Transportation Planning Research Articles

Measuring integrated accessibility for sustainable mobility: a fuzzy set approach case study

AbstractSustainable transportation is vital to climate justice and social equity. Despite the efforts to achieve sustainability, there is still a lack of adequate measurement that integrates land use and transportation systems, which can be barriers to planning implementation. With methodological improvements in fuzzy theory application, this study develops an integrated index to measure the sustainability of multimodal accessibility. We do so by defining a fuzziness degree based on the different trip purposes and modes of transportation with a case study in Isfahan, Iran. Sustainable accessibility indicators were developed for walking, biking, and public transportation to represent the performance of each transportation system, considering the integration with land-use patterns. We analyze transportation modes and the accessibility to five main urban activities, including employment opportunities, education, healthcare, shopping, and recreation services, based on the travel distances, followed by a statistical integration method with Principal Components Analysis (PCA) for each travel mode. The outcome provides insights for urban planners and transportation planners to effectively evaluate the degree of integration between transportation and land-use systems and contribute to enhancing sustainable accessibility.

Lived expertise of the structurally disadvantaged: towards a more just participatory transport planning process

In response to the negative effects of the car-dominated transport sector, especially in urban areas, and wider attempts to tackle the climate crisis, cities are reallocating car-dominated areas to promote active mobility, leisure and urban green space. These reallocations often take an experimental character and are accompanied by participation processes. Increased citizen participation results from both a paradigm shift in urban planning and a discourse shift towards mobility justice, emphasizing procedural and recognitional aspects of the transport transition. However, participatory planning processes themselves are conflict-ridden. They are criticised for favouring a loud, priviliged minority. Based on the need for diverse knowledge for mobility justice, including lived expertise, this study examines reasons for (non-) participation among structurally disadvantaged groups in transport planning, using Berlin’s Graefekiez neighbourhood as a case study. Focus groups were conducted with mobility-disabled people and women from a residential area with low socio-economic status. Our analysis revealed that non-participation was influenced by the feeling of being excluded and ignored. Simultaneously, the research format created was perceived as a welcoming space that better reflects the lived expertise of the neighbourhood and facilitates real exchange of perspectives. Based on this, recommendations are derived to improve participatory transport planning processes and the strengths of transdisciplinary projects.

An OpenStreetMap derived building classification dataset for the United States

Building classification is crucial for population estimation, traffic planning, urban planning, and emergency response applications. Although essential, such data is often not readily available. To alleviate this problem, this work presents a comprehensive dataset by providing residential/non-residential building classification covering the entire United States. We developed a dataset of building types based on building footprints and the available OpenStreetMap information. The dataset is validated using authoritative ground truth data for select counties in the U.S., which shows a high precision for non-residential building classification and a high recall for residential buildings. In addition to the building classifications, this dataset includes detailed information on the OpenStreetMap data used in the classification process. A major result of this work is the resulting dataset of classifying 67,705,475 buildings. We hope that this data is of value to the scientific community, including urban and transportation planners.

A study of short-term passenger flow forecasting for public transportation based on the time series method

Abstract. In order to solve the conflicts between the supply and demand of urban transport, improve the living standard of urban residents, raise the level of urbanization, and promote the sustainable socio-economic development of the whole city, it is necessary to increase the pace of urban transport construction, planning and management in China. And at the same time, its necessary to take various measures to regulate the structure of urban transport and guide urban transport to develop in the direction of taking public transport as the mainstay. The experience of the development of urban transportation in China and abroad also proves that prioritizing the development of public transportation is the fundamental way to solve the problem of urban transportation. Public transport passenger flow data is the basis for optimizing public transport operations and scheduling. Accurate passenger flow forecasts on public transport routes can effectively guide public transport operation decisions, formulate operation scheduling plans and effectively improve the operational efficiency of the public transport system. The following are some of the key factors that can be taken into consideration when making passenger flow forecasts. The main contribution of this article is to propose the use of data mining technology, use bus IC card data and bus GPS data to integrate and organize them, conduct correlation analysis on the data, and on this basis, obtain the main distribution characteristics of bus passenger flow, and provide short-term Passenger flow forecast provides relevant ideas.

