Transportation Problem Research Articles

An approach to optimize transportation problemswith neutrosophic numbers based on a newranking function

A transportation problem (TP) is built on the framework of supply-demand and cost parameters which are uncertain in nature. Neutrosophic numbers are capable of handling incomplete information. This paper introduces a new solution approach to optimize TPs with neutrosophic parameters based on a new ranking function. This function utilizes the attitudinal character of a basic unit-interval monotonic function inspired from the domain of continuous ordered weighted average operators. Ranking rules are established followed by defining a neutrosophic transportation problem. A solution methodology followed by solved numerical illustrates the efficiency of the proposed method. Conclusion and future directions summarize the work.

Synthesis of terpolymer from Helianthus annuus (natural oil) and evaluation as pour point depressant and viscosity reducer on Indian crude oil

Pour Point Depressant is introduced to crude oil at ppm level to overcome transportation problem of crude oil because of its complex chemical structure. Synthesized PPDs improve flow property, viscosity and also improve its numerous parameters to improve performance of crude oil. Low molecular weight and high molecular weight, copolymer having better PPD types. In present work, synthesized Terpolymer, from natural source, was formed from the reaction with Helianthus annuus oil and ester of Erucic Acid with various fatty alcohol. It was evaluated for its properties on Indian waxy crude oils, i.e., From Limbodra well. Structure and molecular weight of synthesized polymer was confirmed by Spectral data and Gel permeation chromatography (GPC). Also its effect on crude oil was evaluated by Rheological studies, SARA Analysis, Pour point depressant effect. Cross–polarizing microscopic studies were performed to study changes in morphology of wax crystals in crude oil with and without additive. A zero friction advanced Rheometer AR-500 was used to determine the viscosity by applying Bingham plastic-flow model.

The role of representations constructed by students in learning how to solve the transportation problem

The purpose of the research presented in this paper was to study the role of concrete and table representations created by students in learning how to solve an optimization problem called the transportation problem. This topic was learned in collaborative groups using table representations suggested by teachers in 2021. In 2022, the researchers decided to enrich the students’ learning environment with concrete objects and urged the students to use them to present the problem to be solved. The students did it successfully and, to be able to record it in their notebooks, they constructed a table representation by themselves without any help from their teacher. After that, they managed to solve the problem by manipulating the objects. At the same time, each step in the solution was presented with changes in the table. The students were assessed before (pre-test) and after collaborative learning (test) in both academic years. The pre-test results were similar, but the test results were better in 2022. Therefore, it can be concluded that using concrete and table representations constructed by students in learning how to solve transportation problems makes collaborative learning more constructivist and more effective than when they use only table representations suggested by their teachers. Subject Classification: 97M10, 97M40

MILP models of a patient transportation problem

With ageing societies and increasing number of patients, there is a growing need for quality services that help transporting non-urgent patients to hospitals. In logistics, patient transportation problems are usually modeled as a dial-a-ride problem. In a Dial-a-Ride problem, a fleet of vehicles is providing the delivery services between the loading points and the delivery destinations. The demands are known in advance. In most cases the total travel distance of the vehicles is to be minimized. In this paper, we consider a specific dial-a-ride problem, where a single vehicle is used to transport patients to the same hospital. In determining the optimal route, the multiple and different travel needs of patients, such as their maximum travel time, are also taken into consideration. We introduce 4 different mixed integer linear programming models of the routing problem. Finally, the efficiency of the four models was compared using some real-life problems by solving them with a commercial solver.

Модульні вантажні одиниці та модульні вантажоперевізні комплекси для інтермодального перевезення рідких вантажів

