Optimization on emergency materials dispatching considering the characteristics of integrated emergency response for large-scale marine oil spills

Many governments have been strengthening the construction of hardware facilities and equipment to prevent and control marine oil spills. However, in order to deal with large-scale marine oil spills more efficiently, emergency materials dispatching algorithm still needs further optimization. The present study presents a methodology for emergency materials dispatching optimization based on four steps, combined with the construction of Chinese oil spill response capacity. First, the present emergency response procedure for large-scale marine oil spills should be analyzed. Second, in accordance with different grade accidents, the demands of all kinds of emergency materials are replaced by an equivalent volume that can unify the units. Third, constraint conditions of the emergency materials dispatching optimization model should be presented, and the objective function of the model should be postulated with the purpose of minimizing the largest sailing time of all oil spill emergency disposal vessels, and the difference in sailing time among vessels that belong to the same emergency materials collection and distribution point. Finally, the present study applies a toolbox and optimization solver to optimize the emergency materials dispatching problem. A calculation example is presented, highlighting the sensibility of the results at different grades of oil spills. The present research would be helpful for emergency managers in tackling an efficient materials dispatching scheme, while considering the integrated emergency response procedure.Peer ReviewedPostprint (published version

Model and algorithm of two-stage distribution location routing with hard time window for city cold-chain logistics

Taking cold-chain logistics as the research background and combining with the overall optimisation of logistics distribution networks, we develop two-stage distribution location-routing model with the minimum total cost as the objective function and varying vehicle capacity in different delivery stages. A hybrid genetic algorithm is designed based on coupling and collaboration of the two-stage routing and transfer stations. The validity and feasibility of the model and algorithm are verified by conducting a randomly generated test. The optimal solutions for different objective functions of two-stage distribution location-routing are compared and analysed. Results turn out that for different distribution objectives, different distribution schemes should be employed. Finally, we compare the two-stage distribution location-routing to single-stage vehicle routing problems. It is found that a two-stage distribution location-routing system is feasible and effective for the cold-chain logistics network, and can decrease distribution costs for cold-chain logistics enterprises.Peer ReviewedPostprint (published version

From a feeder port to a hub port: the evolution pathways, dynamics and perspectives of Ningbo-Zhoushan port (China)

This paper analyses the spatio-temporal evolution of Ningbo-Zhoushan port growing from a feeder port to a hub port finding the historical pathways followed by its expanding in terms of container throughput capacity and total traffic. The dynamic mechanism of evolution is the results of economic globalization, containerization and its natural endowments in channel and terminal depths. Analysis of the traffic evolution and its underlying dynamics suggest 3 periods in the development processes of container transport in Ningbo-Zhoushan: (1) adoption period (1986–2000) in which the main dynamics is the impact of the Chinese ‘Open Door policy’; (2) acceleration period (2001–2008) in which the dynamics is related of the mainland China's entry into the World Trade Organization; (3) peak growth period (2009-now) in which the dynamics is impacted by the anti-crisis strategy against the financial and economic crisis in 2008. We analyse the perspectives of Ningbo-Zhoushan port. ARIMA model is employed to forecast the container traffic in the coming future; about after 2026, the throughput in Ningbo-Zhoushan port would reach about 49 million TEU which would be approximately equal to that of Shanghai port. The resultant port development would exemplify a model of spatial distribution such as a multi-layered gateway hub. In the respect of growth potential, Ningbo-Zhoushan port possesses excellent coastline resource suitable for deep-water berthing, bonded port policy and free trade zone policy. Geographical position, service level, hinterland economic level and government will support its perspectives.Peer ReviewedPostprint (author's final draft

Route Restoration Method for Sparse Taxi GPS trajectory based on Bayesian Network

In order to improve the availability of taxi GPS big data, we restore the chosen route for the sparse taxi GPS trajectory in this work. A trajectory restoration method based on Bayesian network is proposed. Compared with the traditional research solely based on time-spatial variables, this method additionally considers the characteristics of empty/heavy taxi status, weather conditions, drivers, vehicle running and other factors to carry out route restoration. A field case of grid network in Ningbo is taken to verify the applicability of the method, using the taxi GPS trajectory data from Ningbo Taxi Information Management Platform. The case results show that the accuracy of Bayesian network method based on multiple factors reaches 91.4%. Its performance is superior to the Multivariate logistic regression model. In addition, the proposed method is especially suitable for scenarios with a high missing rate of track data, such as a scene with timespan of about 5 min between neighbour trajectories

Collision risk assessment for ships’ routeing waters: An information entropy approach with Automatic Identification System (AIS) data

