Browsing by Author "Davis, Lauren"

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Citation Count: 8
A Heuristic Approach for Allocation of Data To Rfid Tags: A Data Allocation Knapsack Problem (dakp)
(Pergamon-Elsevier Science Ltd, 2012) Davis, Lauren; Samanlıoğlu, Funda; Jiang, Xiaochun; Mota, Daniel; Stanfield, Paul
Durable products and their components are increasingly being equipped with one of several forms of automatic identification technology such as radio frequency identification (RFID). This technology enables data collection, storage, and transmission of product information throughout its life cycle. Ideally all available relevant information could be stored on RFID tags with new information being added to the tags as it becomes available. However, because of the finite memory capacity of RFID tags along with the magnitude of potential lifecycle data, users need to be more selective in data allocation. In this research, the data allocation problem is modeled as a variant of the nonlinear knapsack problem. The objective is to determine the number of items to place on the tag such that the value of the "unexplained" data left off the tag is minimized. A binary encoded genetic algorithm is proposed and an extensive computational study is performed to illustrate the effectiveness of this approach. Additionally, we discuss some properties of the optimal solution which can be effective in solving more difficult problem instances. (C) 2011 Elsevier Ltd. All rights reserved.
Citation Count: 0
Predicting and Optimizing the Fair Allocation of Donations in Hunger Relief Supply Chains
(Elsevier, 2025) Sharmile, Nowshin; Nuamah, Isaac A.; Davis, Lauren; Samanlioglu, Funda; Jiang, Steven; Crain, Carter
Non-profit hunger relief organizations primarily depend on donors' benevolence to help alleviate hunger in their communities. However, the quantity and frequency of donations they receive may vary over time, thus making fair distribution of donated supplies challenging. This paper presents a hierarchical forecasting methodology to determine the quantity of food donations received per month in a multi-warehouse food aid network. We further link the forecasts to an optimization model to identify the fair allocation of donations, considering the network distribution capacity in terms of supply chain coordination and flexibility. The results indicate which locations within the network are under-served and how donated supplies can be allocated to minimize the deviation between overserved and underserved counties. (c) 2024 International Institute of Forecasters. Published by Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.