Predicting Cyclist Speed in Urban Contexts: A Neural Network Approach

Bicycle use has become more important today, but more information and planning models are needed to implement bike lanes that encourage cycling. This study aimed to develop a methodology to predict the speed a cyclist can reach in an urban environment and to provide information for planning cycling infrastructure. The methodology consisted of obtaining GPS data on longitude, latitude, elevation, and time from a smartphone of two groups of cyclists to calculate the speeds and slopes through a model based on a recurrent short-term memory (LSTM) type neural network. The model was trained on 70% of the dataset, with the remaining 30% used for validation and varying training epochs (100, 200, 300, and 600). The effectiveness of recurrent neural networks in predicting the speed of a cyclist in an urban environment is shown with determination coefficients from 0.77 to 0.96. Average cyclist speeds ranged from 6.1 to 20.62 km/h. This provides a new methodology that offers valuable information for various applications in urban transportation and bicycle line planning. A limitation can be the variability in GPS device accuracy, which could affect speed measurements and the generalizability of the findings.

Low-Carbon Route Optimization Model for Multimodal Freight Transport Considering Value and Time Attributes

As the international community increasingly focuses on climate change, optimizing low-carbon transportation routes in the multimodal freight transport system has become a pressing issue. However, due to the variability in cargo properties and the influence of various factors on transportation route decisions, formulating a low-carbon and economical multimodal freight transport plan remains a significant challenge. To address the issue, this study considered cargoes with different attributes in terms of both value and time attributes. Triangular fuzzy numbers were employed to represent the uncertain demand for cargo, with confidence levels introduced for clarification. A low-carbon route decision optimization model for multimodal freight transport was established to minimize the combined transportation carbon emission and time costs. The catastrophe adaptive genetic algorithm, based on Monte Carlo sampling, was employed to solve the model using arithmetic examples. Finally, parameter sensitivity analysis revealed that adjustments to carbon tax values and changes in the proportion of electric trucks and green electricity supply had the most significant impact on the low-carbon route decision-making plan for multimodal freight transport. For low value-added and timeliness-strong cargo, a 60% increase in carbon tax value shifted the mode of transportation from road to railway. When the carbon tax increased by more than 140%, the transportation mode shifted from railway to waterway. Additionally, when the proportion of electric trucks and green electricity supply both exceeded 80%, the transportation mode between some city nodes shifted from railway to road. When these proportions increased beyond 90%, road transportation became the predominant mode.

Examining the health effects of public transport use on older adults: A systematic review

Background and aimPublic transport use has been linked to several health benefits in the general population and is crucial for older adults’ mobility, due to an age-related decline in physical and cognitive capacity and mobility, particularly the ability to use other modes of transport. The objective of this systematic review is to determine what is known about the physical and mental health outcomes of public transport use of older adults and to identify remaining gaps in the literature. MethodsFive electronic databases were searched in April 2023, and then updated in January 2024: Pubmed, Scopus, Web of Science, Ageline and Transport Research International Documentation (TRID). Included were studies that were in English, contained a measure of public transport use as exposure, and any health outcome, including mental or physical health, physical or cognitive function, morbidity, or mortality, among people aged ≥60 years. ResultsOf a total of 2247 unique records that were screened, the full text of 20 was assessed for eligibility and 11 were identified as eligible. Citation search identified two additional studies, amounting to a total of 13 included studies. Significant health outcomes described in assessed studies were decreased obesity and depressive symptoms, and to a lesser extent increased gait speed and cognitive function. ConclusionsInitial evidence suggests a positive impact of public transport use on obesity, depressive symptoms, gait and cognitive function, although available research was limited in context and methodology. Further research should focus on determining causality between public transport use and health, and be conducted in more diverse contexts. Transport and urban planners, as well as policymakers, should consider the implications of public transport on the health and independence of older adults.

Investigating the factors determining service quality in Bhopal’s multimodal public transport system: A factor analysis

Multimodal public transport systems are crucial for sustainable urban mobility in growing cities like India. This study investigates the factors determining service quality in Bhopal’s multimodal public transport system using factor analysis. A survey of 650 regular users was conducted to assess service quality perceptions. Exploratory factor analysis revealed six significant factors: integration (22.12 % of variance explained), reliability (14.30 %), comfort (9.38 %), safety (8.07 %), accessibility (6.85 %), and customer service (5.74 %). The factors demonstrated high internal consistency reliability (Cronbach’s alpha > 0.8). Satisfaction levels varied across factors, with accessibility and comfort receiving higher ratings than reliability. Demographic comparisons revealed significant differences based on gender and age. The findings provide insights into the critical factors shaping service quality perceptions and offer a framework for assessment. The results highlight the need for targeted interventions, particularly in areas with lower satisfaction levels. This research contributes to the literature on public transport service quality in developing cities and underscores the importance of considering passenger perspectives in multimodal transport planning and management. This research contributes to the growing body of literature on public transport service quality in developing cities and underscores the importance of considering passenger perspectives in the planning and management of multimodal transport systems.

