Abstract:Fuel consumption and CO 2 emission are among the main criteria to assess the environmental and economical impact of vessels on inland waterways. Both criteria, however, are directly affected by the vessels' sailing speed. In this paper, we present a mathematical programming formulation of the speed optimization problem, which aims at minimizing the aggregated fuel consumption on an inland waterway network. The network can consist of multiple river segments, connected by a set of locks, without restrictions on … Show more
“…They developed a ship-lockage assignment model based on time discretization and analyzed the impact of optimizing ship speeds on the total ship staying time and carbon emissions. Golak et al [28] focused on ships passing through a serial-lock system, assuming the uninterrupted continuous operation of the locks. They constructed an MILP to optimize the total ship staying time and carbon emissions.…”
Inland navigation serves as a vital component of transportation, boasting benefits such as ample capacity and minimal energy consumption. However, it also poses challenges related to achieving navigation efficiency and environmental friendliness. Locks, which are essential for inland waterways, often cause ship passage bottlenecks. This paper focuses on a green lock scheduling problem (GLSP), aiming to minimize fuel emissions and maximize navigation efficiency. Considering the realistic constraints, a mixed-integer linear programming model and a large neighborhood search solution algorithm are proposed. From a job shop scheduling perspective, the problem is decomposed into three main components: ship-lockage assignment, ship placement subproblem, and lockage scheduling subproblem coupled with ship speed optimization. A large neighborhood search algorithm based on a decomposition framework (LNSDF) is proposed to tackle the GLSP. In this, the complex lockage scheduling problem is addressed efficiently by mapping it to a network planning problem and applying the critical path method. Numerical experiments substantiate the effectiveness of our proposed model and a heuristic approach was used in solving the GLSPs. In the sensitivity analysis, under three different objective weight assignments, the resulting solutions achieved average effective ship fuel savings of 4.51%, 8.86%, and 2.46%, respectively. This indicates that our green lock scheduling problem considering ship speed optimization can enhance ship passage efficiency while reducing carbon emissions.
“…They developed a ship-lockage assignment model based on time discretization and analyzed the impact of optimizing ship speeds on the total ship staying time and carbon emissions. Golak et al [28] focused on ships passing through a serial-lock system, assuming the uninterrupted continuous operation of the locks. They constructed an MILP to optimize the total ship staying time and carbon emissions.…”
Inland navigation serves as a vital component of transportation, boasting benefits such as ample capacity and minimal energy consumption. However, it also poses challenges related to achieving navigation efficiency and environmental friendliness. Locks, which are essential for inland waterways, often cause ship passage bottlenecks. This paper focuses on a green lock scheduling problem (GLSP), aiming to minimize fuel emissions and maximize navigation efficiency. Considering the realistic constraints, a mixed-integer linear programming model and a large neighborhood search solution algorithm are proposed. From a job shop scheduling perspective, the problem is decomposed into three main components: ship-lockage assignment, ship placement subproblem, and lockage scheduling subproblem coupled with ship speed optimization. A large neighborhood search algorithm based on a decomposition framework (LNSDF) is proposed to tackle the GLSP. In this, the complex lockage scheduling problem is addressed efficiently by mapping it to a network planning problem and applying the critical path method. Numerical experiments substantiate the effectiveness of our proposed model and a heuristic approach was used in solving the GLSPs. In the sensitivity analysis, under three different objective weight assignments, the resulting solutions achieved average effective ship fuel savings of 4.51%, 8.86%, and 2.46%, respectively. This indicates that our green lock scheduling problem considering ship speed optimization can enhance ship passage efficiency while reducing carbon emissions.
“…However, locks, such as Three Gorges Dam (TGD), have become bottlenecks and impeded the development of Yangtze Economic Belt (Figure 1 from https://cjhy.mot.gov.cn/). As is well known, waterway locks are indispensable to help overcome height differences between two adjacent river segments, and also bring benefits for power generation and flood prevention [2][3]. However, they can also become choke points for transport when traffic volumes exceed their navigation capacity, resulting in severe time delays and economic losses to carriers, shippers and consumers.…”
Transshipment can be a detour for carriers to bypass congested locks. Therefore, the local government provides subsidies to carriers reluctant to adopt transshipment due to high costs. Using the Three Gorges Dam (TGD) as the subject, we address the interaction between the government and carriers and the rational routine choice for carriers when facing severe congestion. Specifically, we investigate pricing competition among carriers under different scenarios. A two-stage game model based on Evolutionary game theory and Bertrand game is used for the study. The results confirm that: (1) Subsidies for the road alternative can alleviate congestion in waterways transport before TGD; (2) Road transport is an efficient way to alleviate lock congestion, especially under emergency states; (3) Public subsidies for road transport support this change of modes at a reasonable price to shippers. Additionally, carriers with transshipment mode can provide more competitive freight prices and more convenient services to customers.
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