The purpose of the article is to analyze the problems of liquid cargo transportation between Ukraine and the EU countries, due to the non-interoperability of their railway transport systems. The analysis of existing solutions in the intermodal way of transporting liquid cargo was carried out. Their shortcomings are pointed out and their solution proposed by introducing a modular tank container MVO 480.00.110-02 for intermodal transportation of fuels and lubricants (F&L), liquefied petroleum gases (LPG), oil and other liquid cargoes by rail transport of 1435/1520 mm gauges. In the conditions of the ongoing war, there was an acute problem of ensuring the transportation of F&L from EU countries to Ukraine. It was complicated by the different width of the railway track. This required the replacement of tank car bogies at the joints of the 1435/1520 mm railway tracks. In addition, private tank cars had dimensions that are allowed for transportation only on railways with a gauge of 1520 mm. They exceeded the dimensions allowed for transportation on tracks of 1435 mm. This did not allow them to be used for transporting liquid cargo from EU countries. Usually, ISO 1496-3 tank containers with a length of 20 feet are used for intermodal transportation of liquid cargoes by sea, rail and road transport. In connection with the universal purpose and the need for stacking during sea transportation, their dimensions are made much smaller than the dimensions allowed for transportation by rail. Tank containers in the form of removable bodies – Swap Body tank containers are used for intermodal transportation of liquid cargo only by road and rail transport. The article points out the shortcomings of existing cargo units. To eliminate them, our company developed and patented tank containers – modular loading units (MLU) 480.00.110-02.
 For intermodal transportation of liquid cargo by rail transport of gauge 1435/1520 mm. MLU 480.00.110-02 are made in the form of modular connector complexes, which are assembled from container and cargo modules. The unified platform container model 480.00.010 of the ISO 668 standard, series 1, size and type code 29Р0 is used as a container module. Cargo modules can be mounted on the container module – removable tanks of various specializations for the transportation of various liquid cargoes. This execution of modular loading units made it possible to expand their specialization and increase the volume of tanks by 40 ÷ 45% in comparison with existing cargo units, with the possibility of transportation in the dimensions of the load of tracks of 1435/1520 mm. A comparison of the cost of transportation of liquid cargoes by tank cars, tank trucks and tank containers is given. MLU 480.00.110-02. The technical conditions of NTU 480.00.110-02 on transportation by fitting platforms of tracks of 1435/1520 mm were developed and agreed with the railway administrations of Ukraine and EU countries. An example of the implementation of a modular cargo transport complex for the transportation of liquid cargo on 1435 mm tracks is given. It can be retrofitted in operation by shippers by replacing the removable tank with a removable tank of the desired specialization, or by replacing the 1435 mm track fitting platform with a 1520 mm track fitting platform. Modular cargo transport complexes are an intermodal alternative to specialized tank cars, which is extremely necessary to ensure the transportation of liquid cargo between Ukraine and the EU countries.

Students' Transportation Problems in University Campus A Case Study, Tripoli University, Libya

University campuses are small cities in urban areas that are active and attractive destinations. This high level of activity causes severe congestion on campuses and in the surrounding area, especially in urban university locations. Tripoli University campuses are multi-modal and complicated, combining automotive traffic, public transportation, and pedestrians into a single transportation system. This poses a serious problem for university campuses. Vehicular congestion in a campus setting creates several significant conflict areas that range from pedestrian safety to traffic and transit operations. The university has the greatest influence on the surrounding neighborhoods. Innovative transportation approaches can diffuse from higher education to other parts of society.The aim of this study is to understand the main transportation system used at Tripoli University and document a systematic approach to analyze the problems associated with university campus transportation systems and develop solutions to this problem.The research question how can Tripoli University students reach the university campus in less time and more safely?The methodology used in the research will also generate a questionnaire online for students and staff collecting data from other studies and gain knowledge from other countries' solutions. Effective university campus design has the biggest impact in this area. The expected outcome will be a Based on the findings, this study proposed a mode of transportation that would aid in the discovery of effective solutions to the problem, reduce the amount of time spent traveling every day at the university, and create an integrated university campus.