Decision-making optimization for post-disaster restoration of multimodal transport networks in terms of resilience

IntroductionPublic health emergencies can have a ripple effect on the resilience of multimodal transport network, which will lead to problems such as route disruptions or blockages, route selection change and information transmission delay spreading to the whole network, further hindering the transportation planning and operational efficiency of the network. MethodsThis study constructs a multimodal transport route optimization model under uncertainty with the objective of the sum of transportation cost, transshipment cost, penalty cost and carbon emission cost. To enhance the computational efficiency of the model, a novel invasive weed optimization with memory and encoding value clustering capabilities is proposed. In addition, by fusing the Q-learning algorithm in reinforcement learning with the novel invasive weed algorithm, the action-value function table obtained from the training facilitates the selection of optimal routes. Based on empirical data, explore the sensitivity analysis of node disruptions, time windows, and fuzzy demand on route decision-making under public health emergencies. ResultsThe transport network is affected by public health emergencies, which makes the optimal route deviate from the expected goal, resulting in an increase in the total cost. The proportion of total cost is determined by the position of nodes in the network, with critical nodes suffering more losses than ordinary nodes. Reasonable setting of time windows and fuzzy demand intervals is an effective way to improve the resilience and transportation efficiency of multimodal transport network. ConclusionsThis study provides more applicable decision-making references for enterprises to prevent the risk of supply chain disruptions caused by public health emergencies.

Using Statewide Transportation Planning Model to Forecast Demand for Electric Vehicle Charging at Stations Along Intercity Highways

The availability of Charging Stations (CSs) with adequate capacity is critical for the growth in ownership and usage of Electric Vehicles (EVs). In the United States, the state Departments of Transportation (DOTs) are responsible for planning CSs along the Interstate, national, and state highways. While the state DOTs have their Statewide Transportation Planning Models (STPMs), most of these models do not represent EVs internally. The state DOTs can only rely on the existing STPMs to forecast the demand for EV charging at specific CS locations in a state’s highway network. This research proposes a methodology that utilizes an existing STPM, EV and non-EV vehicle registration data, and hourly traffic volumes at strategic counting stations to predict the hourly demand for EV charging (charging port occupancy) at proposed CSs. This approach first estimates the volume of all passenger cars that will pass the vicinity of a CS along intercity highways, and identifies the Traffic Analysis Zones (TAZs) of their trip origins. Based on the EV adoption rates of the TAZs, EV range, and EV owner’s charging behavior, the methodology forecasts the volume of EVs that pass the vicinity of a CS and the number of EVs that will stop at the CS to charge every hour of the day. An example problem demonstrated the application of the methodology in the State of Texas. It not only forecasted the hourly occupancy at CSs along three major corridors, but also demonstrated how to determine the capacities of the CSs. The challenges of using the existing STPM and their solutions are discussed. This proposed methodology enables the state DOTs to forecast the demand for EV charging and the capacities at the proposed CSs along intercity highways, thus allowing the DOTs to apply for federal funds to accelerate the deployment of the CSs. (298 words)

Modelling Severe Weather Impact on Traffic Mobility and Evaluating Cross-Regional Applicability to Functionally Distinct Segments in Cold Region Highway Networks

This study in Alberta, Canada, focuses on winter traffic modeling, crucial for transportation agencies in cold regions. By gathering data from six Weigh-in-motion (WIM) sites, models were developed and tested for three vehicle types. Notably, the research assessed the transferability of models between different highway segments, indicating successful transfer of coefficients to varied road functionalities. This suggests that agencies can optimize model structures for specific vehicle classes, enhancing usability without additional monitoring sites. Overall, the study highlights the feasibility of improving winter traffic models and their applicability across diverse road segments, benefiting transportation planning and management in cold climates.

