Transportation Problem Research Articles

Investigation of independence in the tasks involving the use of public transportation in patients with subacute stroke.

To clarify the percentage of stroke patients who are independent in performing tasks involved in public transportation use and problems faced while doing so. Single-institution retrospective study. A total of 237 post-stroke patients utilized public transportation during their hospitalization in subacute rehabilitation wards. Participants' actual performance in 14 tasks involving public transportation use was assessed using the Public Transportation Use Assessment Form. For each task, the percentage of participants who could perform the task independently was calculated and identified performance problems were categorized. The task with the lowest percentage of independent participants was "Walking in crowds", with 146 of 236 (61.9%) participants performing this independently, followed by "Selecting departure time and platform" (149 of 229, 65.1%), and "Getting on and off trains" (162 of 230, 70.4%). Problems faced when "Walking in crowds" included the "Risk of colliding with others" (n = 34), "Stopping abruptly" (n = 16), "Lack of attention to surroundings" (n = 14), and "Unable to walk with the flow of people" (n = 11). A significant number of patients could not perform tasks independently and faced various performance problems. These issues should be addressed during rehabilitation to enable patients to use public transportation.

Modelling route choice in public transport with deep learning

Abstract For choice problems in transportation, machine learning and deep learning are alternative methods to traditional choice models. While several works explored the potential of this technology for modelling mode choice, lower attention is given to route choice, especially in public transport. In this work, we propose a deep learning model designed specifically for route choice in public transport. The model can estimate a nonlinear utility function, allowing complex interactions among the variables; it can easily include non-alternative specific variables, such as weather or socio-demographic information. Moreover, compared to the traditional choice models, it numerically outperforms the Path Size Logit Model in prediction performance, and does not require pre-specification of the model by an experienced human modeler. These properties are particularly useful for route choice analyses, to capture possible heterogeneities or complex behavior, which are difficult to model a priori. We evaluated the interpretability of the model observing the marginal rates of substitution and applying Accumulated Local Effects, showing meaningful effects of the variables on the probability to choose an alternative. We tested the proposed model on a large-scale dataset based on GPS tracking. We considered both synthetic choices, to demonstrate the model properties, and real choices, to evaluate the model in practice. The results showed moderately better performance of the deep learning model compared to the Path Size Logit, confirming the possibility of using it for modeling and predicting route choice.

Exponential neutrosophic programming contrivance in multiple criteria for type-2 uncertain multi-objective transportation problem

Exponential neutrosophic programming contrivance in multiple criteria for type-2 uncertain multi-objective transportation problem

Assessing the Landscape for PrEP Provisions in Prisons: A Systematic Review.

This systematic review aims to review awareness and willingness for PrEP use in the prison complex and the factors influencing PrEP uptake among people incarcerated in state or federal prisons. We searched MEDLINE (OVID), EMBASE, and Scopus for relevant articles. Qualitative or quantitative studies focusing on incarcerated population, and outcome measures such as knowledge, willingness, or influencing factors for PrEP uptake were included. A narrative method was used to summarise the findings. Inmates' knowledge of PrEP was very low. Inmates who were briefly introduced to PrEP showed a favourable attitude and willingness toward it. However, low-risk perception of HIV, fear of stigma, jail policies, low priority to health overall, appointment issues, transportation problems, depression, substance misuse, and budgetary limitations after release were perceived as barriers to its uptake and continuation. PrEP is a much-needed HIV prevention strategy for the incarcerated population. However, removing the structural and social obstacles to sustained adherence is imperative.

A solution of mathematical multi-objective transportation problems using the fermatean fuzzy programming approach

A solution of mathematical multi-objective transportation problems using the fermatean fuzzy programming approach

Partial transport for point-cloud registration

Abstract Point cloud registration is an important task in fields like robotics, computer graphics, and medical imaging, involving the determination of spatial relationships between point sets in 3D space. Real-world challenges, such as non-rigid movements and partial visibility, including occlusions and sensor noise, make non-rigid registration particularly difficult. Traditional methods are often computationally intensive, exhibit unstable performance, and lack strong theoretical guarantees. Recently, the optimal transport problem, including its unbalanced variations like the optimal partial transport problem, has emerged as a powerful tool for point-cloud registration. These methods treat point clouds as empirical measures and provide a mathematically rigorous framework to quantify the correspondence between transformed source and target points. In this paper, we address the non-rigid registration problem using optimal transport theory and introduce a set of non-rigid registration methods based on the optimal partial transportation problem. Additionally, by leveraging efficient solutions to the one-dimensional optimal partial transport problem and extending them via slicing, we achieve significant computational efficiency, resulting in fast and robust registration algorithms. We validate our methods by comparing baselines on various 3D and 2D non-rigid registration problems with noisy point clouds.

