Commodity demand forecasting using modulated rank reduction for humanitarian logistics planning

Fuqua, Donovan; Hespeler, Steven

doi:10.1016/j.eswa.2022.117753

Cited by 6 publications

(3 citation statements)

References 19 publications

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“…Logistics tracking is a process that is used to track storage details and information of resources in a system. The logistics tracking method tracks every detail of particular information and produces an accurate set of data for various processes [ 1 ]. Logistics tracking is a complicated task to perform in every application due to the global diversity of goods.…”

Section: Introductionmentioning

confidence: 99%

Logistics Information Traceability Mechanism of Fresh E-Commerce Based on Image Recognition Technology

Zhang

Shao

2022

Applied Bionics and Biomechanics

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Logistics migration and movement require precise information updates for traceability and visibility of goods through E-commerce platforms. Computer vision and digital image processing techniques are used for visual identification and tracking through different warehouses and delivery points. In this article, an incessant visualized tracking scheme (IVTS) is designed for identifying and tracking E-commerce logistics throughout the migration points. This scheme endorsed computer vision technology for logistics recognition and labelled data detection. In this scheme, the labelled logistics data is verified for its similarity in different migrating locations and to the endpoint. Based on the dimensional features and regional-pixel similarity factor, it is verified using the deep neural network. This learning process identifies dimensional variations due to logistics displacement and position suppressing the similarity variations. It is performed based on the migration and information available to prevent tracking errors. For the varying locations and logistics displacement, the error pixel regions are identified and trained for possible similarity detection. The proposed scheme effectively improves visual accuracy, tracking maximization, and logistics detection by reducing dimensional errors.

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Section: Introductionmentioning

confidence: 99%

Logistics Information Traceability Mechanism of Fresh E-Commerce Based on Image Recognition Technology

Zhang

Shao

2022

Applied Bionics and Biomechanics

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“…It contains many criteria and attempts to group methods. A forecast is considered an essential source of information for preparing logistical plans (Fuqua & Hespeler, 2022), including plans related to distribution and collaboration in distribution networks, and stocks in both distribution networks and supply chains should typically be treated as the ultimate mechanism balancing supply and demand (Ivanov et al, 2016). Forecasting is recognized as one of the key elements of organization management (Morlidge & Player, 2010) and as a category of risk (Christoffersen & Diebold, 2000) in material flows.…”

Section: Prediction Activity Of 3plmentioning

confidence: 99%

Supply and demand prediction by 3PL for assortment planning

Kmiecik

2025

10.5267/j.msl

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To underscore the critical role of predictive capabilities in third-party logistics (3PL) companies for assortment planning, particularly within the rapidly evolving e-commerce sector and business to business (B2B) flows. This study employs a comprehensive literature review on the forecasting capabilities of 3PL firms, enriched by empirical research across nine logistics facilities. It leverages statistical tools and the ARIMA_PLUS algorithm to evaluate the precision and dependability of demand and supply forecasts generated by these companies. The research reveals that 3PLs possess the ability to generate accurate demand and supply forecasts utilizing advanced forecasting tools. The effectiveness of these forecasts is closely linked to the quality of data available, and the expertise of the personnel involved. Challenges arise in forecasting for smaller order volumes, which are more common in e-commerce flows. The study also highlights that technological advancements and investments in data analytics are pivotal in enhancing forecast accuracy. The investigation focuses on a select group of 3PL companies, potentially limiting the generalizability of the findings. Moreover, the study underscores the necessity for further exploration into how technological innovations impact forecasting capabilities. By emphasizing the significance of 3PL firms' predictive abilities, also for e-commerce assortment planning, this paper addresses a notable gap in existing research. Its insights are invaluable for businesses contemplating logistics outsourcing and for 3PL providers aiming to advance their forecasting proficiency. The findings stress the importance of integrating advanced forecasting models and analytics to stay competitive in the dynamic e-commerce landscape.

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“…They presented a model for resistant principal component analysis (RPCA) and long short-term memory (LSTM) to deal with demand prediction issues, which has also contributed to correcting the delay in online learning. They employed a machine learning approach for demand prediction in their problem [24]. International and local aid is frequently employed to assist impacted communities in recovering from calamities or disasters.…”

Section: Literature Reviewmentioning

confidence: 99%

Efficient Humanitarian Logistics: Multi-Commodity Location–Inventory Model Incorporating Demand Probability and Consumption Coefficients

Delshad,

Chobar,

Ghasemi

et al. 2024

Logistics

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Background: A logistics network plan could be a major key issue due to its effect on supply chain effectiveness and responsiveness. This study aims to investigate the inventory location in the humanitarian logistics response stage using a three-level logistics network to integrate location–allocation problems such as warehouse location and shelter allocation to each facility, and then determine the inventory level in each warehouse. Methods: In this research, the center and its distribution, as well as the reduction in service-level costs due to inventory deficit, have been considered to increase the level of shelter services. In order to investigate the network, in this study, bi-objective mixed-integer linear programming (BOMILP) is presented. Results: The first objective is to reduce location costs and inventory costs that take into account probable demand, consumption factors, and transportation costs, and the second objective is to raise the level of services offered to victims in the model. The software programs GAMS win32, 25.1.2 and MATLAB have been utilized with numerical examples in various dimensions. Conclusions: To maximize the efficiency and quality of the service, first, the model was numerically solved, and then the location where the most commodities could be transported at the lowest possible cost was identified.

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Commodity demand forecasting using modulated rank reduction for humanitarian logistics planning

Cited by 6 publications

References 19 publications

Logistics Information Traceability Mechanism of Fresh E-Commerce Based on Image Recognition Technology

Logistics Information Traceability Mechanism of Fresh E-Commerce Based on Image Recognition Technology

Supply and demand prediction by 3PL for assortment planning

Efficient Humanitarian Logistics: Multi-Commodity Location–Inventory Model Incorporating Demand Probability and Consumption Coefficients

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