ENVIRONMENTAL RISK ASSESSMENT OF TRANSPORTATION INFRASTRUCTURE DEVELOPMENT USING GIS IN LAGOS STATE

Transportation infrastructure development poses significant environmental risks, including habitat disruption, air and water pollution, and climate change. This study develops a GIS-based framework for ecological risk assessment of transportation infrastructure development. This research identifies high-risk areas and prioritizes mitigation measures by integrating spatial analysis, multi-criteria decision analysis, and expert consultations. The GIS-based approach evaluates environmental sensitivity, proximity to ecosystems, and potential hazards. Results provide valuable insights for sustainable transportation planning, policy-making, and ecological management. This study explored its application in solving Environmental Risk Assessment of Transportation Infrastructure Development GIS application in environmental Risk Assessment monitoring has mainly been divided into three aspects: water, soil, and atmosphere. Based on ArcGIS 10.1 software and ArcGIS 9.3.1 version, GIS has been applied in Transportation system monitoring and soil heavy metal concentration monitoring, respectively. A major function of planners is to promote the best use of a community's land and resources for different construction projects; especially critical are infrastructure projects on which economic development relies. Transportation projects typically involve both environmental and economic issues facing a community as it grows and changes. Considerations of sustainability, as well as the widespread use of collaborative planning, design, and construction, require tools that facilitate long-term impact analysis and easy communication among built-environment professionals. Environmental impact assessment (EIA) is instrumental in studying transportation project impacts, but it is a time-consuming process because of the large number of dependent and independent variables involved. A vulnerability grade map and road distribution map were produced, providing an overall vulnerability score for each of the three planning alternatives considered. A road alignment was indicated as the preferred corridor, which was further recommended for a project development and environmental (PD&E) study.

Optimizing Traveler Behavior Between MADINA and JEDDA Using UPPAAL Stratego: A Stochastic Priced Timed Games Approach

This study looks at how travelers move between MADINA and JEDDA, using the UPPAAL Stratego tool to tackle the complexities of urban mobility. As cities grow, effective transportation planning becomes more challenging. Travelers have three options: car, bus, and train. The choices for car and bus travel are impacted by traffic conditions, which can vary between heavy and light, affecting both travel time and cost. We propose a detailed mathematical model that captures all possible scenarios related to these travel options, incorporating the uncertainties of real life. This allows us to simulate different traffic situations. By using UPPAAL Stratego, we evaluate three strategies: the Safe Strategy, which minimizes risk; the Fast Strategy, which aims to reduce travel time; and the Fast and Safe Strategy, which seeks a balance between speed and safety. This paper starts with an introduction to the Stochastic Priced Timed Games approach, highlighting its relevance in modeling dynamic travel environments. We then provide an overview of UPPAAL Stratego, showcasing its abilities in generating, optimizing, and comparing strategies. Next, we outline our mathematical model, explaining the assumptions, parameters, and data sources we used. Our simulation results illustrate how each strategy performs under different conditions, shedding light on traveler preferences and behaviors. The findings underscore the significance of accounting for traffic variability in travel planning and offer important insights for urban transportation policies aimed at improving the traveler experience and optimizing resource use. Additionally, we emphasize the theoretical contributions of our model by demonstrating its applicability to real-world scenarios and its potential to inform future research in urban mobility optimization. Ultimately, this research adds to the growing knowledge of smart transportation systems, demonstrating how formal mathematical modeling can address complex real-world challenges and inform future urban mobility strategies.

Urban burden of disease estimation for policy making

Abstract Introduction The Urban Burden of Disease Estimation for Policy Making (UBDPolicy) project aims to estimate the health impacts resulting from urban and transport planning related exposures in nearly 1000 European cities. So far, quantitative burden of disease assessments have estimated premature mortality attributable to the environmental stressors of air pollution, noise, urban heat islands and lack of green space for the year 2015. Regular reporting and trend monitoring of the health impacts associated with urban environments is crucial for assessing the wider impacts of urban and transport planning. Methods For almost 1000 European cities, quantitative Health Impact Assessments (HIAs) will be conducted that employ the comparative risk assessment methodology. Baseline exposure levels of air pollution, noise, urban heat islands and green space will be estimated and preventable health impacts modelled using counterfactual exposure scenarios. Analysis will comprise two components: firstly, the 2018 HIA will incorporate multiple environmental exposures for that year, while the second component will monitor trends at three-yearly reporting intervals covering the years of 2015, 2018, 2021 and 2024. Results Results are intended to shape evidence-informed urban planning and policies throughout Europe. By ranking cities according to environmental exposures and health impacts, cities are encouraged to address challenges and learn from successful urban design and planning policies in other cities. Discussion HIAs serve as an effective tool for identifying the health impacts of current and future urban policies. The provision of burden of disease estimates will provide policy-makers and practitioners robust data for informed decision-making, while estimates over time will allow tracking of changes from implemented policies. To fully harness the potential of cities as key drivers of sustainable and healthy living, robust evidence must be at the forefront of this change. Key messages • A multitude of urban and transport planning pathways contribute toward the health of urban populations. • Compact city designs often promote health, however there are exceptions.

