Sustainable generalized refueling station location problem under uncertainty

Tafakkori, Keivan; Bozorgi-Amiri, Ali; Yousefi-Babadi, Abolghasem

doi:10.1016/j.scs.2020.102497

Cited by 12 publications

(2 citation statements)

References 74 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The model is used to run multiple simulations of the transport system to consider the overall influence of random parameters on the simulations' results and to evaluate statistically significant values of the efficiency criteria. The authors of the study [27] use the robust optimization approach to alleviate the impact of uncertainty on obtained solutions.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The most widely used criterion is total costs: In the research [5], the e-commerce distribution system based on cargo bikes and delivery points is assessed with total operational and external costs, the authors of the paper [9] propose to select cost-minimizing locations of parcel lockers for goods deliveries by cargo bikes, the study [15] uses total costs as the objective function to substantiate the location of recharging stations for electrical vehicles. However, some recently developed approaches define facility locations considering environmental pollution together with operational costs: The model developed in [10] uses the total costs and the environmental impacts to assess alternative configurations of urban consolidation centers, while the study [27] considers the combination of total costs and parameters of environmental pollution to select locations of refueling stations.…”

Section: The Objective Function For the Hub Location Problemmentioning

confidence: 99%

See 1 more Smart Citation

Substantiation of Loading Hub Location for Electric Cargo Bikes Servicing City Areas with Restricted Traffic

Naumov

2021

Energies

View full text Add to dashboard Cite

Electric cargo bicycles have become a popular mode of transport for last-mile goods deliveries under conditions of restricted traffic in urban areas. The indispensable elements of the cargo bike delivery systems are loading hubs: they serve as intermediate points between vans and bikes ensuring loading, storage, and e-vehicle charging operations. The choice of the loading hub location is one of the basic problems to be solved when designing city logistics systems that presume the use of electric bicycles. The paper proposes an approach to justifying the location of a loading hub based on computer simulations of the delivery process in the closed urban area under the condition of stochastic demand for transport services. The developed mathematical model considers consignees and loading hubs as vertices in the graph representing the transport network. A single request for transport services is described based on the set of numeric parameters, among which the most significant are the size of the consignment, its dimensions, and the time interval between the current and the previous requests for deliveries. The software implementation of the developed model in Python programming language was used to simulate the process of goods delivery by e-bikes for two cases—the synthetically generated rectangular network and the real-world case of the Old Town district in Krakow, Poland. The loading hub location was substantiated based on the simulation results from a set of alternative locations by using the minimum of the total transport work as the efficiency criterion. The obtained results differ from the loading hub locations chosen with the use of classical rectilinear and center-of-gravity methods to solve a simple facility location problem.

show abstract

Section: Literature Reviewmentioning

confidence: 99%