Vehicle Routing Optimization of Instant Distribution Routing Based on Customer Satisfaction

Zhang, Yan; Yuan, Chunhui; Wu, Jiang

doi:10.3390/info11010036

Cited by 10 publications

(7 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Compared with traditional delivery, instant delivery has the advantages of quick response, strong timeliness, greater influence by driving road conditions, and better communication with customers. It has the characteristics of close contact and so on [ 1 ]. With the continuous growth of the demand for instant delivery, the conflict between the complex driving environment and the high delivery time is further intensified.…”

Section: Introductionmentioning

confidence: 99%

A Time-Dependent Vehicle Routing Problem for Instant Delivery Based on Memetic Algorithm

Cui

Sun

Zhang

2022

Computational Intelligence and Neuroscience

View full text Add to dashboard Cite

Instant delivery is an intermediary bridge for same-city O2O services and an important part of urban short-distance logistics. The route planning and scheduling of instant delivery need to balance cost and customer satisfaction and consider the impact of traffic conditions on the distribution process. In this paper, we propose a vehicle routing problem model considering two types of customer time windows under time-dependent road networks and design a memetic algorithm combined with genetic algorithm and variable neighborhood search to solve the problem. By comparing the results of the different time periods and conducting sensitivity analysis for the two types of customer time windows, the effectiveness of the model and algorithm is verified.

show abstract

Section: Introductionmentioning

confidence: 99%

A Time-Dependent Vehicle Routing Problem for Instant Delivery Based on Memetic Algorithm

Cui

Sun

Zhang

2022

Computational Intelligence and Neuroscience

View full text Add to dashboard Cite

show abstract

“…This phenomenon was studied in countries such as France (Dablanc et al, 2017;Aguilera et al, 2018), England (Allen et al, 2021), China (Nordzi et al, 2018;Tong et al, 2020), and Brazil (Abilio et al, 2021;Abilio et al, 2021;Mello et al, 2022). However, most of the literature focuses on the operational processes of ondemand delivery services, analyzing route optimization based on customer satisfaction (Zhang et al, 2020), simulations for scheduling instant deliveries (Huang et al, 2020), evaluating the operational performance of meal deliveries and their impacts on transport and the environment (Allen et al, 2021), proposing an application of on-demand runner booking services (Nordzi et al, 2018), evaluating the dynamics of the pricing of on-demand food delivery apps (Tong et al, 2020), the commission fee of ondemand services (Li and Wang, 2021), and analyzing the optimal pricing decision and the impacts brought by customers' risk attitudes on the platform's profit (Choi et al, 2020). Moreover, some scholars have analyzed the working conditions of couriers (Abilio et al, 2021;Abilio et al, 2021) and the relationship between the delivery fee and the remuneration of couriers (Mello et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

“…These deliveries are time-sensitive, as the customer wants to be served immediately (Taylor, 2018). Instant deliveries, therefore, impose a strict deadline for delivery that, in turn, should occur within up to 2 h (Dablanc et al, 2017;Zhang et al, 2020). Instant delivery services are part of a diversity of urban freight delivery modalities that modify personal mobility patterns, challenging freight transport operations and practices and urban planning (Bjørgen et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Identification of factors that influence the delivery fee pricing of on-demand delivery services

Oliveira¹,

Mello²,

Carneiro³

et al. 2022

Front. Future Transp.

View full text Add to dashboard Cite

The use of on-demand delivery services increased in Brazil during the COVID-19 pandemic, mainly by requests for ready meals. While consumers appreciate convenience, the delivery fee is a decisive factor in the purchase process. However, the delivery fee pricing strategy of on-demand delivery service platforms has not been discussed in the literature. Thus, this study aims to analyze the factors that influence the delivery fee pricing of on-demand delivery services and explores the impact of delivery fee strategies on the remuneration of couriers. We collected data from three leading on-demand delivery service platforms regarding product type, order price, service fee, delivery fee, order day, order time, waiting time, and distance. As a result, our database comprises 1,440 orders in 12 Brazilian municipalities. A linear regression model was estimated to identify the factors influencing the delivery fee pricing considering different product types. Findings showed that product type has a diverse effect on delivery fee pricing. Moreover, distance, regardless of the product type, positively influences the delivery fee. The delivery fee of the ready meals is affected by the service fee, waiting time, order day, and order time. Furthermore, the waiting time and order day affect the delivery fee of supermarket and bakery products and beverages. Finally, the delivery fee of medical products is influenced by order day and time. Findings can be helpful for the pricing strategy of on-demand delivery services.

show abstract

“…ACO and GA were used to solve the model, and the optimal number of vehicles and the optimal distribution path were obtained accurately. The research content of this paper is based on practical problems, which can provide a decision basis for the development of e-commerce logistics of rice agricultural products [25].…”

Section: Introductionmentioning

confidence: 99%

Research on e-Commerce Distribution Optimization of Rice Agricultural Products Based on Consumer Satisfaction

et al. 2021

View full text Add to dashboard Cite

With the continuous development of agricultural product e-commerce platforms and the rapid growth of trading volume, conducting in-depth mining and analysis of online review data to improve consumer satisfaction is of considerable importance. This paper uses JingDong's self-run online reviews of rice agricultural products as the research object and analyzes the logistics factors that affect consumer satisfaction through text mining technology. A multi-objective model for logistics center distribution path optimization under a soft time window was constructed. The model used the results of online review analysis, namely, packaging integrity, delivery timeliness, and logistics cost, as the goals, and the model used ant colony algorithm (ACO) and genetic algorithm (GA) to solve the optimal distribution solution to minimize the penalty cost and transportation cost. Through examples to solve the optimal distribution vehicle number and shipping routes, in addition, a comparison of the two types of algorithm performance of the model under different node number indicated that the number of nodes affects algorithm performance. With a node number below 50, the ant ACO has high precision and a better distribution path. With a node number above 50, GA has more comprehensive performance. The average efficiency of the GA is 12.28% higher than that of ACO.

show abstract

Vehicle Routing Optimization of Instant Distribution Routing Based on Customer Satisfaction

Cited by 10 publications

References 16 publications

A Time-Dependent Vehicle Routing Problem for Instant Delivery Based on Memetic Algorithm

A Time-Dependent Vehicle Routing Problem for Instant Delivery Based on Memetic Algorithm

Identification of factors that influence the delivery fee pricing of on-demand delivery services

Research on e-Commerce Distribution Optimization of Rice Agricultural Products Based on Consumer Satisfaction

Contact Info

Product

Resources

About