A dragonfly algorithm for solving the Fixed Charge Transportation Problem FCTP

The primary focus of this article is dedicated to a thorough investigation of the Fixed Load Transportation Problem (FCTP) and the proposition of an exceedingly efficient resolution method, with a specific emphasis on the achievement of optimal transportation plans within practical time constraints. The FCTP, recognized for its intricate nature, falls into the NP-complete category, notorious for its exponential growth in solution time as the problem's size escalates. Within the realm of combinatorial optimization, metaheuristic techniques like the Dragonfly algorithm and genetic algorithms have garnered substantial acclaim due to their remarkable capacity to deliver high-quality solutions to the challenging FCTP. These techniques demonstrate substantial potential in accelerating the resolution of this formidable problem. The central goal revolves around the exploration of groundbreaking solutions for the Fixed Load Transportation Problem, all while concurrently minimizing the time investment required to attain these optimal solutions. This undertaking necessitates the adept utilization of the Dragonfly algorithm, an algorithm inspired by natural processes, known for its adaptability and robustness in solving complex problems. The FCTP, functioning as an optimization problem, grapples with the multifaceted task of formulating distribution plans for products originating from multiple sources and destined for various endpoints. The overarching aspiration is to minimize overall transportation costs, a challenge that mandates meticulous considerations, including product availability at source locations and demand projections at destination points. The proposed methodology introduces an innovative approach tailored explicitly for addressing the Fixed Charge Transport Problem (FCTP) by harnessing the inherent capabilities of the Dragonfly algorithm. This adaptation of the algorithm's underlying processes is precisely engineered to handle large-scale FCTP instances, with the ultimate objective of unveiling solutions that have hitherto remained elusive. The numerical results stemming from our rigorous experiments unequivocally underscore the remarkable prowess of the Dragonfly algorithm in discovering novel and exceptionally efficient solutions. This demonstration unequivocally reaffirms its effectiveness in overcoming the inherent challenges posed by substantial FCTP instances. In summary, the research represents a significant leap forward in the domain of FCTP solution methodologies by seamlessly integrating the formidable capabilities of the Dragonfly algorithm into the problem-solving process. The insights and solutions presented in this article hold immense promise for significantly enhancing the efficiency and effectiveness of FCTP resolution, ultimately benefiting a broad spectrum of industries and logistics systems, and promising advancements in the optimization of transportation processes

Maximizing the Supply Chain Profit in Multimodal Transportation Problem with Transfer Part using Two-Echelon Genetic Algorithm

Multimodal transportation is a highly effective method for optimizing deadlines and reducing inventory costs, both of which are crucial in a supply chain environment. This study employs a mathematical programming model to optimize the supply chain profit for multimodal transportation distribution within a specified time window. The model considers five factors, such as production cost, transportation cost, transport time, penalty cost, and sales price. Additionally, a Two-Echelon Genetic Algorithm (TEGA) is proposed to solve the optimization problem, and a numerical example is provided to validate the model and algorithm. The study compares the performance of the proposed algorithm with the exact solution from a previous study, presents implementation details and numerical experiment results, and analyses the findings. The results demonstrate the efficiency and robustness of the algorithm, making it a significant contribution to transportation planning for freight transportation and supply chain management.

Integrated Q-Learning with Firefly Algorithm for Transportation Problems

The study addresses the optimization of land transportation in the context of vehicle routing, a critical aspect of transportation logistics. The specific objectives are to employ various meta-heuristic optimization techniques, including Genetic Algorithms (GA), Ant Colony Optimization (ACO), Firefly Algorithm (FA), Particle Swarm Optimization (PSO), and Q-Learning reinforcement algorithm, to find the optimal solutions for vehicle routing problems. The primary aim is to enhance the efficiency and effectiveness of land transportation systems by minimizing factors such as travel distance or time while adhering to constraints. The study evaluates the advantages and limitations of each algorithm and introduces a novel-based approach that integrates Q-learning with the FA. The results demonstrate that these meta-heuristic optimization techniques offer promising solutions for complex vehicle routing challenges. The integrated Q-learning with Firefly Algorithm (iQLFA) emerges as the most successful approach among them, showcasing its potential to significantly improve transportation optimization outcomes.

