scholarly journals Multimodal Automated Last-Mile Delivery System: Design and Application

2021 ◽  
Author(s):  
Farah Samouh

This thesis focuses on exploring the emerging automated technologies for last-mile on-demand food delivery as a new means of transportation to reduce congestion in urban areas. In order to achieve that 4 systems are designed and evaluated: Robot delivery system, drone delivery system and two hybrid delivery systems. Both hybrid systems are based on hub-spoke networks, Hybrid System 1.0 uses robots for phase one of the delivery and drones for phase two Hybrid System 2.0 uses drones for phase one and robots for phase two. To evaluate the efficiency of these systems, an in-house agent-based simulation model in MATLAB is developed for the City of Mississauga. 30 scenarios are tested differing in terms of demand and fleet size. The results show that Hybrid system 2.0 is the most efficient system of all four proposed due to the use of hub, customer waiting time and landing zones for drones.

2021 ◽  
Author(s):  
Farah Samouh

This thesis focuses on exploring the emerging automated technologies for last-mile on-demand food delivery as a new means of transportation to reduce congestion in urban areas. In order to achieve that 4 systems are designed and evaluated: Robot delivery system, drone delivery system and two hybrid delivery systems. Both hybrid systems are based on hub-spoke networks, Hybrid System 1.0 uses robots for phase one of the delivery and drones for phase two Hybrid System 2.0 uses drones for phase one and robots for phase two. To evaluate the efficiency of these systems, an in-house agent-based simulation model in MATLAB is developed for the City of Mississauga. 30 scenarios are tested differing in terms of demand and fleet size. The results show that Hybrid system 2.0 is the most efficient system of all four proposed due to the use of hub, customer waiting time and landing zones for drones.


Author(s):  
Christian Fikar ◽  
Manfred Gronalt

"Last-mile distribution in urban areas is challenged by congestion and restriction for motorized traffic. To support operations, this work investigate the impact of operating urban consolidation points and facilitating cargo-bikes for urban last-mile distribution. Motivated by sample setting originating from the food delivery industry, a decision support system combining agentbased simulation with heuristic optimization procedure is developed. It considers a logistics provider who performs the last-mile delivery for multiple competing restaurants in an urban area. Therefore, both demand and the availability of cargo-bikes, which are operated by freelancers, are subject to randomness. Computational experiments investigate the impact of the available amount of cargo-bike drivers as well as the number of operated consolidation points, highlighting the importance of facilitating simulation models to support operations in highly dynamic and uncertain settings."


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Btissam Moncef ◽  
Marlène Monnet Dupuy

PurposeThe purpose of this paper is to explore sustainability paradoxes in sharing economy initiatives by focusing on logistics management in last-mile logistics.Design/methodology/approachIn this exploratory study, a total of 10 case studies were conducted in three categories of companies: anti-waste platforms, food delivery platforms and bicycle delivery companies. Twenty-seven face-to-face interviews with founders and/or managers and contractors (couriers, logistics service providers or volunteers) were the primary source of data collection. The heterogeneity of the sample enabled the authors to build an understanding of sustainability paradoxes in the logistics of sharing economy initiatives.FindingsThe findings indicate how logistics management impacts the sustainability of sharing economy initiatives in last-mile delivery. The authors identify seven paradoxical tensions (five of them social) generated by the contradictions between the organizations' promised environmental and social values and the impacts of their operations.Research limitations/implicationsThis exploratory research is based on a qualitative study of 10 cases and 27 interviews from heterogeneous samples; further empirical research is needed to ensure generalization.Practical implicationsThe paper increases the understanding of environmental and social paradoxical tensions and awareness of logistics challenges.Social implicationsThe paper helps identify ways to reconcile promised values and impacts generated by sharing economy initiatives while managing last-mile delivery.Originality/valueThe results enrich the literature about the paradoxes in sharing economy initiatives by providing illustrations in last-mile logistics and exposing the underlying challenges for sharing economy logistics actors.


Kybernetes ◽  
2019 ◽  
Vol 49 (4) ◽  
pp. 1267-1284 ◽  
Author(s):  
Yandong He ◽  
Xu Wang ◽  
Fuli Zhou ◽  
Yun Lin

Purpose This paper aims to study the vehicle routing problem with dynamic customers considering dual service (including home delivery [HD] and customer pickup [CP]) in the last mile delivery in which three decisions have to be made: determine routes that lie along the HD points and CP facilities; optimize routes in real time, which mode is better between simultaneous dual service (SDS, HD points and CP facilities are served simultaneously by the same vehicle); and respective dual service (RDS, HD points and CP facilities are served by different vehicles)? Design/methodology/approach This paper establishes a mixed integer linear programing model for the dynamic vehicle routing problem considering simultaneous dual services (DVRP-SDS). To increase the practical usefulness and solve large instances, the authors designed a two-phase matheuristic including construction-improvement heuristics to solve the deterministic model and dynamic programing to adjust routes to dynamic customers. Findings The computational experiments show that the CP facilities offer greater flexibility for adjusting routes to dynamic customers and that the SDS delivery system outperforms the RDS delivery system in terms of cost and number of vehicles used. Practical implications The results provide managerial insights for express enterprises from the perspective of operation research to make decisions. Originality/value This paper is among the first papers to study the DVRP-SDS. Moreover, this paper guides the managers to select better delivery mode in the last mile delivery.