Assessing inequalities and inequities in Health Impact Assessment: a systematic review

Abstract Background Health Impact Assessment (HIA) procedures can include the assessment inequalities and inequities associated with the distribution of environmental health risks and benefits, attenuating the exacerbation of health disparities in this domain. However, prevailing approaches to tackle inequalities in accessing ecosystem services exhibit limitations. We explored how this kind of assessment in HIA procedures is documented within the international literature. Methods Following PRISMA Guidelines, we conducted a systematic review of scientific literature by searching in MEDLINE/PubMed, Scopus, and Embase databases up to 8 March 2024. Moreover, a grey literature analysis was conducted, examining the World Health Organization’s Institutional Repository for Information Sharing (IRIS) to identify guidance considering equity in HIA. Results Eight out of 158 documents identified on IRIS, using ‘health impact assessment’ as a filter, underscore the importance of integrating the equity domain into the HIA; of these, only 1 employs methodologies to actively consider it. Of the 806 literature studies analyzed, only 14 included used methods to evaluate inequalities and equity in HIA in various contexts, ranging from urban planning, such as green or redeveloped areas, and transport planning, to mining. Preliminary results show that in most studies, data were collected through surveys, focus group discussions, and peculiar “walks” with local experts. The predominant approaches in extant literature entail the use of socioeconomic status and health determinants as metrics for assessing equity and inequalities within HIA. Conclusions Our findings highlight a critical gap in integrating equity into HIA practices, with limited attention and methodological diversity observed across the analysed documents and studies. Strategies for probing and mitigating inequalities can be strengthen by engaging different stakeholders and the residing population. Key messages • There are few and highly heterogeneous methods for assessing inequality in HIA. • An effective and standardized strategy to asses inequality in HIA could involve stakeholders and the resident population.

A systematic review of health outcomes of public transport use by older adults

Abstract Background and Aim Public transport use has been linked to several health benefits in the general population, and is crucial for older adults’ mobility, due to an age-related decline in mobility, and particularly the ability to use other transport modes. The objective of this systematic review is to determine what is known about the physical and mental health outcomes of public transport use by older adults and to identify remaining gaps in the literature. Methods Five electronic databases were searched in April 2023, with an update in January 2024: Pubmed, Scopus, Web of Science, Ageline and Transport Research International Documentation (TRID). Included were studies that were in English, contained a measure of public transport use as exposure, and any health outcome, including mental or physical health, physical or cognitive function, morbidity, or mortality, among people aged ≥ 60 years. Results Of a total of 2247 unique records that were screened, the full text of 20 was assessed for eligibility and 11 were identified as eligible. Citation search identified two additional studies, amounting to a total of 13 included studies. Significant health outcomes described in assessed studies were decreased obesity and depressive symptoms, and to a lesser extent increased gait speed and cognitive function. Conclusions Initial evidence suggests a positive impact of public transport use on obesity, depressive symptoms, gait and cognitive function, although available research was limited in context and methodology. Further research should focus on determining causality between public transport use and health, and be conducted in more diverse contexts. Transport and urban planners, as well as policymakers, should consider the implications of public transport on the health and independence of older adults. Key messages • Public transport use is linked to reduced obesity and depression among older adults. Links with other health outcomes were reported in several studies, but evidence is scarce. • Current research is limited in terms of quantity, scope, and design. Future research should be conducted in wider contexts, encompass a broader range of health outcomes, and address reverse causality.

