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Inland waterway transport is an important mode of transportation for many countries and regions. Route planning optimization can reduce navigation time, avoid traffic congestion, and improve transportation efficiency. In actual operations, many vessels determine their navigation routes based on the experience of their shipowners. When the captain fails to obtain accurate information, experience-based routes may pose significant navigation risks and may not consider the overall economic efficiency. This study proposes a comprehensive method for optimizing inland waterway vessel routes using automatic identification system (AIS) data, considering the geographical characteristics of inland waterways and navigation constraints. First, AIS data from vessels in inland waters are collected, and the multi-objective Peak Douglas–Peucker (MPDP) algorithm is applied to compress the trajectory data. Compared to the traditional DP algorithm, the MPDP algorithm reduces the average compression rate by 5.27%, decreases length loss by 0.04%, optimizes Euclidean distance by 50.16%, and improves the mean deviations in heading and speed by 23.53% and 10.86%, respectively. Next, the Ordering Points to Identify the Clustering Structure (OPTICS) algorithm is used to perform cluster analysis on the compressed route points. Compared to the traditional DBSCAN algorithm, the OPTICS algorithm identifies more clusters that are both detailed and hierarchically structured, including some critical waypoints that DBSCAN may overlook. Based on the clustering results, the A* algorithm is used to determine the connectivity between clusters. Finally, the nondominated sorting genetic algorithm II is used to select suitable route points within the connected clusters, optimizing objectives, including path length and route congestion, to form an optimized complete route. Experiments using vessel data from the waters near Shuangshan Island indicate that, when compared to three classic original routes, the proposed method achieves path length optimizations of 4.28%, 1.67%, and 0.24%, respectively, and reduces congestion by 24.15%. These improvements significantly enhance the planning efficiency of inland waterway vessel routes. These findings provide a scientific basis and technical support for inland waterway transport. [ABSTRACT FROM AUTHOR]

Inland waterway transport (IWT) is recognized by its social, environmental, and economic advantages if compared with other transportation means. Nevertheless, several barriers have been identified which require the implementation of solutions that lead to the sustainable development of IWT. After reviewing the literature, this paper presents a framework of barriers and solutions for the sustainable development of IWT. The data were classified within the main elements of the IWT system: ports, fleet, and waterway, and subsequently grouped into one of the five proposed factors (governance and policies, management, operational, infrastructure and technology, and human resources). The basis for the enhancement of IWT is the attitude and change of mindset of governments towards IWT development. From there, several solutions can be implemented, such as policies that stimulate IWT growth aligned with the environmental requirements of each basin and encourage the private sector to take part in the search for alternatives in Favor of IWT development as a reliable, sustainable, and economically viable means of transport.

Inland waterway transport is considered a critical component of sustainable maritime transportation and is subject to strict legal regulations on fuel quality. However, crew members often prefer cheaper, inferior fuels for economic reasons, making government inspections crucial. To address this issue, we formulate the ship selection and inspection scheduling problem into an integer programming model under a multi-inspector and multi-location scenario, alongside a more compact symmetry-eliminated model. The two models are developed based on ship itinerary information and inspection resources, aiming to maximize the total weight of the inspected ships. Driven by the unique property of the problem, a customized heuristic algorithm is also designed to solve the problem. Numerical experiments are conducted using the ships sailing on the Yangtze River as a case study. The results show that, from the perspective of the computation time, the compact model is 102.07 times faster than the original model. Compared with the optimal objectives value, the gap of the solution provided by our heuristic algorithm is 0.37% on average. Meanwhile, our algorithm is 877.19 times faster than the original model, demonstrating the outstanding performance of the proposed algorithm in solving efficiency. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to evaluate the operational performance and service quality of inland waterway transport in Warri Southwest, Nigeria, by examining the factors that influence them. Methodology: The study employs a quantitative research approach, using a structured questionnaire to collect data from 180 respondents. The data is analyzed using regression analysis and a structural equation model (SEM) with the help of PLS Software Version 13.0. Results: The findings indicate that cargo clearance, infrastructure quality, and storage facilities significantly influence the performance of agent operation in inland waterway transport (p=0.000). Staff performance also directly impacts the provision of logistical services, which affects customer service. However, jetty operations do not promote operational performance (p=0.075). Additionally, staff performance does not significantly influence the association between jetty operation and performance and the relationship between cargo clearance and infrastructure level (p=0.136, 0.388). Theoretical contribution: This study contributes to the literature on inland waterway transport by providing empirical evidence on the factors influencing operational performance and service quality. The findings can help inform the development of policies and strategies to improve the efficiency and effectiveness of inland waterway transport in Nigeria and other similar contexts. Practical implications: The study's recommendations include improving the quality of infrastructure, cargo clearance processes, and storage facilities to enhance operational performance. Additionally, investing in staff training and development can improve the provision of logistical services and, in turn, customer service. The study also suggests that the government and relevant stakeholders should prioritize the development of inland waterway transport to unlock its potential for socioeconomic development, particularly in rural and hard-to-reach areas. [ABSTRACT FROM AUTHOR]

Abstract Over the years, the demand for transportation has experienced a consistent rise, which has exacerbated a multitude of issues including environmental, visual, and noise pollution, congestion, land use conflicts, and various other related challenges. In this regard, the pursuit of alternatives aimed at mitigating these adverse effects stands as a priority for governments and policymakers. Consequently, inland waterway transport (IWT) emerges as an appealing solution, due to its advantages across the social, environmental, and economic considerations. However, in relation to IWT the concept of sustainable development is insufficiently investigated. The objective of this paper is to undertake a comprehensive review of how the concept of sustainable development is addressed and applied within the framework of IWT systems. To achieve this goal, a systematic literature review was meticulously conducted, utilizing three academic databases (Scopus, Google Scholar, and EBSCO). The review process yielded a total of 51 papers that proved to be pertinent and relevant to the subject matter. The comprehensive literature review facilitated the delineation of the principal elements, factors, and characteristics of the IWT system, as well as the primary drivers for its sustainable development. However, the implications for further research were identified, such as a comprehensive examination of each case due to the distinct geographical, social, economic, and political conditions inherent to each individual basin. That is essential for understanding the unique barriers present within each context and for formulating viable solutions aimed at fostering and incentivizing the sustainable development of IWT systems.

