City Logistics and Traffic Management: Modelling the Inner and Outer Urban Transport Flows in a Two-tiered System

Amaral, Rodrigo Rezende; Aghezzaf, El‐Houssaine

doi:10.1016/j.trpro.2015.03.023

Cited by 22 publications

(10 citation statements)

References 8 publications

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“…(9) is used to calculate criteria weights. r Z = IFWA λ = Nr (1) , r (2) , … , r ( ) O r Z = 1 * r (1) ⊕ 2 * r (2)…”

Section: If Codas Methodsmentioning

confidence: 99%

“…When the literature on urban logistics is examined, it is seen that the studies on this subject have intensified especially in recent years. Some of the studies are summarized as follows: Amaral and Aghezzaf [1] modeled traffic management in metropolitan areas and effective management of urban logistics strategies. In this study, the proposed optimization model and solution approaches for two-step system strategies are discussed.…”

Section: The Determination Of Strategies For Smart City Logisticsmentioning

confidence: 99%

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Prioritizing the Strategies to Enhance Smart City Logistics by Intuitionistic Fuzzy CODAS

Büyüközkan¹,

Göçer²

2019

Proceedings of the 2019 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and

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Accurate, well-timed, and efficient delivery operations is a must for supply chains and logistics providers' survival in a digitally enhanced business environment. Sustainability, mobility and livability related objectives of Smart City Logistics (SCL) address the reduction of trucks, congestion and pollution. In order to accomplish this objective, all stakeholders must work together. In addition to strong collaboration among cities, supply chains, and logistics providers, digital enablers can resolve traditional challenges in last-mile logistics for sustainable, mobile and livable cities. While the approaches to enhance SCL are in abundance, prioritizing suitable SCL strategies is a non-trivial task. In order to improve the SCL and evaluate the required strategies, this paper develops a decisionmaking model based on the Combinative Distance Based Assessment (CODAS) under Intuitionistic Fuzzy (IF) setting and carries out a pioneering study to determine and prioritize the required SCL strategies. It proposes a new approach to support the claim, and analyzes the SCL for the evaluation system. Then, selection criteria are established to define SCL strategies and to develop a method based on IF CODAS and the prospect theory. Finally, the advantages, disadvantages, as well as the limitations of the proposed method are discussed. This study is one of the pioneering research with empirical contributions to the existing vastly conceptual discussion.

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“…(9) is used to calculate criteria weights. r Z = IFWA λ = Nr (1) , r (2) , … , r ( ) O r Z = 1 * r (1) ⊕ 2 * r (2)…”

Section: If Codas Methodsmentioning

confidence: 99%

Section: The Determination Of Strategies For Smart City Logisticsmentioning

confidence: 99%

Prioritizing the Strategies to Enhance Smart City Logistics by Intuitionistic Fuzzy CODAS

Büyüközkan¹,

Göçer²

2019

Proceedings of the 2019 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and

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“…The use of AI solutions allowed designing smart logistics networks to consolidate traditional flows and reach higher economies scales [10]- [13]. In the literature, various decent approaches issues were widely proposed to smooth workflow in logistics contexts, such as route optimization [14], [15], warehouse and inventory management [16], traffic management [17], [18], packaging [19], and order tracking [7], [20].…”

Section: Literature Reviewmentioning

confidence: 99%

An Advanced LSTM Model for Optimal Scheduling in Smart Logistic Environment: E-Commerce Case

et al. 2021

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At present, most logistics systems, especially those dedicated to e-commerce, are based on artificial intelligence techniques to offer better services and increase outcomes. However, the variety and complexity of resource allocation, as well as task scheduling, denote that dynamic environments have still great challenges to overcome. So advanced models based on strong algorithms are required. Introducing advanced models into scheduling solutions is a promising way to enhance logistics efficiency. As a result, managing system resources remain essential to optimize task scheduling respecting the interactive impacts, and logistics systems requirements. In response to these challenges, in this paper, a powerful solution based on a Long short-term memory (LSTM) model is proposed to optimize resource allocation and to enhance task scheduling in a smart logistics framework. This paper explores some of the most important scheduling techniques and hypothesizes that deep learning techniques might be able to afford accurate approaches. The proposed smart logistics model lays on strong techniques, for that, experimental simulations were conducted using various project instances. The validation tests demonstrated competitive results with important performance rates i.e.: accuracy of 92,44% with a precision of 93,83, a recall of 95.18%, and F1score of 94,92%, and AUC of 88,17%. These results reveal the proof-of-principle for using LSTM models for effective and truthful logistics operations.

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“…(Mesjasz-Lech, 2016; Zhang et al , 2014). Green logistics relates with effectively and efficiently managing of urban freight transport with objectives of reducing environmental impacts, and optimum supply network productivity (Amaral and Aghezzaf, 2015). Various research works are available in which researchers have presented different methodologies for greening the supply chain and logistics activities in different countries.…”

Section: Literature Reviewmentioning

confidence: 99%

Pollution optimisation study of logistics in SMEs

Jaiswal

Samuel

Ganesh

2019

MEQ

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Purpose The purpose of this paper is to provide a solution for greening the supply chain of small and medium enterprises (SMEs) by minimising the vehicular pollutant emission in the logistics network. Design/methodology/approach The paper proposes an optimisation model to reduce the pollution emission in the logistics of supply chain network in SMEs. The work considers vehicle routing and selection of suppliers, manufacturers and assemblers according to the availability of various Bharat Stage Emission Standards type vehicles. Introsort sorting based selection algorithm is used to solve the problem. The proposed solution is implemented using C++ on an experimental data set for analysing the model. Findings The outcome of the study is a pollution optimisation model for logistics of SMEs. The finding shows an approach to reduce total vehicular pollution emission in the logistics network in meeting the demand. The model is tested over an experimental study, and the result findings show which supply chain entities, type of environmental standard vehicles and vehicle routes are selected for the specific demand. Research limitations/implications The proposed model is confined to pollution optimisation with limited parameters only and does not consider cost and other factors that can be included in future work. Practical implications The work can be used for limiting pollution in logistics system as the corporate social responsibility of enterprises. Originality/value Proposed work presents a sustainable and green solution for pollution control in logistics activities of the SMEs.

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City Logistics and Traffic Management: Modelling the Inner and Outer Urban Transport Flows in a Two-tiered System

Cited by 22 publications

References 8 publications

Prioritizing the Strategies to Enhance Smart City Logistics by Intuitionistic Fuzzy CODAS

Prioritizing the Strategies to Enhance Smart City Logistics by Intuitionistic Fuzzy CODAS

An Advanced LSTM Model for Optimal Scheduling in Smart Logistic Environment: E-Commerce Case

Pollution optimisation study of logistics in SMEs

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