7.M. Round table: A new lens on loneliness: leveraging the built environment for social health

Abstract Loneliness is a global issue impacting a third of all adults, with young adults (15-25 years) disproportionately affected. Prolonged loneliness has serious consequences for mental and physical health and should be addressed as a matter of urgency. The built environment, where we live, work, and socialise, is increasingly recognised as a significant factor influencing loneliness. However, existing interventions often focus on older adults and neglect the role of the built environments in promoting connectedness across the life course. To bridge this gap, we need interdisciplinary collaboration to understand how our environments and communities can mitigate loneliness. This workshop will explore the critical intersection of place and loneliness interventions. The three panellists bring unique interdisciplinary expertise on loneliness ranging from policy to intervention implementation. These three talks (10min each) will set the stage for a dynamic discussion (30min): 1. Nina Goldman, commissioned by the World Health Organization to undertake a global overview of national loneliness policies, will present findings on how national strategies integrate place-based strategies across sectors such as housing, transportation, and urban planning. 2. Mathias Lasgaard, leading researcher on loneliness interventions, will present the innovative ‘More Together’ (MoTo) project - a multifaceted intervention addressing loneliness in both young and older adults within the Silkeborg Municipality, Denmark. This presentation will contextualize MoTo within the broader landscape of targeted loneliness interventions. 3. Eric Schoenmakers, advisor of the national loneliness action program in the Netherlands, will introduce the “I BELONG” project, an international network dedicated to understanding the relationship between public spaces, loneliness, and effective interventions for young adults in the Netherlands. Key messages • We aim to stimulate a paradigm shift in the way we address loneliness by moving beyond individual-centred solutions to develop a more holistic and community-based approach. • We need more interdisciplinary collaboration to understand how our environments and communities can mitigate loneliness. Speakers/Panelists Nina Goldman University of Manchester, Manchester, UK Mathias Lasgaard Defactum, Central Denmark Region, Aarhus, Denmark Eric Schoenmakers Fontys University of Applied Sciences, Eindhoven, Netherlands

A Procedure to Characterize Wood Pile Inventories at Roadside

Tracking roadside wood inventories is necessary for wood procurement. However, this operation is increasingly problematic due to the costs associated with reaching remote sites, labour shortage, and the methods providing limited information on the characteristics of the logs required for transport planning. To overcome these problems, an automated procedure has been developed in Arcmap to characterize individual wood pile inventories at roadside by using GPS points of forwarders, harvester production files, and the road network shape files. An inventory of the logs in the harvest area followed by a wood pile inventory at the roadside were made to evaluate how the procedure could trace logs from machine operating trail to predicted wood pile locations. The study was done at six harvest blocks in the Saguenay-Lac-Saint-Jean region in the province of Quebec, Canada. The procedure was not able to differentiate individual wood piles and aggregated several piles into predicted unloading areas. Results indicated a similarity index of 72% to manually inventoried wood piles. The similarity index could be explained by the low percentage of inventoried unpredicted wood pile lengths (3%) and a high percentage of overpredicted wood pile lengths (27%). The positive allocation rate could not be assessed at the level of the individual piles. On the other hand, the procedure properly allocated 96% of the logs to unloading areas. With the level of precision obtained, the developed procedure could be beneficial for managing the transportation of wood at the level of the road segment since it provides all the dendrometric data of the logs available for transport without requiring human intervention in the forest.

Optimizing Transportation Logistics for Cost Efficiency in a Garment Factory: A Linear Programming Approach Using LINDO

The garment industry in Bangladesh plays a pivotal role in the nation's economy, yet it faces significant challenges in optimizing transportation logistics to minimize costs and enhance efficiency. This paper uses linear programming techniques to negotiate the optimization of transportation logistics in a garment factory located in Gazipur, Bangladesh. The primary objective is to develop an optimized transportation plan that reduces costs while satisfying supply and demand constraints across multiple suppliers, production facilities, and distribution centers. The study formulates the transportation problem as a linear programming model and employs the simplex method to determine the optimal solution. LINDO software is utilized for model implementation and optimization. The model incorporates real data from the garment factory, including supply capacities, demand requirements, and transportation costs. Results from the LINDO optimization reveal a detailed transportation plan that minimizes total transportation costs, demonstrating significant cost savings compared to existing practices. The optimized plan improves operational efficiency and provides a robust decision-support tool for logistics managers. Sensitivity analysis is conducted to ensure the model's robustness under varying conditions. The methodologies and findings are scalable and adaptable to other industrial settings, offering valuable insights for enhancing logistical efficiency in the garment industry. The study also highlights potential areas for future research, including integrating environmental considerations and advanced optimization techniques. Through this research, the garment factory in Gazipur can achieve substantial cost reductions and operational improvements, enhancing its competitiveness in the global market.

A Study on Consistency and Its Actual Situation of Hub Setting by Urban Facility Location Plan and Regional Public Transportation Plan in Local City

A Study on Consistency and Its Actual Situation of Hub Setting by Urban Facility Location Plan and Regional Public Transportation Plan in Local City