The two-echelon vehicle routing problem with covering options: City logistics with cargo bikes and parcel lockers

Enthoven, David L.J.U.; Jargalsaikhan, Bolor; Roodbergen, Kees Jan; Broek, Michiel A. J. uit het; Schrotenboer, Albert H.

doi:10.1016/j.cor.2020.104919

Cited by 102 publications

(48 citation statements)

References 26 publications

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“…The contemporary scientific literature describes the set of operational problems to be solved while designing the e-bike delivery system in an urban area: vehicle routing [9][10][11], synchronization of bikes with conventional vans [12], choice of vehicle type [10,13], vehicles scheduling [14,15], shaping the recharging strategy [15][16][17], etc. However, the most significant practical and theoretical issue when setting up the regional e-bike delivery system is the substantiation of the transshipment hub(s) parameters, including the type and location of the hub(s).…”

Section: Literature Reviewmentioning

confidence: 99%

“…To solve FLP, various approaches are used by scholars and practitioners. The most popular mathematical apparatus for substantiation of the loading hubs location is the mixed-integer linear programming [9,14,15,21,24], although the fuzzy-logic-based models are used as well [17,25]. Another direction for finding the solution of FLP is the simulationbased approaches [5,8,19,26]: The delivery and servicing processes are simulated for a set of alternative locations and the best option is being substantiated based on the simulation results.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Special scientific literature proposes various efficiency criteria for solving FLP. 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%

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

Naumov

2021

Energies

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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.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: The Objective Function For the Hub Location Problemmentioning

confidence: 99%

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

Naumov

2021

Energies

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“…However, very few articles cover a multi-echelon approach combined with heterogeneous vehicle fleets, including the use of ECBs, in the field of city logistics. In this context, Enthoven et al [33] present an example of a 2-echelon VRP with two delivery options. On the one hand, parcels are delivered in a van from a depot to parcel stations, from where customers can pick up their parcels themselves.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

“…Constraint (32) imposes that the van's load of a particular product type must not exceed the associated compartment's capacity. With (33), the tour length of a van can be restricted by parameter ∆ van (33). Constraints (34)-(37) secure the time-window compliance of the grocery lockers.…”

Section: Stage 3: Sp-vrpmpctwmentioning

confidence: 99%

Shortening the Last Mile in Urban Areas: Optimizing a Smart Logistics Concept for E-Grocery Operations

et al. 2020

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Urbanization, the corresponding road traffic, and increasing e-grocery markets require efficient and at the same time eco-friendly transport solutions. In contrast to traditional food procurement at local grocery stores, e-grocery, i.e., online ordered goods, are transported directly to end customers. We develop and discuss an optimization approach to assist the planning of e-grocery deliveries in smart cities introducing a new last mile concept for the urban food supply chain. To supply city dwellers with their ordered products, a network of refrigerated grocery lockers is optimized to temporarily store the corresponding goods within urban areas. Customers either collect their orders by themselves or the products are delivered with electric cargo bicycles (ECBs). We propose a multi-echelon optimization model that minimizes the overall costs while consecutively determining optimal grocery locker locations, van routes from a depot to opened lockers, and ECB routes from lockers to customers. With our approach, we present an advanced concept for grocery deliveries in urban areas to shorten last mile distances, enhancing sustainable transportation by avoiding road traffic and emissions. Therefore, the concept is described as a smart transport system.

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Cost‐optimal truck‐and‐robot routing for last‐mile delivery

2021

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During recent years, several companies have introduced small autonomous delivery robots and evidenced their technical applicability in field studies. However, a holistic planning framework for routing and utilizing these robots is still lacking. Current literature focuses mainly on logistical performance of delivery using autonomous robots, ignoring real world limitations, and does not assess the respective impact on total delivery costs. In contrast, this paper presents an approach to cost‐optimal routing of a truck‐and‐robot system for last‐mile deliveries with time windows, showing how to minimize the total costs of a delivery tour for a given number of available robots. Our solution algorithm is based on a combination of a neighborhood search with cost‐specific priority rules and search operators for the truck routing, while we provide and evaluate two alternatives to solve the robot scheduling subproblem: an exact and a heuristic approach. We show in numerical experiments that our approach is able to reduce last‐mile delivery costs significantly. Within a case study, the truck‐and‐robot concept reduces last‐mile costs by up to 68% compared to truck‐only delivery. Finally, we apply sensitivity analyses to provide managerial guidance on when truck‐and‐robot deliveries can efficiently be used in the delivery industry.

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The two-echelon vehicle routing problem with covering options: City logistics with cargo bikes and parcel lockers

Cited by 102 publications

References 26 publications

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

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

Shortening the Last Mile in Urban Areas: Optimizing a Smart Logistics Concept for E-Grocery Operations

Cost‐optimal truck‐and‐robot routing for last‐mile delivery

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