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Articles 1 - 4 of 4
Full-Text Articles in Business
Statistics-Based Anomaly Detection And Correction Method For Amazon Customer Reviews, Ishani Chatterjee
Statistics-Based Anomaly Detection And Correction Method For Amazon Customer Reviews, Ishani Chatterjee
Dissertations
People nowadays use the Internet to project their assessments, impressions, ideas, and observations about various subjects or products on numerous social networking sites. These sites serve as a great source of gathering information for data analytics, sentiment analysis, natural language processing, etc. The most critical challenge is interpreting this data and capturing the sentiment behind these expressions. Sentiment analysis is analyzing, processing, concluding, and inferencing subjective texts with the views. Companies use sentiment analysis to understand public opinions, perform market research, analyze brand reputation, recognize customer experiences, and study social media influence. According to the different needs for aspect granularity, …
Optimizing Vaccine Supply Chains With Drones In Less-Developed Regions: Multimodal Vaccine Distribution In Vanuatu, Deng Pan
Dissertations
In recent years, many less-developed countries (LDCs) have been exploring new opportunities provided by drones, such as the capability to deliver items with minimal infrastructure, fast speed, and relatively low cost, especially for high value-added products such as lifesaving medical products and vaccines. This dissertation optimizes the delivery network and operations for routine childhood vaccines in LDCs. It analyzes two important problems using mathematical programming, with an application in the South Pacific nation of Vanuatu. The first problem is to optimize the nation-wide multi-modal vaccine supply chain with drones to deliver vaccines from the national depot to all health zones …
Multi-Stage Stochastic Optimization And Reinforcement Learning For Forestry Epidemic And Covid-19 Control Planning, Sabah Bushaj
Multi-Stage Stochastic Optimization And Reinforcement Learning For Forestry Epidemic And Covid-19 Control Planning, Sabah Bushaj
Dissertations
This dissertation focuses on developing new modeling and solution approaches based on multi-stage stochastic programming and reinforcement learning for tackling biological invasions in forests and human populations. Emerald Ash Borer (EAB) is the nemesis of ash trees. This research introduces a multi-stage stochastic mixed-integer programming model to assist forest agencies in managing emerald ash borer insects throughout the U.S. and maximize the public benets of preserving healthy ash trees. This work is then extended to present the first risk-averse multi-stage stochastic mixed-integer program in the invasive species management literature to account for extreme events. Significant computational achievements are obtained using …
Constructive Solution Methodologies To The Capacitated Newsvendor Problem And Surrogate Extension, Pinyuan Shan
Constructive Solution Methodologies To The Capacitated Newsvendor Problem And Surrogate Extension, Pinyuan Shan
Dissertations
The newsvendor problem is a single-period stochastic model used to determine the order quantity of perishable product that maximizes/minimizes the profit/cost of the vendor under uncertain demand. The goal is to fmd an initial order quantity that can offset the impact of backlog or shortage caused by mismatch between the procurement amount and uncertain demand. If there are multiple products and substitution between them is feasible, overstocking and understocking can be further reduced and hence, the vendor's overall profit is improved compared to the standard problem. When there are one or more resource constraints, such as budget, volume or weight, …