Kombinasi Metode Bilqis Chastine Erma dan Sumathi Sathiya dengan Metode Stepping Stone untuk Optimasi Masalah Transportasi

Transportation problems experienced by UD. Raja Wangi in distributing Maha Dewa fragrant incense. UD. Raja Wangi incurs high transportation costs due to irregular direct distribution patterns and has not paid attention to the route to be passed. One way to solve the problem is to use transportation methods to get the optimal distribution route so that the transportation costs incurred are minimal. This study aims to solve transportation problems using the Bilqis Chastine Erma (BCE) method and the Sumathi Sathiya method with the Stepping Stone method to obtain the optimal solution. The Bilqis Chastine Erma (BCE) and the Sumathi Sathiya methods are indirect methods of solving transportation problems by obtaining an initial solution. After obtaining the initial solution, the Stepping Stone method is used to obtain the optimal solution. The results showed that the optimal solution using the Stepping Stone method based on the initial solution of the Bilqis Chastine Erma (BCE) method obtained a total transportation cost of Rp42,937.00 while the optimal solution using the Stepping Stone method based on the initial solution of the Sumathi Sathiya method obtained a total transportation cost of Rp38,727.00. In addition, the Sumathi Sathiya method gets a difference in total transportation costs of Rp11,790.00 or 23% of the total transportation costs incurred by the UD. Raja Wangi. Therefore, the Sumathi Sathiya method is the best solution for minimizing transportation costs.

Abstract HUP4: Can A Remote Telehealth-based Program Support Survivors With Varying Social Needs Post-stroke?

Introduction: There are significant and longstanding inequities in stroke prevalence and care as well as outcomes. Social determinants of health (SDOH) are known to be a risk factor in post-stroke recovery. SDOH also put individuals at higher risk for 90-day mortality. Social determinants are a significant contributor to disparities in health and specifically addressing SDOH needs may improve the health and outcomes of stroke survivors. Methods: An app-based, virtual care model was used to impact survivor quality of life and outcomes for stroke survivors and their care partners. As a part of program onboarding, the clinical navigator utilized the CMS Accountable Health Communities Health-Related Social Needs Screening Tool to assess survivor needs in five core domains including housing instability, food insecurity, transportation problems, utility needs, and interpersonal safety. As needs were identified, they were cross-walked to pre-populated community resource maps to aid the survivor in their recovery and support subsequent stroke prevention. Results: Of the (n=50) stroke survivors (median age of 62) that completed the 12-week survivor-led Navigator support program, 35% had one SDOH need, 16% had 2 SDOH needs, 16% had 3 SDOH needs, 3% had 4 SDOH needs and 28% had 5 or more SDOH needs. The most regularly identified areas of social need in the cohort were mental health (20%), financial strain (15.7%), employment (13.6%) and transportation (12.9%). These SDOH were addressed throughout the 90-day program based on individual access considerations. The 30- and 90-day all-cause readmission rates for survivors were 5% and 10%, respectively, superior to recent publications reporting 30-day unplanned readmission rates after stroke ranging from 8.7%-12.5%, and 90-day readmissions ranging from 18.9% to 20.7%. Conclusion: By assessing SDOH and providing specifically tailored post-acute resources to meet those needs, a tech-enabled platform with clinical navigator support can improve outcomes for stroke survivors with a variety of SDOH needs. Additional post-acute stroke care and targeted programming are needed to address the ongoing inequalities in the healthcare system as they relate to post-stroke care and recovery in populations with high SDOH needs.

Abstract NS4: Can a Remote Telehealth-Based Program Support Survivors With Varying Social Needs Post-Stroke?

Introduction: There are significant and longstanding inequities in stroke prevalence and care as well as outcomes. Social determinants of health (SDOH) are known to be a risk factor in post-stroke recovery. SDOH also put individuals at higher risk for 90-day mortality. Social determinants are a significant contributor to disparities in health and specifically addressing SDOH needs may improve the health and outcomes of stroke survivors. Methods: An app-based, virtual care model was used to impact survivor quality of life and outcomes for stroke survivors and their care partners. As a part of program onboarding, the clinical navigator utilized the CMS Accountable Health Communities Health-Related Social Needs Screening Tool to assess survivor needs in five core domains including housing instability, food insecurity, transportation problems, utility needs, and interpersonal safety. As needs were identified, they were cross-walked to pre-populated community resource maps to aid the survivor in their recovery and support subsequent stroke prevention. Results: Of the (n=50) stroke survivors (median age of 62) that completed the 12-week survivor-led Navigator support program, 35% had one SDOH need, 16% had 2 SDOH needs, 16% had 3 SDOH needs, 3% had 4 SDOH needs and 28% had 5 or more SDOH needs. The most regularly identified areas of social need in the cohort were mental health (20%), financial strain (15.7%), employment (13.6%) and transportation (12.9%). These SDOH were addressed throughout the 90-day program based on individual access considerations. The 30- and 90-day all-cause readmission rates for survivors were 5% and 10%, respectively, superior to recent publications reporting 30-day unplanned readmission rates after stroke ranging from 8.7%-12.5%, and 90-day readmissions ranging from 18.9% to 20.7%. Conclusion: By assessing SDOH and providing specifically tailored post-acute resources to meet those needs, a tech-enabled platform with clinical navigator support can improve outcomes for stroke survivors with a variety of SDOH needs. Additional post-acute stroke care and targeted programming are needed to address the ongoing inequalities in the healthcare system as they relate to post-stroke care and recovery in populations with high SDOH needs.

