Abstract
In this study, the author focuses on modeling and optimizing a freight routing problem in a road-rail intermodal transportation network that combines the hub-and-spoke and point-to-point structures. The operations of road transportation are time flexible, while rail transportation has fixed departure times. The reliability of the routing is improved by modeling the uncertainty of the road-rail intermodal transportation network. Parameters that are influenced by the real-time status of the network, including capacities, travel times, loading and unloading times, and container trains’ fixed departure times, are considered uncertain in the routing decision-making. Based on fuzzy set theory, triangular fuzzy numbers are employed to formulate the uncertain parameters as well as resulting uncertain variables. Green routing is also discussed by treating the minimization of carbon dioxide emissions as an objective. First of all, a multiobjective fuzzy mixed integer nonlinear programming model is established for the specific reliable and green routing problem. Then, defuzzification, linearization, and weighted sum method are implemented to present a crisp linear model whose global optimum solutions can be effectively obtained by the exact solution algorithm run by mathematical programming software. Finally, a numerical case is given to demonstrate how the proposed methods work. In the case, sensitivity analysis is adopted to reveal the effects of uncertainty on the routing optimization. Fuzzy simulation is then performed to help decision makers to select the best crisp route plan by determining the best confidence level shown in the fuzzy chance constraints.
Highlights
Rail transportation has been acknowledged to be a costeffective means of long-distribution transportation
Sun et al [11] discuss a green intermodal routing problem with capacity uncertainty and road traffic congestion. e empirical case study presented in this study indicates that the green routing optimization is not sensitive to the unit emission tax, and the routes are not changed unless the unit emission tax reach a substantial value that is infeasible in practice
In the existing literature that focuses on the freight routing problem in the deterministic road-rail intermodal transportation network, parameters including capacities, fixed departure times, travel times, and loading/unloading times, are estimated in a deterministic way by using their most likely values. eir omtn2oidteolintagkceatnhebepleaacseilyofreraijlniz, efdni,byttiujns,inagndr2ijont,ni fin2ni, tt2ijn, and the fuzzy programming model established in this study, respectively
Summary
Rail transportation has been acknowledged to be a costeffective means of long-distribution transportation. (1) A road-rail intermodal routing problem is extended by enhancing its environmental sustainability with carbon dioxide emission optimization and improving transportation reliability with multiple sources of uncertainty. (3) Fuzzy goal programming approach is used to formulate the green and reliable freight routing problem in the road-rail intermodal transportation network with hub-and-spoke and point-to-point structures. (4) e proposed methods are demonstrated in a numerical case, in which sensitivity analysis and fuzzy simulation are utilized to analyze the effects of transportation network uncertainty on the routing optimization quantitatively, and determine the optimum confidence level in the fuzzy chance constraints. Is study uses sensitivity analysis and fuzzy simulation to quantify the effects of transportation network uncertainty on the routing optimization .
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