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

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

scholarly journals A Crowdsourcing Approach for Sustainable Last Mile Delivery

2018 ◽  
Vol 10 (12) ◽  
pp. 4563 ◽  
Author(s):  
Adriana Giret ◽  
Carlos Carrascosa ◽  
Vicente Julian ◽  
Miguel Rebollo ◽  
Vicente Botti
Keyword(s):  
Complex Network ◽  
Sustainable Transportation ◽  
Last Mile ◽  
Delivery Routes ◽  
Private Transportation ◽  
Multi Agent ◽  
High Reduction ◽  
Intelligent Approach ◽  
Last Mile Delivery ◽  
The City

Sustainable transportation is one of the major concerns in cities. This concern involves all type of movements motivated by different goals (mobility of citizens, transportation of goods and parcels, etc.). The main goal of this work is to provide an intelligent approach for Sustainable Last Mile Delivery, by reducing (or even deleting) the need of dedicated logistic moves (by cars, and/or trucks). The method attempts to reduce the number of movements originated by the parcels delivery by taking advantage of the citizens’ movements. In this way our proposal follows a crowdsourcing approach, in which the citizens that moves in the city, because of their own needs, become temporal deliverers. The technology behind our approach relays on Multi-agent System techniques and complex network-based algorithms for optimizing sustainable delivery routes. These artificial intelligent approaches help to reduce the complexity of the scenario providing an efficient way to integrate the citizens’ routes that can be executed using the different transportation means and networks available in the city (public system, private transportation, eco-vehicles sharing systems, etc.). A complex network-based algorithm is used for computing and proposing an optimized Sustainable Last Mile Delivery route to the crowd. Moreover, the executed tests show the feasibility of the proposed solution, together with a high reduction of the CO 2 emission coming from the delivery trucks that, in the case studies, are no longer needed for 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 Pricing and Collaboration in Last Mile Delivery Services

2018 ◽  
Vol 10 (12) ◽  
pp. 4560 ◽  
Author(s):  
Seung Ko ◽  
Sung Cho ◽  
Chulung Lee
Keyword(s):  
Time Function ◽  
Integer Programming Problem ◽  
Delivery Time ◽  
Optimal Price ◽  
Service Market ◽  
Collaboration Model ◽  
Last Mile ◽  
Last Mile Delivery ◽  
Market Density ◽  
Express Delivery

Recently, last mile delivery has emerged as an essential process that greatly affects the opportunity of obtaining delivery service market share due to the rapid increase in the business-to-consumer (B2C) service market. Express delivery companies are investing to expand the capacity of hub terminals to handle increasing delivery volume. As for securing massive delivery quantity by investment, companies must examine the profitability between increasing delivery quantity and price. This study proposes two strategies for a company’s decision making regarding the adjustment of market density and price by developing a pricing and collaboration model based on the delivery time of the last mile process. A last mile delivery time function of market density is first derived from genetic algorithm (GA)-based simulation results of traveling salesman problem regarding the market density. The pricing model develops a procedure to determine the optimal price, maximizing the profit based on last mile delivery time function. In addition, a collaboration model, where a multi-objective integer programming problem is developed, is proposed to sustain long-term survival for small and medium-sized companies. In this paper, sensitivity analysis demonstrates the effect of delivery environment on the optimal price and profit. Also, a numerical example presents four different scenarios of the collaboration model to determine the applicability and efficiency of the model. These two proposed models present managerial insights for express delivery companies.

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.

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.

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