Multi-Objective Green 4-Dimensional Transportation Problem for Incompatible Damageable Items with Optimum Use of Transport Vehicles’ Space

In the transportation system, an item is transported from sources to destinations. In this process, as well as the weight of the items volume of the items also plays a crucial role in obtaining minimum objectives. In general, one of these constraints becomes binding. Few transportation problems (TPs) have been formulated with the restriction on vehicle volume capacity. Surface transport is one of the most powerful carbon emitters, which leads to global climate change. Thus, in addition to the usual travel cost and time minimization, carbon emission (CE) minimization and maximum vehicle space utilization should also be considered. A TP for damageable and incompatible items in a multi-objective green 4-dimensional environment is presented in this paper. The model is developed with four objectives: minimizing transportation cost, transportation time, vehicles’ vacant space, and carbon emission amount. The model is solved by six multi-objective optimization methods, and their results are compared. A multi-criteria decision-making method, “MetaRanking,” is used to compare the results of the different multi-objective methods. The model is illustrated with some numerical data using the Generalized Reduced Gradient method through Lingo 11.0. A real-life example is also presented. Several particular models are deduced. The numerical results demonstrate the importance of each objective. Pareto fronts represent that each objective is conflicting with the other.

An adaptive differential evolution algorithm to solve the multi-compartment vehicle routing problem: A case of cold chain transportation problem

This research paper introduces an adaptive differential evolution algorithm (ADE algorithm) designed to address the multi-compartment vehicle routing problem (MCVRP) for cold chain transportation of a case study of twentyeight customers in northeastern Thailand. The ADE algorithm aims to minimize the total cost, which includes both the expenses for traveling and using the vehicles. In general, this algorithm consists of four steps: (1) The first step is to generate the initial solution. (2) The second step is the mutation process. (3) The third step is the recombination process, and the final step is the selection process. To improve the original DE algorithm, the proposed algorithm increases the number of mutation equations from one to four. Comparing the outcomes of the proposed ADE algorithm with those of LINGO software and the original DE based on the numerical examples In the case of small-sized problems, both the proposed ADE algorithm and other methods produce identical results that align with the global optimal solution. Conversely, for larger-sized problems, it is demonstrated that the proposed ADE algorithm effectively solves the MCVRP in this case. The proposed ADE algorithm is more efficient than Lingo software and the original DE, respectively, in terms of total cost. The proposed ADE algorithm, adapted from the original, proves advantageous for solving MCVRPs with large datasets due to its simplicity and effectiveness. This research contributes to advancing cold chain logistics with a practical solution for optimizing routing in multi-compartment vehicles.

SOLVE THE TRANSPORTATION PROBLEM OF TRAPEZOIDAL FUZZY NUMBERS USING RUSSELL’S APPROXIMATION METHOD

Fuzzy set theory has been applied in many fields such as management, engineering, theory of matrices and so on. In this paper, some elementary operations on proposed trapezoidal fuzzy numbers (TrFNs) are defined and also have been defined some operations on trapezoidal fuzzy matrices(TrFMs).Using Russell’s approximation method to solve the Fuzzy transportation problem of Trapezoidal Fuzzy numbers.

