scholarly journals Optimised solutions to the last-mile delivery problem in London using a combination of walking and driving

2020 ◽  
Vol 295 (2) ◽  
pp. 645-693
Author(s):  
Antonio Martinez-Sykora ◽  
Fraser McLeod ◽  
Carlos Lamas-Fernandez ◽  
Tolga Bektaş ◽  
Tom Cherrett ◽  
...  

AbstractInspired by actual parcel delivery operations in London, this paper describes a two-echelon distribution system that combines the use of driving and walking as part of last-mile deliveries in urban areas for a single driver. The paper presents an optimisation model that explicitly treats and integrates the driving and walking elements, and describes a branch-and-cut algorithm that uses new valid inequalities specifically tailored for the problem at hand. Computational results based on real instances obtained from a courier operating in London are presented to show the performance of the algorithm.

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.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sayan Chakraborty ◽  
Kalpit Darbhe ◽  
Sarada Sarmah

Purpose In the modern era of e-grocery, attended home delivery (AHD) has been identified as a crucial part of the last-mile delivery problem. This paper aims to deal with a real-life last-mile-delivery problem in the context of the Indian public distribution system (PDS). The authors identified two different environments for the said AHD problem and proposed two different approaches to address the issue under these problem settings. Design/methodology/approach In this study, the authors first consider the problem in a static environment and propose an iterated local search (ILS) integrated with an adaptive large neighborhood search (ALNS) meta-heuristic algorithm to obtain a routing solution. Thereafter, they extend the study in a dynamic environment where new delivery requests occur dynamically and propose a heuristic algorithm to solve the problem. For the dynamic case, multiple scenarios for the occurrence of delivery requests are considered to determine decisions regarding the opportunity to include a new request into the current solution. Findings By computational experiments, the authors show that the proposed approach performs significantly well for large size problem instances. They demonstrate the differences and advantages of the dynamic problem setting through a set of different scenarios. Also, they present a comparative analysis to show the benefits of adopting the algorithm in dynamic routing scenarios. Research limitations/implications Future research may extend the scope of this study by incorporating stochastic delivery failure probabilities and customer behavior affecting the delivery response. Also, the present study does not take inventory policies at the depot into consideration. It will be of interest to see how the system performs under the uncertainty of supply from the depot. Despite the limitations, the authors believe that this study provides food for thought and encouragements for practitioners. Practical implications This study shows the benefits of adopting an AHD problem in a dynamic setting in terms of customer service as compared to a traditional static environment. The authors clearly demonstrate the differences and advantages of the dynamic problem setting through a set of different scenario analysis. Social implications This paper investigates a real-life AHD problem faced by the Department of Food, Supply and Consumer Affairs, India. The findings of this study will be of particular interest to the policy-makers to build a more robust PDS in India. Originality/value The study is unique and highly relevant for real-world applications and can help build a more robust AHD system. Also, the proposed solution approaches to aid the problem in both static and dynamic routing scenarios will be of particular interest to practitioners.


2012 ◽  
Vol 46 (17) ◽  
pp. 9481-9490 ◽  
Author(s):  
Kyo Suh ◽  
Timothy Smith ◽  
Michelle Linhoff

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 ◽  
pp. 115894
Author(s):  
Li Jiang ◽  
Xiaoning Zang ◽  
Ibrahim I.Y. Alghoul ◽  
Xiang Fang ◽  
Junfeng Dong ◽  
...  

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."


2017 ◽  
Author(s):  
◽  
Pengkun Zhou

Cooperation between a truck and a drone for last-mile delivery has been viewed as a way to help make more efficient ways of delivery of packages because of the great advantage of drones delivery. This problem was described and formulated a as FSTSP by Maurry and Chu. Because of the weakness concerning drones' batteries lifespan, this paper proposed a new delivery scenario in which a charge-station will be applied in the truck-drone delivery network to increase the performance of the last-mile delivery. This new delivery problem is formulated for the first time in this thesis as a multi-objective problem. The purpose of this is to address both transportation cost and total time consumption. Data analysis is conducted to explore the relation between factors and the overall objective. The analysis shows that a charge-station will significantly increase the performance of the last-mile delivery. Lastly, future work is discussed that will enhance the model even more and possibly lead to better ways to use drones for delivery.


2021 ◽  
Vol 18 ◽  
pp. 636-645
Author(s):  
Junyi Mo ◽  
Shunichi Ohmori

In the last decade, dynamic and pickup delivery problem with crowd sourcing has been focused on as a means of securing employment opportunities in the field of last mile delivery. However, only a few studies consider both the driver's refusal right and the buffering strategy. This paper aims at improving the performance involving both of the above. We propose a driver-task matching algorithm that complies with the delivery time constraints using multi-agent reinforcement learning. Numerical experiments on the model show that the proposed MARL method could be more effective than the FIFO and the RANK allocation methods


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