Author(s):  
Sameh M. Saad ◽  
Ramin Bahadori

"The Last mile delivery is known as one of the most costly and highest polluting stages within the food supply chain where food companies deliver the food products to the final consumers. As a new approach in this area, currently, a few food retailers offering pick up point service delivery using lockers. This paper provides a comprehensive comparison of the sustainability performance between home service delivery and picks up point service delivery using lockers. Hypothetical last mile food models for both approaches are developed. A Vehicle Route Problem with Time Window (VRPTW) is developed to minimise the CO2 emission and implemented using the simulated annealing algorithm which is programmed in MATLAB software. Supply Chain GURU Software is adapted to implement the Greenfield analysis to identify the optimal number and the location of the locker facilities through a Greenfield service constraint."


2020 ◽  
Vol 6 (159) ◽  
pp. 153-160
Author(s):  
A. Rossolov ◽  
O. Lobashov ◽  
A. Botsman

The paper presents the theoretical and experimental study results on construction sustainable urban supply chain, namely last mile delivery. Within the theoretical part we proposed to estimate the necessary number of local depots within the supply chain taking into account the direct and indirect impacts from a delivery system functioning. The indirect effect is presented with CO2 emissions. The conducted experiment has covered the pes-simistic and optimistic scenarios for delivery system states. Within the experiment along with demand attributes we assessed the range of vehicle carrying capacity from 0.5 to 2 tons. The obtained experimental results revealed the shift in necessary local depots number to guarantee the sustainable effect for delivery system and promote liveable state for the urban area.


Author(s):  
Jay R. Brown ◽  
Alfred L. Guiffrida

This paper presents a stochastic representation of the last mile problem that quantifies expected maintenance, regular labor, overtime labor, fuel, and carbon emission costs resulting from different delivery fleet options. The last mile delivery fleet planning model presented herein can be used in a decision framework to evaluate alternative delivery strategies involving fleet size and delivery frequency with information regarding cost, carbon emissions, service levels for available delivery hours, and payload capacity, as well as the transportation capacity needed to meet customer demand and lends itself well to performing what-if analyses.


Author(s):  
Sheng Liu ◽  
Long He ◽  
Zuo-Jun Max Shen

We study how delivery data can be applied to improve the on-time performance of last-mile delivery services. Motivated by the delivery operations and data of a food delivery service provider, we discuss a framework that integrates travel-time predictors with order-assignment optimization. Such integration enables us to capture the driver’s routing behavior in practice as the driver’s decision-making process is often unobservable or intricate to model. Focusing on the order-assignment problem as an example, we discuss the classes of tractable predictors and prediction models that are highly compatible with the existing stochastic and robust optimization tools. We further provide reformulations of the integrated models, which can be efficiently solved with the proposed branch-and-price algorithm. Moreover, we propose two simple heuristics for the multiperiod order-assignment problem, and they are built upon single-period solutions. Using the delivery data, our numerical experiments on a real-world application not only demonstrate the superior performance of our proposed order-assignment models with travel-time predictors, but also highlight the importance of learning behavioral aspects from operational data. We find that a large sample size does not necessarily compensate for the misspecification of the driver’s routing behavior. This paper was accepted by Hamid Nazerzadeh, big data analytics.


Author(s):  
Farah Samouh ◽  
Veronica Gluza ◽  
Shadi Djavadian ◽  
SeyedMehdi Meshkani ◽  
Bilal Farooq

Author(s):  
Julian Allen ◽  
Tolga Bektas ◽  
Tom Cherrett ◽  
Oliver Bates ◽  
Adrian Friday ◽  
...  

The UK parcel sector generated almost £9 billion in revenue in 2015, with growth expected to increase by 15.6% to 2019 and is characterized by many independent players competing in an “everyone-delivers-everywhere” culture leading to much replication of vehicle activity. With road space in urban centers being increasingly reallocated to pavement widening, and bus and cycle lanes, there is growing interest in alternative solutions to the last-mile delivery problem. We make three contributions in this paper: firstly, through empirical analysis using carrier operational datasets, we quantify the characteristics of last-mile parcel operations and demonstrate the reliance placed on walking by vehicle drivers with their vans being parked at the curbside for on average 60% of the total vehicle round time; secondly, we introduce the concept of “portering” where vans rendezvous with porters who operate within specific geographical “patches” to service consignees on foot, potentially saving 86% in driving distance on some rounds and 69% in time; finally, we highlight the wider practical issues and optimization challenges associated with operating driving and portering rounds in inner urban areas.


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