Abstract
Long queues of arrival trucks are a common problem in seaports, and thus, carbon emissions generated from trucks in the queue cause environmental pollution. In order to relieve gate congestion and reduce carbon emissions, this paper proposes a lane allocation framework combining the truck appointment system (TAS) for four types of trucks. Based on the distribution of arrival times obtained from the TAS, lane allocation decisions in each appointment period are determined in order to minimize the total cost, including the operation cost and carbon emissions cost. The resultant optimization model is a non-linear fractional integer program. This model was firstly transformed to an equivalent integer program with bilinear constraints. Then, an improved branch-and-bound algorithm was designed, which includes further transforming the program into a linear program using the McCormick approximation method and iteratively generating a tighter outer approximation along the branch-and-bound procedure. Numerical studies confirmed the validity of the proposed model and algorithm, while demonstrating that the lane allocation decisions could significantly reduce carbon emissions and operation costs.
Highlights
Accepted: 16 March 2021With the development of economic globalization and the fast growth of international trade, maritime transportation plays an increasingly important role in the international supply chain [1,2]
This paper focuses on lane allocation problem with the consideration of carbon emissions
This paper considered green lane allocation with the consideration of carbon emissions generated by trucks in the gate
Summary
With the development of economic globalization and the fast growth of international trade, maritime transportation plays an increasingly important role in the international supply chain [1,2]. How to shorten the queue time and guide trucks to move faster in order to relieve congestion in the gate has become a necessary breakthrough to achieve the green management of seaports. With the distribution of arrival time and the service rate of lanes, the opening planning of lanes for different types of trucks in each appointment period is made, in order to minimize the total cost including the carbon emissions cost and operation cost. A numerical study shows the effectiveness of the proposed model and algorithm, and demonstrates that the resulting lane allocation policy could relieve congestion and reduce carbon emissions.
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