scholarly journals A Disruption Recovery Problem with Time Windows Change in the Last Mile Delivery of Online Shopping

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Li Jiang ◽  
Changyong Liang ◽  
Junfeng Dong ◽  
Wenxing Lu ◽  
Marko Mladenovic
Keyword(s):  
Online Shopping ◽  
Time Window ◽  
Time Windows ◽  
Home Delivery ◽  
Delivery Mode ◽  
Variable Neighborhood Descent ◽  
Last Mile ◽  
Last Mile Delivery ◽  
Disruption Recovery ◽  
Recovery Problem

Frequent time window changing disruptions result in high secondary delivery rates in the last mile delivery. With the rapid growth of parcel volumes in online shopping, the time window changing disruptions could translate to substantial delivery cost-wastes. In recent years, customer pickup (CP), a new delivery mode that allows customers to pick up their parcels from shared delivery facilities, has provided a new way to deal with such disruptions. This study proposed a disruption recovery problem with time windows change in the last mile delivery in which customers can be served through home delivery (HD) or CP. A variant variable neighborhood descent (VVND) algorithm was presented to solve the problem. Computational experiments based on a set of instances were tested, and results were compared with other heuristics in the literature, which have affirmed the competitiveness of the model and algorithm.

scholarly journals "Sustainability evaluation of last mile food delivery: pick up point using lockers versus home delivery"

2018 ◽  
Author(s):  
Sameh M. Saad ◽  
Ramin Bahadori
Keyword(s):  
Supply Chain ◽  
Service Delivery ◽  
Simulated Annealing Algorithm ◽  
Time Window ◽  
Home Delivery ◽  
Food Delivery ◽  
Optimal Number ◽  
Home Service ◽  
Last Mile ◽  
Last Mile Delivery

"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."

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

Parcel Locker as the Alternative of Parcel Delivery Service of Online Shopping

2020 ◽  
Vol 17 (2) ◽  
pp. 1311-1317
Author(s):  
Hendra Gunawan ◽  
Nahry ◽  
Andyka Kusuma ◽  
Sarini Abdullah
Keyword(s):  
Online Shopping ◽  
Choice Model ◽  
Stated Preference ◽  
Home Delivery ◽  
Long Distance ◽  
Delivery Service ◽  
Last Mile ◽  
Online Shoppers ◽  
The Cost ◽  
Last Mile Delivery

Currently, parcel delivery activities are growing rapidly in the urban area along with the increase in online shopping transactions. This trend has an impact on the deterioration in the performance of the urban transportation system due to the increase of fleet of goods carriers as part of last mile delivery of online shopping. To overcome this situation, many countries have developed a delivery service using a parcel locker. In parcel locker service, consumers collect their shipments from lockers, which are mostly situated in public places, such as train stations, gas filling places, convenience stores, etc., instead of receiving them at their homes using a home delivery service. This service also exists in Indonesia, but its use is still not popular. This study aims to develop a choice model of last mile supply package between home delivery and parcel locker. The development of the model is based on the Binomial Logit Model. The calibration process uses the results of Stated Preference survey conducted to online shoppers who have not used parcel locker. Hypothetical conditions used in this survey represent the cost and location of a parcel locker. Location is represented by the shortest (<1 km), medium (1–3 km) and longest (3–5 km) distance of a parcel locker to the respondent’s home. Given the current cost, the potential demand for parcel lockers is 26%, 17% and 13% for short, medium and long distance, respectively. When the willingness to pay of the respondent is represented by a value whereby both methods will be chosen with the same probability, the parcel locker must offer a cost of 65% and 33%, respectively, of the home delivery option for the condition of short distance and medium distance; whereas the parcel locker cannot compete for long distance condition.

scholarly journals Urban Crowdsourced Last Mile Delivery: Mode of Transport Effects on Fleet Performance

