-Dependent Form and an Alternative Travel Time Function. Australian Road Research, Vol. 21, No. 3, 1991, pp. 49–59.
9.
DavidsonK. B.A Flow Travel Time Relationship for Use in Transportation Planning. Proceedings of the Australian Transportation Research Board, Vol. 3, No. 1, 1966, pp. 183–194.
10.
MaherM. J.SAM—A Stochastic Assignment Model. In Mathematics in Transport Planning and Control, Oxford University Press, United Kingdom, 1992, pp. 121–133.
11.
MaherM. J., and HughesP. C.A Probit-Based Stochastic User Equilibrium Assignment Model. Transportation Research, Vol. 31B, No. 4, 1997, pp. 341–345.
12.
LoH. K., and TungY. K.Network with Degradable Links: Capacity Analysis and Design. Transportation Research, Vol. 37B, No. 4, 2003, pp. 345–363.
13.
FrieszT. L., ChoH-J., MehtaN. J., TobinR. L., and AnandalingamG.A Simulated Annealing Approach to the Network Design Problem with Variational Inequality Constraints. Transportation Science, Vol. 26, No. 1, 1992, pp. 18–26.
14.
DavisG. A.Exact Local Solution of the Continuous Network Design Problem via Stochastic User Equilibrium Assignment. Transportation Research, Vol. 28B, No. 1, 1994, pp. 61–75.
15.
WeiC-H., and SchonfeldP.Multiperiod Network Improvement Model. In Transportation Research Record 1443, TRB, National Research Council, Washington, D.C., 1994, pp. 110–118.
16.
BabayanA., KapelanZ., SavicD. A., and WaltersG. A.Least-Cost Design of Water Distribution Networks Under Demand Uncertainty. Journal of Water Resources Planning and Management, Vol. 131, No. 5, 2005, pp. 375–382.
17.
MetropolisN., RosenbluthA. W., RosenbluthM. N., TellerA. H., and TellerE.Equations of State Calculations by Fast Computing Machines. Journal of Chemical Physics, Vol. 21, 1953, pp. 1087–1091.
18.
KirkpatrickS., GelattC. D., and VecchiM. P.Optimization by Simulated Annealing. Science, Vol. 220, No. 4598, 1983, pp. 671–680.
19.
CernyV.Thermodynamical Approach to the Traveling Salesman Problem: An Efficient Simulation Algorithm. Journal of Optimization Theory and Applications, Vol. 45, No. 1, 1985, pp. 41–51.
20.
SmithD. S.Double Stack Container Systems: Implications for U.S. Railroads and Ports. Report FRA-RRP-90-2. FRA and MARAD, U.S. Department of Transportation, 1990.
21.
2003 Carload Waybill Sample. CD-ROM. Surface Transportation Board, U.S. Department of Transportation, Washington, D.C., 2003.
22.
RockafellarR. T., and WetsR. J.-B.Scenarios and Policy Aggregation in Optimization Under Uncertainty. Mathematics of Operations Research, Vol. 16, No. 1, 1991, pp. 119–147.
23.
LokketangenA., and WoodruffD. L.Progressive Hedging and Tabu Search Applied to Mixed Integer (0, 1) Multistage Stochastic Programming. Journal of Heuristics, Vol. 2, No. 2, 1996, pp. 111–128.
24.
WoodruffD. L., and VossS.Planning for a Big Bang in a Supply Chain: Fast Hedging for Production Indicators. Proc., 39th Hawaii International Conference on System Sciences, IEEE Computer Society, Jan. 2006.
