Last-mile delivery (LMD) is one of the crucial phases of the shipping process. Since e-commerce rapidly evolves, there are many issues that should be addressed in city logistics. This paper specifically tackles the issue of Third-Party Logistics (3PL) provider selection for sustainable last-mile delivery. The 3PL selection problem has been solved for the e-shop company from Belgrade, which has online sales. The management of the e-shop company has identified five possible 3PL providers. Those five 3PL providers have been evaluated according to six criteria such as distribution cost, on-time delivery, flexibility of distribution, IT capability, good cultural fit, and customer satisfaction index. To evaluate and rank the 3PL providers, two multi-criteria decision-making methods were coupled. The first one is a Best-Worst Method (BWM) used to find the criteria weights, while the second one is a Combined Compromised Solution (CoCoSo) method utilized to rank the 3PL providers from best to worst one. To check the stability as well as the robustness of the applied methods, sensitivity and comparative analyses are performed. The results show high confidence in the applied methods.
For the wounded triage, transport and cooperative scheduling problem of emergency surgery in urban emergency rescue, this study uses the idea of supply chain collaborative scheduling, considers factors such as the number of the wounded, rescue vehicle capacity and hospital operation time to achieve the optimization goals of the shortest rescue response time and the most economical transportation capacity, establishes a mixed integer programming model, and designs a two-stage scheduling algorithm to solve the model. It uses the relative gap between the maximum time span of the entire rescue process and the optimal performance under ideal conditions to measure the performance of the algorithm. The simulation experiments show that the two-stage scheduling algorithm has better problem-solving ability for scenarios with larger number of the wounded and stronger carrying capacity, and has better performance than MFF algorithm and MBF algorithm.
To accurately identify unlicensed taxis, this study measured their mileage using a traffic surveillance bayonet and obtained a threshold value by fitting a function to the mileage of previously identified unlicensed taxis. Abnormal driving vehicles were identified as those with a mileage exceeding the threshold value. Through a "white list" screening process, information on suspected unlicensed taxis was obtained. An empirical analysis of City A in Anhui Province showed an identification threshold of 85.8 km for unlicensed taxis. The study identified 68 highly suspected unlicensed taxis, 513 moderately suspected unlicensed taxis, and 1595 generally suspected unlicensed taxis. Suspected unlicensed taxis had a strong correlation with taxi mileage (r=0.895, sig(2-tailed)=0), with a mean mileage of 128.5 km and standard deviation of 50.8. This mileage was less than the average taxi mileage but significantly higher than the mileage traveled by private cars (mean=25.1 km, SD=16.4). The study's contribution lies in its development of a method for accurately identifying unlicensed taxis, which has significant implications for improving transportation safety.
The scientific location and layout of emergency material storage and rescue points in urban areas are critical aspects of emergency management. In this study, a multi-objective programming optimization model was constructed based on related theories, incorporating multiple goal combinations with different dimensions according to various disaster scenarios and urban emergency needs. The weight factors of emergency timeliness, economy, and safety were considered, and the multi-objective model optimization problem was transformed into a single-objective comprehensive optimization model problem using the weight method. The analysis decision function was utilized to study the transformation and solution method of the urban emergency rescue point location model. Heuristic optimization algorithms were employed to perform average segmentation calculations on the preset neighborhoods, constantly changing and narrowing the neighborhood range until the algorithm termination conditions were met, approaching the domain range of the optimal solution. Additionally, another precision parameter was utilized to control the accuracy of the final solution neighborhood range. The optimization of emergency vehicle scheduling was used to synergistically solve the problem of reserve rescue point location layout and optimization solution. The results of the example demonstrate the feasibility of constructing a multi-objective model with multiple combinations of different dimensions of objectives and the rationality of the Dijkstra heuristic optimization algorithm used. This study provides multiple methodologies and alternative site selection plans for decision-makers to select the required multi-objective reserve rescue point location model based on different urban disaster situations and their own emergency rescue needs.
The utilization of public transport by people with disabilities presents significant challenges, as the services offered are often inaccessible and fail to meet the diverse needs of users. Despite attempts to improve accessibility, these solutions are often partial and poorly planned, resulting in limited connectivity to daily activities. Therefore, increasing the usage of public transport by people with disabilities requires a multifaceted approach. In this context, a research study was conducted in the Republic of Serbia through open-ended questionnaires to investigate mobility patterns, primarily focusing on rail traffic and extending to other modes of transport. The study reveals several problems, highlighting the need for collaborative interventions among authorities, transport service providers, and people with disabilities. This is the first study in the Republic of Serbia to investigate this issue, and the results indicate that the process of improving accessibility is iterative and requires ongoing monitoring to assess progress and mutual understanding. To improve the usage of railways and public transport by people with disabilities, it is essential to implement interventions that target the identified issues.
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