2019 ◽  
Vol 18 (3) ◽  
pp. 441-452
Author(s):  
D. Dupljanin ◽  
M. Mirkovic ◽  
S. Dumnic ◽  
D. Culibrk ◽  
S. Milisavljevic ◽  
...  
Keyword(s):  
Delivery Mode ◽  
Last Mile ◽  
Transport Effects ◽  
Mode Of Transport ◽  
Last Mile Delivery

Design of Carbon Efficient Online Logistics Networks

2014 ◽  
Vol 962-965 ◽  
pp. 1444-1449
Author(s):  
Guang Yong Yang
Keyword(s):  
Carbon Emission ◽  
Home Delivery ◽  
Design Constraint ◽  
Logistics Network ◽  
Logistics Networks ◽  
Last Mile ◽  
Emission Regulations ◽  
Brick And Mortar ◽  
Last Mile Delivery ◽  
Delivery Network

With development of internet network, more traditional brick-and-mortar firms sell products via online channels. The key feature of online channels is home delivery, hence, how to design efficient online logistics networks has been the core problem faced by online firms. Furthermore, with increasing pollution of ecological environment and global warming, more carbon emission regulations enacted and implemented also impact firms operation and decision. This paper mainly study online logistics networks design constraint from carbon emission regulations. We analyze the following three types of networks, dropping delivery network (D), delivery network via distribution center (W), and last mile delivery network (L). Combining carbon emission from inbound and outbound transportation, and emission from inventory storage, we design optimal logistics networks and then analyze online logistics network design of Sunfeng best choice firm.

scholarly journals Picture fuzzy WASPAS method for selecting last-mile delivery mode: a case study of Belgrade

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Vladimir Simić ◽  
Dragan Lazarević ◽  
Momčilo Dobrodolac
Keyword(s):  
Urban Areas ◽  
High Reliability ◽  
Real Life ◽  
Delivery Mode ◽  
Uncertain Information ◽  
Logistics Industry ◽  
Last Mile ◽  
Picture Fuzzy Set ◽  
Last Mile Delivery

Abstract Background Last-mile delivery (LMD) is becoming more and more demanding due to an increasing number of users and traffic problems in cities. Besides, medical crises (like the COVID-19 outbreak) and air pollution represent additional motives for the transition from traditional to socially and environmentally sustainable LMD mode. An emerging problem for companies in the postal and logistics industry is how to determine the best LMD mode in a multi-criteria setting under uncertainty. Method For the first time, an extension of the Weighted Aggregated Sum Product ASsessment (WASPAS) method under the picture fuzzy environment is presented to solve the LMD mode selection problem. The introduced picture fuzzy set (PFS) based multi-criteria decision-making (MCDM) method can be highly beneficial to managers who are in charge of LMD since it can take into account the neutral/refusal information and efficiently deal with high levels of imprecise, vague, and uncertain information. The comparative analysis with the existing state-of-the-art PFS-based MCDM methods approved the high reliability of the proposed picture fuzzy WASPAS method. Its high robustness and consistency are also confirmed. The presented method can be used to improve LMD in urban areas worldwide. Besides, it can be applied to solve other emerging MCDM problems in an uncertain environment. Findings A real-life case study of Belgrade is presented to fully illustrate the potentials and applicability of the picture fuzzy WASPAS method. The results show that postomates are the best mode for LMD in Belgrade, followed by cargo bicycles, drones, traditional delivery, autonomous vehicles, and tube transport.

scholarly journals Last mile deliveries with lockers: formulations and algorithms

2021 ◽  
Author(s):  
Giovanni Buzzega ◽  
Stefano Novellani
Keyword(s):  
Valid Inequalities ◽  
Time Windows ◽  
Home Delivery ◽  
Branch And Cut ◽  
Routing Problems ◽  
Last Mile ◽  
Multiple Vehicles ◽  
Recent Method ◽  
The Difference

Abstract In this paper we consider the use of lockers in parcel delivery, a recent method used in the last mile logistics. Lockers are pick up points made of several cells that are located in several points of a city where customers can collect their parcels as an alternative to home delivery. We study routing problems in which one or multiple vehicles are used to deliver parcels directly to customers or to lockers. We also study the influence of the introduction of lockers when these problems include time windows. We propose a set of novel formulations for these problems, some valid inequalities, and a branch-and-cut algorithm. Moreover, we investigate the difference between the routing problems with lockers and the classical routing problems.