The ship's routing was adopted to organise marine traffic flow and reduce the risk of collision between ships in crowded waters. With the expansion of the world's fleet, ship traffic in shipping bottleneck and chokepoint areas became more and more busy and complex creating serious challenges for navigational safety. Therefore, quantitative collision risk assessment is significantly important for the ships' routeing waters. In this paper, the information entropy method which integrates the K-means clustering based on Automatic Identification System (AIS) data is introduced to quantitatively evaluate the collision risks in the ships' routeing waters. As a case study, the information entropy of Courses Over Ground (COG) for Ningbo-Zhoushan Port (the largest port in the world since 2009) is calculated by using historical AIS data. Then the K-means clustering is used to group the bytes of information entropy of the different legs in the shipping route. We find that in Ningbo-Zhoushan port Precautionary Area (PA) 2, 4 and 7 are the highest risk legs; PA 1, 5 and 6, Traffic Separation Scheme (TSS) 16, and 17 are medium-high risk areas. Therefore, ship collision risk prevention measures should be prioritised in those legs. Our contributions provide a novel approach to quantitatively assess ship collision risks in busy waters.Postprint (author's final draft

Optimization of urban distribution centres: a multi-stage dynamic location approach

Customer demand is dynamic and changeable; thus, optimality of the enterprise’s initial location cannot be guaranteed throughout the planning period in order to minimize site selection cost and maximize service reliability in the whole operation cycle. The enterprise planning period is divided into different stages, and a static location model is established at the fixed stage. In addition, a multi-stage dynamic location model is established by introducing the transfer cost between adjacent stages. To reduce the difficulty of solving the dynamic location model, first, we determined the optimal site selection and allocation strategy for each stage. Second, we designed a novel method that transforms the multi-stage dynamic location problem into the shortest path problem in graph theory. Finally, the Dijkstra algorithm was used to find the optimal dynamic location sequence so that its cumulative cost was the lowest in the whole planning period. Through a case study in China, we compare the costs of static and dynamic locations and the location cost under different objectives. The results show that this dynamic location generates more income (as it reduces cost) in comparison to the previous static location, and different location objectives have a substantial influence on location results. At the same time, the findings indicate that exploring the problem of enterprise location from a dynamic perspective could help reduce the operating cost and resources from a sustainable development perspective.Postprint (published version

Evaluation of the effectiveness of active and passive safety measures in preventing ship–bridge collision

The risk of ship–bridge collisions should be evaluated using advanced models to consider different anti-collision and bridge-protection measures. This study aimed to propose a method to evaluate the effectiveness of active and passive safety measures in preventing ship–bridge collision. A novel ship–bridge collision probability formulation taking into consideration different safety measures was proposed. The model was applied at Jintang Bridge in China where the surrounding vessel traffic is ultra-crowded. We calculated the collision probability between the bridge and passing traffic using automatic identification system (AIS) data, Monte Carlo simulation, and Bayesian networks. Results under four different safety measures (i.e., active measures, passive measures, both measures and none) were analyzed and compared. The analysis concluded that both active and passive safety measures are effective in reducing the ship–bridge collision probability. Active measures, if deployed properly, can provide protection at an equivalent level than passive measures against collision risks. However, passive measures, such as setting arresting cables, are necessary in cases where the response time of the active measures is long. The proposed method and the results obtained from the case study may be useful for robust and systematic effectiveness evaluation of safety measures in other cases worldwide.Postprint (published version

Analysis of taxi travels during an epidemic period using system dynamics method

This paper explores the factors influencing taxi travel in the context of COVID-19 from both demand and supply sides and provides a quantitative comparison of taxi travel characteristics and taxi industry operations before and after the epidemic. A model was established using system dynamics to simulate a taxi travel system, which was used to analyze the changes in demand and supply of taxi travel under scenarios such as closedowns, travel restrictions, etc. The analysis is based on a typical middle-sized city in China, Ningbo in Zhejiang Province, revealing factors leading to the significant drop in the amount of taxi travel due to the epidemic. The study can provide insights into impacts of public (or similar anomalous or catastrophic) events on taxi travel systems and could be useful for urban transport planning and management.Postprint (published version

Analysis of factors affecting the effectiveness of oil spill clean-up: A bayesian entwork approach

Ship-related marine oil spills pose a significant threat to the environment, and while it may not be possible to prevent such incidents entirely, effective clean-up efforts can minimize their impact on the environment. The success of these clean-up efforts is influenced by various factors, including accident-related factors such as the type of accident, location, and environmental weather conditions, as well as emergency response-related factors such as available resources and response actions. To improve targeted and effective responses to oil spills resulting from ship accidents and enhance oil spill emergency response methods, it is essential to understand the factors that affect their effectiveness. In this study, a data-driven Bayesian network (TAN) analysis approach was used with data from the U.S. Coast Guard (USCG) to identify the key accident-related factors that impact oil spill clean-up performance. The analysis found that the amount of discharge, severity, and the location of the accident are the most critical factors affecting the clean-up ratio. These findings are significant for emergency management and planning oil spill clean-up efforts.Postprint (published version