Community logistics and dynamic community partitioning: A new approach for solving e-commerce last mile delivery

Ouyang, Zhiyuan; Leung, Eric Ka Ho; Huang, George Q.

doi:10.1016/j.ejor.2022.08.029

Cited by 11 publications

(4 citation statements)

References 43 publications

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“…Timeliness refers to the most favourable duration from order placement to the reception of parcels at the clients' location. Nowadays, with information systems and various optimization software for storage, picking, sorting and transport planning, courier service providers can deliver in lesser time possible and at a higher speed [40]. Timeliness of courier service providers also proves the reliability of the providers as they can deliver within the expected date of delivery [41].…”

Section: Resultsmentioning

confidence: 99%

Multi-Criteria Decision Analysis on the Preference of Courier Service Providers with Analytic Hierarchy Process Model

Pei Fun Lee,

Weng Siew Lam,

Weng Hoe Lam

et al. 2023

ARASET

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The rising interest in E-commerce has increased the reliance on courier service providers in Malaysia. However, the logistical performances of the courier service providers in Malaysia still require improvement especially in the enhancement of information system adoption as the providers are suffering from bottlenecks in some hubs and centres which affect the satisfaction of clients and the reputation of the online retailers. Online retailers place high concern in the performances of the courier service providers as their services affect the sales and revenues of the online retailers. Therefore, the goal of this study is to propose a framework to determine and rank the factors that affect the selection of courier service providers among online retailers in Malaysia with Analytic Hierarchy Process (AHP) model. This study found that real time notification, cost and timeliness are the three most important factors of consideration while GDEX is the highly preferred courier service provider among the online retailers. This study can serve as a guide to the courier service providers to improve based on the top factors that influence the selection of their services.

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Section: Resultsmentioning

confidence: 99%

Multi-Criteria Decision Analysis on the Preference of Courier Service Providers with Analytic Hierarchy Process Model

Pei Fun Lee,

Weng Siew Lam,

Weng Hoe Lam

et al. 2023

ARASET

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“…Transportation of items from a distribution hub to the customer's door is known as last-mile delivery (LMD) or last-mile logistics (Gonzalez, 2023). To deliver the packages at the latest possible momenteconomically, swiftly, and accurately is the aim of last-mile delivery logistics (Ouyang et al, 2023). LMD has been growing worldwide by 17 percent annually (World economic forum, 2023).…”

Section: Introductionmentioning

confidence: 99%

Examining environmental sustainability in last-mile delivery: a quality function deployment analysis

Agarwal,

Ojha

2024

Preprint

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Considering the unprecedented growth in last-mile delivery (LMD) of goods in the e-commerce business, the paper aims to analyze its related environmental sustainability concerns. It involves prioritizing the barriers to sustainable LMD and recommending countermeasures to minimise the growing adverse impact of last-mile logistics on the environment. The Quality Function Deployment (QFD) approach is applied to convert the LMD barriers into sustainable LMD design requirements. It utilizes Delphi approach to capture inputs for the development of the House of Quality (HOQ) framework. The analysis from the HOQ has highlighted that four dominant barriers contribute approximately 70% to the total sustainability issues of LMD. These are high emissions due to fossil-fuelled vehicles, lack of consumer awareness, increasing traffic congestion due to delivery vehicles, and growing expectations from today’s end-consumers. Five out of the nine countermeasures identified together have a significant 72% contribution in mitigating the adverse impact of the growing LMD.

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“…To provide consumers with high-quality service, logistics companies typically either deliver the goods directly to the customer's home or leave them at a designated location. The final step in delivery, referred to as the "last mile" by Goodman [3], has stimulated the emergence of drone delivery, which aims to enhance the speed and convenience of service. Furthermore, replacing trucks with drones can significantly reduce logistics costs.…”

Section: Introductionmentioning

confidence: 99%

Using Improved Particle Swarm Optimization Algorithm for Location Problem of Drone Logistics Hub

Zheng,

Xu,

Chen

2024

CMC

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Drone logistics is a novel method of distribution that will become prevalent. The advantageous location of the logistics hub enables quicker customer deliveries and lower fuel consumption, resulting in cost savings for the company's transportation operations. Logistics firms must discern the ideal location for establishing a logistics hub, which is challenging due to the simplicity of existing models and the intricate delivery factors. To simulate the drone logistics environment, this study presents a new mathematical model. The model not only retains the aspects of the current models, but also considers the degree of transportation difficulty from the logistics hub to the village, the capacity of drones for transportation, and the distribution of logistics hub locations. Moreover, this paper proposes an improved particle swarm optimization (PSO) algorithm which is a diversity-based hybrid PSO (DHPSO) algorithm to solve this model. In DHPSO, the Gaussian random walk can enhance global search in the model space, while the bubble-net attacking strategy can speed convergence. Besides, Archimedes spiral strategy is employed to overcome the local optima trap in the model and improve the exploitation of the algorithm. DHPSO maintains a balance between exploration and exploitation while better defining the distribution of logistics hub locations Numerical experiments show that the newly proposed model always achieves better locations than the current model. Comparing DHPSO with other state-of-the-art intelligent algorithms, the efficiency of the scheme can be improved by 42.58%. This means that logistics companies can reduce distribution costs and consumers can enjoy a more enjoyable shopping experience by using DHPSO's location selection. All the results show the location of the drone logistics hub is solved by DHPSO effectively.

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Community logistics and dynamic community partitioning: A new approach for solving e-commerce last mile delivery

Cited by 11 publications

References 43 publications

Multi-Criteria Decision Analysis on the Preference of Courier Service Providers with Analytic Hierarchy Process Model

Multi-Criteria Decision Analysis on the Preference of Courier Service Providers with Analytic Hierarchy Process Model

Examining environmental sustainability in last-mile delivery: a quality function deployment analysis

Using Improved Particle Swarm Optimization Algorithm for Location Problem of Drone Logistics Hub

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