Dynamic management of loading bays for energy efficient urban freight deliveries

Letnik, Tomislav; Farina, Alessandro; Mencinger, Matej; Lupi, Marino; Božičnik, Stane

doi:10.1016/j.energy.2018.06.125

Cited by 44 publications

(25 citation statements)

References 36 publications

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“…Logistics and supply chain design focuses on the design of various supply chain aspects, such as fulfillment [12], distribution [127], hub and spoke systems [124], last mile logistics models [3], and logistics challenges related to the distribution system [130]. Urban freight terminals include urban distribution centers [138], urban consolidation centers [135], mobile depots [132], and loading bays [136]. Urban planning focuses on articles related to urban planning, particularly the impact of urban freight activity [143] and parking practices [145].…”

Section: Themes In Last Mile Logisticsmentioning

confidence: 99%

Framework of Last Mile Logistics Research: A Systematic Review of the Literature

2019

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Coincident with the rapid growth of omni-channel retailing, growing urbanization, changing consumer behavior, and increasing focus on sustainability, academic interest in the area of last mile logistics has significantly increased. The growth in academic publications has been tremendous, with three out of four articles appearing within the past five years. The influx of research spans multiple disciplines and various methodologies, underlining the complexity and fragmentation of last mile logistics research, which leads to a lack of unity in the understanding of the concept. We provide a systematic review and classification of the literature to provide a more coherent view of last mile logistics research. The review covers 155 peer-reviewed journal publications focusing on last mile logistics. Findings demonstrate that the literature embraces a diversity of aspects and facets that are classified into five themes: emerging trends and technologies, operational optimization, supply chain structures, performance measurement, and policy. Further, we propose a framework of last mile logistics literature that comprises five components and their interrelationships, namely, last mile logistics, last mile distribution, last mile fulfillment, last mile transport, and last mile delivery. The results provide a foundation for further development of this research area by proposing avenues for future research.

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Section: Themes In Last Mile Logisticsmentioning

confidence: 99%

Framework of Last Mile Logistics Research: A Systematic Review of the Literature

2019

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“…If the second approximation method is used (the algorithm chooses among all the acceptable loading baysnot only the closest one): the average walking distance is around 300 meters, but vehicles almost never wait outside the city before performing the deliveries. For the more detailed description of the model and results please see [7].…”

Section: Achieved Resultsmentioning

confidence: 99%

“…The algorithm is shortly presented in the sequel (see Figure 1). A more detailed elaboration and explanation of the algorithm and model developed in MATLAB can be found in Letnik et al [7]. Generally, last mile delivery problem is divided into two sub-problems: (1) the delivery of goods from outside the city to the LB; and (2) the delivery of goods from the LB to the customer.…”

Section: On Algorithm For Dynamic Management Of Urban Freight Deliveriesmentioning

confidence: 99%

“…In case customers are not accessible by freight delivery vehicles, loading bays (LBs) are needed for transhipment of parcels and parking of delivery vehicles near customers (mainly on the border of pedestrian zone) for the time being of last mile delivery operations. Last mile delivery is predominantly done on foot or by trolley [7]. Urban areas are in general confronted with scattered LBs and many of them are often occupied (sometimes by other delivery vehicles, but in most cases illegally from individual users) [8,9].…”

Section: Introductionmentioning

confidence: 99%

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Dynamic assignment of loading bays for efficient urban last mile deliveries

Letnik¹,

Mencinger²,

Božičnik³

2018

Common Foundations 2018 - uniSTem: 6th Congress of Young Researchers in the Field of Civil Engineering and Related Sciences

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Urban freight deliveries are facing problems of limited accessibility to customers located in the city centre. Due to lack of loading bays, freight vehicles are forced to double parking or circulating in the city centre to find an available loading bay. To solve that problem a model for dynamic management of urban last mile deliveries has been developed. The optimisation is based on fuzzy c-means clustering of customers to dynamically assign the best possible loading bay in combination with a two-echelon routing algorithm. The model is tested on the actual data of deliveries to the historical city centre of Lucca, Italy. Results of simulations have proven significant savings of the total travel time and distance in comparison to the existing situation. The suggested approach is highly flexible and allows adaptation to any city access restriction scheme.

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“…Access to urban areas (especially to historical city centres or some specific parts of the city) is often prohibited or allowed only at certain time of the day and/ or only with small and environmentally friendly delivery vehicles (freight bikes, light commercial vehicles, electric delivery vehicles). When direct delivery to customers is not possible a Loading Bay (LB) is needed for transhipment of goods and parking of delivery vehicles during the final (last mile) delivery operations Guastaroba et al 2016;Letnik et al 2018).…”

Section: Introductionmentioning

confidence: 99%

On Fundamental Principles of the Optimal Number and Location of Loading Bays in Urban Areas

et al. 2019

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The paper is dealing with the problem of finding the optimal number and location of Loading Bays (LBs) for efficient urban last mile deliveries. To solve the problem a multi-parametric model of the idealized urban area is introduced and applied to various instances of a rectangular urban grid structured zones. Multi-parametric approach is used to assess statistically the most relevant number and location of LBs. Computational and graphical results of the idealized model exhibit geometric patterns showing that the optimal Number of LBs (#LB) naturally tends to perfect squares. Moreover, even in case of generalized instances, at a selected number of LBs their distribution is not random but follows specific laws. The optimality is closely related to the prefixed (maximal) walking distance dmax, from the LB to the customer. Based on various simulations the existence and robustness of a descending convex dependence dmax = (#LB) is proven. The results might serve as a decision-making tool to determine the optimal number and location of LBs for any real-life city centre.

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Dynamic management of loading bays for energy efficient urban freight deliveries

Cited by 44 publications

References 36 publications

Framework of Last Mile Logistics Research: A Systematic Review of the Literature

Framework of Last Mile Logistics Research: A Systematic Review of the Literature

Dynamic assignment of loading bays for efficient urban last mile deliveries

On Fundamental Principles of the Optimal Number and Location of Loading Bays in Urban Areas

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