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Reshoring manufacturing: the influence of industry 4.0, Covid-19, and made-in effects
Empirical investigations of how the reshoring of manufacturing is affected by Industry 4.0 technologies, supply chain disruptions, and made-in...
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Free disposal hull models of multicomponent technologies
Free disposal hull (FDH) is a nonparametric model of production technology based on the single assumption of free disposability of all inputs and...
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A multi-objective optimization approach for resource allocation and transportation planning in institutional quarantine centres
The COVID-19 pandemic has profoundly impacted global logistics and supply chains, resulting in widespread disruptions due to outbreaks, labour...
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A dynamic simulation model to improve the livability of transportation systems
Transportation users often face shortcomings, such as unreliable service causing uncertainty in transit, low quality of service, and loss of time due...
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GreenPLM: the concept of sharing community knowledge for new green product development and process planning
The issue of eco-friendliness and sustainable development is crucial in various domains of our lives. This also affects the production of products...
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Digital Sustainability for Energy-Efficient Behaviours: A User Representation and Touchpoint Model
In response to climate change, nations have been tasked with reducing energy consumption and lessening their carbon footprint through targeted...
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Virtual Experiences, Real Memories? A Study on Information Recall and Recognition in the Metaverse
There are high expectations towards extended reality (XR), namely the “metaverse”. However, human performance in the metaverse has been called into...
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Smoothed semicovariance estimation for portfolio selection
Downside risk measures, such as semivariance, are essential for evaluating investment risk. Focusing on semivariance allows investors to emphasize...
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Deep learning for derivatives pricing: a comparative study of asymptotic and quasi-process corrections
In this study, we compare two methods for using neural networks to efficiently learn the price of derivatives. The first method, proposed by...
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A Taxonomy of Home Automation: Expert Perspectives on the Future of Smarter Homes
Recent advancements in digital technologies, including artificial intelligence (AI), Internet of Things (IoT), and information and communication...
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Prediction of bank credit worthiness through credit risk analysis: an explainable machine learning study
The control of credit risk is an important topic in the development of supply chain finance. Financial service providers should distinguish between...
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Complex Fermatean fuzzy partitioned Maclaurin symmetric mean operators and their application to hostel site selection
Complex Fermatean fuzzy (CFF) set is a powerful mathematical model that handles uncertain data effectively. However, existing multi-criteria...
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Operations Research at Netherlands Railways
This paper briefly summarises the role of Operations Research techniques at Netherlands Railways (NS). We discuss the type of problems we are facing,...
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Fighting Fire with Fire: Combating Criminal Abuse of Cryptocurrency with a P2P Mindset
As part of the P2P sharing economy, cryptocurrencies offer both creative and criminal opportunities. To deal with offenders, solutions such as...
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Data Ingestion Validation Through Stable Conditional Metrics with Ranking and Filtering
We introduce an advanced method for validating data quality, which is crucial for ensuring reliable analytics insights. Traditional data quality...
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Weighing hierarchical power and active contribution in cooperative games with authorization structure
Cooperative games model situations in which a group of players work together to make a profit. Frequently, in cooperative situations there are...
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Min–max relative regret for scheduling to minimize maximum lateness
We study the single machine scheduling problem under uncertain parameters, with the aim of minimizing the maximum lateness. More precisely, the...
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Operations Research at Ryanair
This short paper presents how Operations Research methods are employed at Ryanair in various decision problems, the project we have conducted and the...
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Enabling business sustainability for stock market data using machine learning and deep learning approaches
This paper introduces AlphaVision, an innovative decision support model designed for stock price prediction by seamlessly integrating real-time news...