Handling the challenges of a green supply chain in the context of product blending transportation within a neutrosophic environment

The accelerated growth of economic activity and resource consumption underscores the urgent need to integrate sustainability into transportation systems. This paper explores the incorporation of sustainability into multi-product blending processes within these systems, focusing on several critical objectives: minimizing transportation costs — including variable expenses, fixed charges, and maintenance costs — carbon emissions, and product deterioration, while maximizing the volume of liquid transported and reducing transportation time. Real-world transportation scenarios are often complicated by data limitations, measurement inaccuracies, and uncertainties, which challenge effective decision-making. To address these challenges, this research introduces Neutrosophic Sets as a robust framework for managing uncertainty by capturing varying degrees of truth, falsity, and indeterminacy. The study employs a neutrosophic environment with Neutrosophic Goal Programming, Fuzzy Programming, and Two-Phase Programming methodologies to determine a compromise solution for the multi-objective transportation problem. The effectiveness of the proposed model is demonstrated through numerical simulations, with results compared to traditional methods. The paper concludes with a comprehensive sensitivity analysis and outlines future research directions, providing valuable insights into the optimization of sustainable transportation systems.

Solving continuous-discrete two-stage logistic problem of optimal partitioning-allocation

The theory of optimal set partitioning is a powerful tool for solving infinite-dimensionaloptimization problems, including infinite-dimensional transportation problems where oneside, producers or consumers, is continuously allocated in a subset of n-dimensional space,for example, over a part ofa plane. A variation of the transportation problem is describedwhere the transportation of products is done in two stages, with intermediate transporta-tion points being integrated intothe model. First, products are transported from a set ofcontinuously distributed producers to a set of waypoints. Then, products are transportedfrom waypoints to a set of ultimate consumers. The defined problem consists of a classicdiscrete transportation problem and an infinite-dimensional transportation problem withoptimal partitioning-allocation of space. Such problem formulation significantly compli-cates the mathematical model but simultaneously allows us to get more optimal solutionsand solve problems that are closer to real-life cases of product transportation.A process of building a mathematical model is described, a method is proposed for solv-ing a two-stage logistic problem of optimal partitioning-allocation, and an algorithm isformulated based on the proposed method. Based on the formulated algorithm, softwareimplementation is developed thatsolves the two-stage problem in the case of two-dimensional space, that is on the plane. The software implementation consists of a compu-tational part that executes all necessary mathematical calculations, a graphical user inter-face part that allows to quickly and conveniently set initial conditions and parameters ofthe problem, and a visualizing part that conducts an interactive demonstration of interme-diate and final solutions of the problem. All parts are integrated into a single system. Ex-amples of solving several problems are shown for demonstration of the workof the pro-posed methodand explanation of key details.

On goal programming approach for interval-valued intuitionistic fuzzy multi-objective transportation problems with an application to tourism industry

On goal programming approach for interval-valued intuitionistic fuzzy multi-objective transportation problems with an application to tourism industry

A conceptual framework for sustainable location, inventory and transportation problems in a supply chain context

A conceptual framework for sustainable location, inventory and transportation problems in a supply chain context

Solving the Type 2 Trapezoidal Intuitionistic Fuzzy Fractional Transportation Problem Using the Diagonal Optimal Approach

This research develops a diagonal optimal technique for solving the Type 2 Trapezoidal Intuitionistic Fuzzy Fractional Transportation Problem (T2TIFFTP), aiming to minimize transportation costs within an optimal solution framework. By incorporating the intuitionistic fuzzy fractional approach, the method effectively addresses the uncertainty and imprecision commonly encountered in real-world transportation scenarios. Numerical results demonstrate the technique’s efficiency and effectiveness. This highlighting its potential to significantly enhance the accuracy and quality of solutions in complex transportation situations. The diagonal optimal technique provides a robust framework for tackling fuzzy transportation problems, paving the way for more reliable and cost-efficient decision-making in uncertain environments

Faktor-Faktor yang Mempengaruhi Efektivitas Non Aktifnya Trayek Bus Trans Kota di Bandar Lampung

