Supply chain micro-communities in urban areas

Viljoen, Nadia; Joubert, Johan W.

doi:10.1016/j.jtrangeo.2018.11.011

Cited by 12 publications

(4 citation statements)

References 44 publications

(64 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This model's advantage is to generate extensive freight transport observations (from both own account carriers as 3PL's). Using Global Positioning System (GPS) tracks of commercial vehicles and network theory concepts, this work (Viljoen and Joubert 2019) has examined the characteristics of micro-communities in the supply chain in three urban areas of South Africa. The proposed model could make it possible to deduce urban freight transport patterns from supply chain interaction.…”

Section: Agent Based Approachmentioning

confidence: 99%

On understanding the impacts of shared public transportation on urban traffic and road safety using an agent-based simulation with heterogeneous fleets: a case study of Casablanca city

et al. 2022

View full text Add to dashboard Cite

Simulation and computer modeling have a key role in understanding transportation systems. Focusing on the main system, real-time retrieval of outputs based on mutual interactions of the whole autonomous entities makes the agent-based simulation very promising. This paper deals with an agent-based simulation to investigate and evaluate the potential impacts of implementing Shared Public Transports (SPT) in urban areas. Such a system is intended to integrate the two flows of passengers and containerized freights in Public Transportation (PT) patterns towards more sustainable, efficient, and socially suitable mobility. The proposed model is coupled with a stochastic process in order to provide a range of real-world data of Casablanca city (Morocco) based on institutional surveys. In this respect, two urban transportation systems of freight are tested: (1) the conventional transportation system, (2) the SPT system with heterogeneous fleets. In an effort to sustain efficient and safe movements, this paper examines SPT performances according to a set of key evaluation metrics. Results show that PT stopping remains the most relevant factor when evaluating metrics of the number of waiting containers and waiting time of demand by rates of 82.440% and 62.580%, respectively. Such a waiting containers metric is significantly affected by the volume of demand to transport per time slot by a rate of 78.140%. Under SPT, traffic congestion is the main factor to consider in managing PT with a rate of 65.690% in order to reduce potential accidents. However, demand volume could increase the on-street illegal parking metric by 90.070%. More details are provided below.

show abstract

Section: Agent Based Approachmentioning

confidence: 99%

On understanding the impacts of shared public transportation on urban traffic and road safety using an agent-based simulation with heterogeneous fleets: a case study of Casablanca city

et al. 2022

View full text Add to dashboard Cite

show abstract

“…Some researchers focus on topological growth to understand how transportation networks evolve through observing the changes in connectivity indices, such as alpha, beta, gamma, and centrality metrics (Casali and Heinimann 2019;Cats 2017;Strano et al 2012), while others focus on the efficiency of transport networks (Brussel et al 2019). Specifically, transport systems benefit from the graph theory-driven approach for quantitatively analyzing road network characteristics (Barthélemy 2011), robustness (Casali and Heinimann 2020;He et al 2021), and identifying communities and groups (Viljoen and Joubert 2019).…”

Section: Introductionmentioning

confidence: 99%

Assessing the evolution of educational accessibility with self-avoiding random walk: insights from Helsinki

Aydin,

Yigitbasi,

Casali

et al. 2023

Appl Netw Sci

View full text Add to dashboard Cite

Rapid urbanization has posed challenges to accessibility to critical services that require in-depth analysis. Complex networks theory has been used to evaluate the evolution of network topologies or the overall accessibility of transportation systems. However, topological metrics to explain the temporal changes in accessibility levels do not fully capture the dynamics and implications of accessibility to specific critical services. In this study, we address this gap and investigate the opportunities of using a self-avoiding random walk (SARW) algorithm to evaluate and explain the evolution of spatial accessibility to education facilities. We used hotspot analysis to understand the temporal changes and investigated changes in hot and cold spots over time. Furthermore, we explored the relationship between the network indicators and the SARW-based accessibility metric. We illustrated this method in a case study from Helsinki, where large-scale open data spanning from 1991 to 2016 is available. Our findings indicate that the SARW-based metric delivers more detailed node-level results than the traditional isochrone-based metric. The latter generates accessibility zones where accessibility is assumed to be uniform, while the SARW metric captures the dynamic nature of educational facility accessibility more accurately. The developed methodology helps to identify the impacts on the historical development of accessibility and can be applied to investigate accessibility to other critical services.

show abstract

“…The global epidemic of COVID-19 has had a serious impact on urban livelihoods. Urban supermarket chains are essential for the supply of urban goods in a social governance environment when policies are implemented to prevent and control the epidemic ( Ihle, Bar-Nahum & Jongeneel, 2020 ; Viljoen & Joubert, 2019 ). The supply forecasting and profiling of urban supermarket chains play an indispensable role in social governance.…”

Section: Introductionmentioning

confidence: 99%

Supply forecasting and profiling of urban supermarket chains based on tensor quantization exponential regression for social governance

Zhou

Lin

et al. 2022

PeerJ Computer Science

View full text Add to dashboard Cite

Background During the COVID-19 pandemic, the accurate forecasting and profiling of the supply of fresh commodities in urban supermarket chains may help the city government make better economic decisions, support activities of daily living, and optimize transportation to support social governance. In urban supermarket chains, the large variety of fresh commodities and the short shelf life of fresh commodities lead to the poor performance of the traditional fresh commodity supply forecasting algorithm. Methods Unlike the classic method of forecasting a single type of fresh commodity, we proposed a third-order exponential regression algorithm incorporating the block Hankle tensor. First, a multi-way delay embedding transform was used to fuse multiple fresh commodities sales to a Hankle tensor, for aggregating the correlation and mutual information of the whole category of fresh commodities. Second, high-order orthogonal iterations were performed for tensor decomposition, which effectively extracted the high-dimensional features of multiple related fresh commodities sales time series. Finally, a tensor quantization third-order exponential regression algorithm was employed to simultaneously predict the sales of multiple correlated fresh produce items. Results The experiment result showed that the provided tensor quantization exponential regression method reduced the normalized root mean square error by 24% and the symmetric mean absolute percentage error by 22%, compared with the state-of-the-art approaches.

show abstract

Supply chain micro-communities in urban areas

Cited by 12 publications

References 44 publications

On understanding the impacts of shared public transportation on urban traffic and road safety using an agent-based simulation with heterogeneous fleets: a case study of Casablanca city

On understanding the impacts of shared public transportation on urban traffic and road safety using an agent-based simulation with heterogeneous fleets: a case study of Casablanca city

Assessing the evolution of educational accessibility with self-avoiding random walk: insights from Helsinki

Supply forecasting and profiling of urban supermarket chains based on tensor quantization exponential regression for social governance

Contact Info

Product

Resources

About