Inland waterway transport is an important mode of transportation for many countries and regions. Route planning optimization can reduce navigation time, avoid traffic congestion, and improve transportation efficiency. In actual operations, many vessels determine their navigation routes based on the experience of their shipowners. When the captain fails to obtain accurate information, experience-based routes may pose significant navigation risks and may not consider the overall economic efficiency. This study proposes a comprehensive method for optimizing inland waterway vessel routes using automatic identification system (AIS) data, considering the geographical characteristics of inland waterways and navigation constraints. First, AIS data from vessels in inland waters are collected, and the multi-objective Peak Douglas–Peucker (MPDP) algorithm is applied to compress the trajectory data. Compared to the traditional DP algorithm, the MPDP algorithm reduces the average compression rate by 5.27%, decreases length loss by 0.04%, optimizes Euclidean distance by 50.16%, and improves the mean deviations in heading and speed by 23.53% and 10.86%, respectively. Next, the Ordering Points to Identify the Clustering Structure (OPTICS) algorithm is used to perform cluster analysis on the compressed route points. Compared to the traditional DBSCAN algorithm, the OPTICS algorithm identifies more clusters that are both detailed and hierarchically structured, including some critical waypoints that DBSCAN may overlook. Based on the clustering results, the A* algorithm is used to determine the connectivity between clusters. Finally, the nondominated sorting genetic algorithm II is used to select suitable route points within the connected clusters, optimizing objectives, including path length and route congestion, to form an optimized complete route. Experiments using vessel data from the waters near Shuangshan Island indicate that, when compared to three classic original routes, the proposed method achieves path length optimizations of 4.28%, 1.67%, and 0.24%, respectively, and reduces congestion by 24.15%. These improvements significantly enhance the planning efficiency of inland waterway vessel routes. These findings provide a scientific basis and technical support for inland waterway transport.

Purpose: This study aims to evaluate the operational performance and service quality of inland waterway transport in Warri Southwest, Nigeria, by examining the factors that influence them. Methodology: The study employs a quantitative research approach, using a structured questionnaire to collect data from 180 respondents. The data is analyzed using regression analysis and a structural equation model (SEM) with the help of PLS Software Version 13.0. Results: The findings indicate that cargo clearance, infrastructure quality, and storage facilities significantly influence the performance of agent operation in inland waterway transport (p=0.000). Staff performance also directly impacts the provision of logistical services, which affects customer service. However, jetty operations do not promote operational performance (p=0.075). Additionally, staff performance does not significantly influence the association between jetty operation and performance and the relationship between cargo clearance and infrastructure level (p=0.136, 0.388). Theoretical contribution: This study contributes to the literature on inland waterway transport by providing empirical evidence on the factors influencing operational performance and service quality. The findings can help inform the development of policies and strategies to improve the efficiency and effectiveness of inland waterway transport in Nigeria and other similar contexts. Practical implications: The study's recommendations include improving the quality of infrastructure, cargo clearance processes, and storage facilities to enhance operational performance. Additionally, investing in staff training and development can improve the provision of logistical services and, in turn, customer service. The study also suggests that the government and relevant stakeholders should prioritize the development of inland waterway transport to unlock its potential for socio-economic development, particularly in rural and hard-to-reach areas.

Inland waterway transport is considered a critical component of sustainable maritime transportation and is subject to strict legal regulations on fuel quality. However, crew members often prefer cheaper, inferior fuels for economic reasons, making government inspections crucial. To address this issue, we formulate the ship selection and inspection scheduling problem into an integer programming model under a multi-inspector and multi-location scenario, alongside a more compact symmetry-eliminated model. The two models are developed based on ship itinerary information and inspection resources, aiming to maximize the total weight of the inspected ships. Driven by the unique property of the problem, a customized heuristic algorithm is also designed to solve the problem. Numerical experiments are conducted using the ships sailing on the Yangtze River as a case study. The results show that, from the perspective of the computation time, the compact model is 102.07 times faster than the original model. Compared with the optimal objectives value, the gap of the solution provided by our heuristic algorithm is 0.37% on average. Meanwhile, our algorithm is 877.19 times faster than the original model, demonstrating the outstanding performance of the proposed algorithm in solving efficiency.

This paper disentangles the impact of critical water levels on container cargo transported along the Rhine River. It analyzes monthly throughput and all instances where navigability was constrained due to low or high water levels between 2000 and 2022, employing a time series econometric model. The study considers water level conditions at critical locations between economic centers while controlling for confounding effects. Our findings reveal an average monthly impact of -0.2% per day of disruption and -5.9% when the disruption remained for more than 24 days. Notably, vulnerability to critical conditions has doubled since 2018 and exhibits spatial variation. The most pronounced disturbances and their lagged effects are associated with localized low water level incidents. We show that enhancing the resilience of inland waterways to climate change is essential to avert potential losses in container throughput, estimated to range between 7% and 20% annual average by 2050. [ABSTRACT FROM AUTHOR]