Bandar Lampung City is one of the developing cities that has transportation problems, especially mass transportation or public transportation. Existing public transportation, such as city buses and city transportation, is not very efficient for its users. This is because the safety and comfort factors are so lacking that people prefer to use private vehicles compared to public transportation. The purpose of this study was to determine the main factors that influence the inactivity of the Trans City Bus route in Bandar Lampung City and to determine the level of user satisfaction with the Bandar Lampung Trans City Bus service using the Customer Satisfaction Index (CSI) and Importance Performance Analysis (IPA) data analysis methods. The results of this study explain that the main factor causing the inactivity of the Trans City Bus route in Bandar Lampung City is competition with online transportation. Results using the IPA method In quadrant 1, there are 11.11% of respondents who feel that the performance level of these facilities and services is high, In quadrant 2, there are 55.56% Respondents who feel that these facilities and services are very important with a high level of performance. In quadrant 3, there are 22.22% of respondents who feel that these facilities and services are relatively low with a low level of performance.In quadrant 4, there are 11.11% of respondents who feel that these facilities and services are very important, with CSI showing the results of users being satisfied with the satisfaction index value reaching 0.734%.

Exploring a discounted credit-linked multi-objective two-stage transportation problem under triangular hesitant fuzzy environment

Exploring a discounted credit-linked multi-objective two-stage transportation problem under triangular hesitant fuzzy environment

The integrated lot-sizing problem of production, remanufacturing and transportation, considering recovery targets

The integrated lot-sizing problem of production, remanufacturing and transportation, considering recovery targets

On the pure fixed charge transportation problem

On the pure fixed charge transportation problem

Code and Data Repository for Iterated Inside Out: a new exact algorithm for the transportation problem

This software provides the implementation of Iterated Inside Out, a new exact algorithm for solving the transportation problem. The software also implements the Shielding Method by B. Schmitzer and a standard transportation simplex.

A Probabilistic Framework for Evaluating Efficiency Gains in Vogel's Approximation Method

Transportation involves various uncertainties in determining the most efficient method for transporting goods. When a company has supply and destination points, or a supplier has specific demands, achieving an optimized balance becomes crucial. This task becomes more challenging when there is an imbalance between demand and supply, requiring an effective method to measure and address uncertainty. Probability theory provides a reliable framework for quantifying these uncertainties. Basic feasible solutions to transportation problems can be obtained using methods such as the North-West Corner Method, Least Cost Method, Row (Column) Minima Method, or Vogel’s Approximation Method. Among these, Vogel’s Approximation Method is widely recognized for its effectiveness in yielding superior results. This paper proposes a novel approach that integrates probability analysis into transportation problems, emphasizing the derivation of the probability distribution function (PDF) for Vogel's Approximation Method. The derived results not only enhance understanding but also offer valuable insights to improve decision-making processes within the transportation domain.

Solving Multistage Transportation Problems: Minimizing Costs and Optimizing Transshipment Strategies

Solving Multistage Transportation Problems: Minimizing Costs and Optimizing Transshipment Strategies

Generalized Intuitionistic Trapezoidal Fuzzy Numbers in Transportation Problems: An Optimizational Method

In this study, we propose an optimization method for transportation problems utilizing Generalized Intuitionistic Trapezoidal Fuzzy Numbers (GITFNs). This method effectively handles uncertainty and imprecision in transportation systems, enabling more realistic and reliable decision-making. A GITFN-based transportation model is developed, incorporating fuzzy costs, capacities, and demands. An optimization algorithm is designed to minimize transportation costs while satisfying supply and demand constraints. The method is applied to a numerical example, demonstrating its efficiency in solving complex transportation problems. The results show significant improvements in transportation effectiveness and cost reduction.

Navigating a transportation system challenge with hybrid fuzzy stochastic multi-choice travel time and reliability: an application to maritime transportation

In a transportation network, a diverse range of carriers, time alternatives, and cost options lead to the emergence of multi-choice parameters. Moreover, the uncertain nature and the interplay of these factors exacerbate the complexity of decision-making processes in transportation planning. Transportation in an uncertain environment requires flexibility and the ability to adapt quickly. Transportation systems capable of adjusting to diverse conditions can effectively deal with challenges and achieve optimal performance.this paper investigates a time-reliability two-objective uncertain multi-choice scenario for the transportation problem in a multi-commodity network. The proposed Multi-Commodity Network Flow (MCNF) problem has a fractional objective function with multi-choice, fuzzy random, and fuzzy variables. The probability-possibility approach handles the uncertainty and the Lagrange interpolating polynomial represents the relationship between alternative choices. The Charnes–Cooper variable transformation method converts the fractional problem into its deterministic equivalent form. A real-world example of general cargo shipment services is used to assess the model's effectiveness.