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An optimal service model for rail freight transportation: Pricing, planning, and emission reducing

Zhang, Xiaoqiang, Li, Lin, Zhang, Jin
Journal of cleaner production 2019 v.218 pp. 565-574
algorithms, carbon, case studies, consumers (people), freight, greenhouse gas emissions, models, planning, prices, profit maximization
The price and service time are two critical aspects that affect the benefits for customers and rail operators. In the rail freight transportation system, the profit maximization object is explored deeply, which is widely adopted by rail operators. This paper bridges the gap between the maximization profit of rail operators and the minimization of customers’ waiting queue (backlog). We propose a new optimization model which encompasses pricing, operation planning, carbon emissions and service queuing for an infinite-horizon decision process. The infinite-horizon decision problem is NP-hard. More precisely, a backlog control and pricing optimization algorithm is proposed to solve the NP-hard problem. In particular, it is theoretically proved that the result of the proposed algorithm is equal to the optimal solution. The explicit trade-off between the optimization objective and queue backlog is also proven. Finally, a case study was carried out to testify the efficiency of the proposed model. The result shows that the proposed methodology not only improve the rail freight service quality but also reduce the greenhouse gas emission at the freight transportation sector.