scholarly journals New model of flying sidekick traveling salesman problem with a charge-station

2017 ◽  
Author(s):  
◽  
Pengkun Zhou
Keyword(s):  
Transportation Cost ◽  
Traveling Salesman ◽  
Delivery Problem ◽  
Time Consumption ◽  
Consumption Data ◽  
Last Mile ◽  
A Charge ◽  
Last Mile Delivery ◽  
Future Work ◽  
First Time

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.

Leveraging Socially Networked Mobile ICT Platforms for the Last-Mile Delivery Problem

2012 ◽  
Vol 46 (17) ◽  
pp. 9481-9490 ◽  
Author(s):  
Kyo Suh ◽  
Timothy Smith ◽  
Michelle Linhoff
Keyword(s):  
Delivery Problem ◽  
Last Mile ◽  
Last Mile Delivery ◽  
Mobile Ict

A traveling salesman problem with time windows for the last mile delivery in online shopping

2019 ◽  
Vol 58 (16) ◽  
pp. 5077-5088 ◽  
Author(s):  
Li Jiang ◽  
Mohamed Dhiaf ◽  
Junfeng Dong ◽  
Changyong Liang ◽  
Shuping Zhao
Keyword(s):  
Traveling Salesman Problem ◽  
Online Shopping ◽  
Time Windows ◽  
Traveling Salesman ◽  
Last Mile ◽  
Last Mile Delivery

Scheduling the covering delivery problem in last mile delivery

2021 ◽  
pp. 115894
Author(s):  
Li Jiang ◽  
Xiaoning Zang ◽  
Ibrahim I.Y. Alghoul ◽  
Xiang Fang ◽  
Junfeng Dong ◽  
...  
Keyword(s):  
Delivery Problem ◽  
Last Mile ◽  
Last Mile Delivery

scholarly journals Crowd Sourcing Dynamic Pickup & Delivery Problem considering Task Buffering and Drivers’ Rejection -Application of Multi-agent Reinforcement Learning-

2021 ◽  
Vol 18 ◽  
pp. 636-645
Author(s):  
Junyi Mo ◽  
Shunichi Ohmori
Keyword(s):  
Reinforcement Learning ◽  
Numerical Experiments ◽  
Delivery Time ◽  
Crowd Sourcing ◽  
Employment Opportunities ◽  
Matching Algorithm ◽  
Delivery Problem ◽  
Last Mile ◽  
Multi Agent ◽  
Last Mile Delivery

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

scholarly journals The Scope for Pavement Porters: Addressing the Challenges of Last-Mile Parcel Delivery in London

2018 ◽  
Vol 2672 (9) ◽  
pp. 184-193 ◽  
Author(s):  
Julian Allen ◽  
Tolga Bektas ◽  
Tom Cherrett ◽  
Oliver Bates ◽  
Adrian Friday ◽  
...  
Keyword(s):  
Urban Areas ◽  
Urban Centers ◽  
Delivery Problem ◽  
Last Mile ◽  
Road Space ◽  
Total Vehicle ◽  
Vehicle Activity ◽  
The Uk ◽  
Last Mile Delivery ◽  
Alternative Solutions

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.

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 ◽  
...  
Keyword(s):  
Distribution System ◽  
Urban Areas ◽  
Valid Inequalities ◽  
Branch And Cut ◽  
Computational Results ◽  
Delivery Problem ◽  
Last Mile ◽  
Optimisation Model ◽  
Last Mile Delivery

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.

Sign in / Sign up

Export Citation Format

Share Document