The selection and prioritization of suitable strategies to address the challenges to the successful operation and implementation of the bus rapid transit (BRT) system is a common problem faced by practitioners and decision-makers. Recent research has widely discussed the issue, but such assessments have remained limited in the city of Dar es Salaam, Tanzania context, where there are mobility difficulties. The present study addresses this research gap and identifies the most critical challenges to BRT implementation and operation, and recommends the most appropriate strategy for overcoming them. Seven strategies are defined. To prioritize these strategies, five criteria are determined. An integrated multi-criteria decision-making model is introduced. Improved Fuzzy Step-Wise Weight Assessment Ratio Analysis based on the Bonferroni operator was used to determine the importance of the criteria. Measurement of alternatives and ranking according to compromise solution was applied to assess and rank the strategies. The results indicate that “frequent flooding at the Jangwani bridge bus terminal” and “long waiting time at bus stops” are the most critical challenges while the fourth alternative “strengthening the operation and management” is the appropriate strategy to be implemented for successful operation and implementation of the BRT system. After that, a five-phase sensitivity analysis is performed to observe the robustness of the proposed approach. The results indicate the flexibility and applicability of the proposed approach can address real-life problems. The proposed methodology in this work can be instrumental in assisting mass transit operators with the successful implementation and operation of the BRT system.
Quality education and school transport are prerequisites for children to achieve sustainable development goals (SDGs), but they are disproportionately inadequate in rural communities. This study explores 350 parents' perceptions of the willingness‐to‐study (WTS) and learning difficulties of schoolchildren in Ukerewe Island (Tanzania) based on the mode of transport. The study surveyed 17 rural islands to build structural equation models based on Health Belief Model. The results showed that schoolchildren in Ukerewe Island have learning difficulties caused by the quality of their mode of transport to and from school. The children's learning difficulties were positively associated with perceived severity, self‐efficacy, and vulnerability. The perceived benefits of canoe transport supported the WTS. However, WTS could not buffer learning difficulties. Interestingly, male and female caregivers differ regarding the perceived WTS and their children's learning difficulties. This study contributes mitigation measures relevant to education and transport planning toward realizing SDGs 3, 4, and 10.
In the existing literature, the berthing operations, the quay crane assignments, and the scheduling problems were usually conducted without considering the worker performances (WPs) and the yard truck tasks (YTTs). However, professionals in situ corroborate the crucial effect of WPs and the yard YTTs on quay crane performance and efficiency. This study introduced a new feasible model for investigating the berth and the quay crane assignments based on the scheduling problem, including worker performances and yard truck deployment constraints. First, a mixed-integer programming (MIP) model is implemented to reduce the vessel’s departure time. Then, a particle swarm optimization (PSO) algorithm is introduced to solve the problems. The Dar es Salaam port is selected as a case study to test the proposed model with a real-time dataset that was collected from a multinational company managing container terminals. The results show the efficiency and the accuracy of the proposed model. The PSO algorithm is 86% and 62% more time-saving than MILP and T2S solutions for a small number of containers, respectively. Additionally, the PSO solution is 73% and 53% time-saving for a medium number of containers than MILP and T2S models, respectively. Finally, the present study proposes consideration of the worker assignment and the yard truck deployment during the planning phase.
Maritime Autonomous Surface Ships (MASS) have been an important direction for the development of intelligent shipping. However, most current international research on MASS focuses on navigation assistance technologies such as perception and decision-making, ignoring MASS’s traffic organization and management. The traffic organization service (TOS) under the e-Navigation strategy also has not researched MASS. In this paper, we propose the notion of on-demand service to MASS with different degrees of autonomy (DoA) and develop a new maritime service (MS) applicable to the MASS with various (DoA) following the e-Navigation technical architecture. We first analyze MASS requirements with different degrees of autonomy in traffic organization to define the service information. Then, based on the traditional TOS, we developed the MASS traffic organization service (MTOS), consisting of an operational architecture, five subsystems, and four services. In particular, we proposed a phased service trigger mechanism to solve the problem of publishing untimely and redundant service information. Tianjin port and Huanghua port were selected as cases study for simulation experiments; the study finding revealed that MTOS could provide standardized, accurate, and efficient traffic organization service for MASS with different degrees of autonomy on demand. The contribution can be applied in the port operation to improve traffic safety.
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