Optimization of Chicken Egg Distribution Cost Using Revised ASM Method (Case Study: Breeding Industry)

PT. IA is a company engaged in the manufacture of animal feed, producing chicken eggs and broiler chicken farm. The problems at PT. IA is amount of distribution costs incurred by the company, so the method needed to optimize disttribution costs. The purpose of this research is to determine the optimal distribution costs of chicken eggs, compare the distribution cost of chicken eggs before and after optimization, and compare the ASM method with Stepping Stone method. The method use to solve the probelum is using ASM method. ASM method is one of a method that can use to find the optimal solution without have to find the starting solution to minimize costs. Allocation product with ASM Method is done from the smallest index and the largest amount of supply, until all demand is met and supply out of stock. Based on the research, it shown the revision of ASM method is not necessarly able to provide the optimal solution directly to unbalanced transportation problems or the accurance of additional activities. The minimum total cost with ASM method is Rp. 586.800.000, while after test the optimization using Stepping Stone method the result is Rp. 585.300.000. The difference cost before and after optimization using the revised ASM method is Rp. 93.300.000 or decrease of 13.7%.

Pengaruh Kualitas Layanan Dan Harga Terhadap Loyalitas Pelanggan Melalui Kepuasan Pelanggan (Studi Pada Pelanggan Grab Bike Di Kalangan Generasi Z Surabaya)

Transportation is needed to ensure the organization of mobility of people or goods. One of the public transportation that is often used is the motorcycle vehicle, which is often referred to as ojek. But in reality this service still has many shortcomings that its customers complain about, such as unsuitable service and prices. In resolving complaints and transportation problems, transportation service providers are needed who can meet and resolve these problems. Grab is an online transportation application widely used in Indonesia. This study is a study of a quantitative type. This study used the Gen Z population in the Surabaya area who are Grab Bike customers who have used the service more than twice, with the amount of data known through BPS being 877,427 data. In determining the sample is used purposive sampling.Information is collected by distributing a questionnaire to the respondents, that is, giving 20 questions. From the research we have obtained that the quality of service affects customer loyalty, price affects customer loyalty, customer satisfaction affects customer loyalty, quality of service affects customer loyalty, price affects customer loyalty, quality of service affects customer loyalty through customer satisfaction, and price affects customer loyalty through customer satisfaction.

Maximum modulus zero-suffix method for finding an optimal solution to fuzzy transportation problems

Maximum modulus zero-suffix method for finding an optimal solution to fuzzy transportation problems

How do Agri-Startups Perceive the COVID-19 Pandemic: A Thematic Analysis

This study has primarily featured the challenges faced by the Agri-Startups during the pandemic and their coping strategies. The theoretical framework was established based on the theory of dynamic capability, expectancy theory, and the Janusian thinking approach. Nvivo-13 software was used to do thematic analysis, which involved classifying the data by codes. Subsequently, themes were identified to better understand the factors that impact Agri-startups during COVID-19. Transportation and communication problems, a lack of cash, low sales, changes in customer habits and needs, a lack of workers, and competition from new businesses were all problems. As a way to deal with the situation, they used new digital technologies, cut down on operational and administrative costs, stopped doing business during the lockdown time, and put a few investment choices on hold. The study strongly suggests that Agri-Startups use the same tools and policies as other businesses in order to stay in business.

A Study on the Problem of Starting and Depositing of Ming Dynasty Fields Based on the Perspective of HGIS

The origination, transportation, and retention of field levies are the core contents of the Ming Dynasty financial research, and in the past, the academic community's attention to the origination, transportation, and retention problems only stayed in the discussion of the amount of field levies and the institutional level. With the use of digital humanities and historical geographic information systems in historical research, the spatial information implied in the Ming dynasty field levies can also be presented in the study. The book "Wanli Accounting Record" compiled by the Ministry of Revenue during the Wanli period contains the collection and storage of field levies at all levels of provinces and counties in the Ming Dynasty, and the historical documents are converted into data and then the GIS software is utilized to present them in a hierarchical manner on a nationwide scale. The results of the hierarchical presentation are further analyzed by using spatial analysis software to analyze the spatial relationship between the field levies in each state and county in the Ming Dynasty.