Vehicle Routing with Stochastic Supply of Crowd Vehicles and Time Windows

2021 ◽  
Author(s):  
Fabian Torres ◽  
Michel Gendreau ◽  
Walter Rei
Keyword(s):  
Urban Areas ◽  
Time Window ◽  
Time Windows ◽  
Cost Effective ◽  
Branch And Price ◽  
Irrational Behavior ◽  
Last Mile ◽  
Stochastic Solution ◽  
The Cost ◽  
Price Algorithm

The growth of e-commerce has increased demand for last-mile deliveries, increasing the level of congestion in the existing transportation infrastructure in urban areas. Crowdsourcing deliveries can provide the additional capacity needed to meet the growing demand in a cost-effective way. We introduce a setting where a crowd-shipping platform sells heterogeneous products of different sizes from a central depot. Items sold vary from groceries to electronics. Some items must be delivered within a time window, whereas others need a customer signature. Furthermore, customer presence is not guaranteed, and some deliveries may need to be returned to the depot. Delivery requests are fulfilled by a fleet of professional drivers and a pool of crowd drivers. We present a crowd-shipping platform that standardizes crowd drivers’ capacities and compensates them to return undelivered packages back to the depot. We formulate a two-stage stochastic model, and we propose a branch and price algorithm to solve the problem exactly and a column generation heuristic to solve larger problems quickly. We further develop an analytical method to calculate upper bounds on the supply of vehicles and an innovative cohesive pricing problem to generate columns for the pool of crowd drivers. Computational experiments are carried out on modified Solomon instances with a pool of 100 crowd vehicles. The branch and price algorithm is able to solve instances of up to 100 customers. We show that the value of the stochastic solution can be as high as 18% when compared with the solution obtained from a deterministic simplification of the model. Significant cost reductions of up to 28% are achieved by implementing crowd drivers with low compensations or higher capacities. Finally, we evaluate what happens when crowd drivers are given the autonomy to select routes based on rational and irrational behavior. There is no cost increase when crowd drivers are rational and select routes that have a higher compensation first. However, when crowd drivers are irrational and select routes randomly, the cost can increase up to 4.2% for some instances.

scholarly journals E-Groceries: A Channel Choice Analysis in Shanghai

2021 ◽  
Vol 13 (7) ◽  
pp. 3625
Author(s):  
Valerio Gatta ◽  
Edoardo Marcucci ◽  
Ila Maltese ◽  
Gabriele Iannaccone ◽  
Jiarui Fan
Keyword(s):  
Time Window ◽  
Stated Preference ◽  
Heterogeneous Reactions ◽  
Policy Implications ◽  
Delivery Model ◽  
Channel Choice ◽  
Market Shares ◽  
Choice Analysis ◽  
Last Mile ◽  
Last Mile Delivery

E-grocery is becoming more and more popular, involving both pure e-commerce players and physical stores in its development and sales. As a consequence, the last mile delivery model has been heavily modified, with ambiguous final impact on the environment. This paper identifies the key elements germane to e-grocery (demand and supply), discusses e-grocery development and investigates the challenges ahead. In more detail, it presents the results of a stated preference survey on consumers’ channel choices for the grocery market. The survey was carried out in Shanghai (China) in order to investigate different purchase attributes, such as product and delivery service price, product range, lead time, time window and travel time. The paper identifies heterogeneous reactions to alternative service configurations, which allows to estimate market shares for e-grocery, with the in-store option as a reference. Policy implications and operational solutions to improve the sustainability of this renewed last mile delivery model are thus proposed.

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