Titlebook: Optimization in Large Scale Problems; Industry 4.0 and Soc Mahdi Fathi,Marzieh Khakifirooz,Panos M. Pardalos Book 2019 Springer Nature Swit

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The Next Generation of Optimization: A Unified Framework for Dynamic Resource Allocation Problemsisions were made. Applications arise in energy, transportation, health, finance, engineering and the sciences. Problem settings may involve managing resources (inventories for vaccines, financial investments, people and equipment), pure learning problems (laboratory testing, computer simulations, fi

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Modeling Challenges of Securing Gates for a Protected Area in Society 5.0r global reach. Typically, traffic in and out of such protected areas happens through well-defined gates. Therefore, an attacker who wants to penetrate the area has to do it through one of the gates, and the defender should try to prevent it by inspecting the incoming traffic. Security personnel fac

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Industrial Modeling and Programming Language (IMPL) for Off- and On-Line Optimization and EstimationFortran to model and solve large-scale discrete, nonlinear and dynamic (DND) optimization and estimation problems found in the batch and continuous process industries such as oil and gas, petrochemicals, specialty and bulk chemicals, pulp and paper, energy, agro-industrial, mining and minerals, food

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How Effectively Train Large-Scale Machine Learning Models?VM)s,logistic regression, graphical models and deep learning. SGM computes the estimates of the gradient from a single randomly chosen sample in each iteration. Therefore, applying a stochastic gradient method for large-scale machine learning problems can be computationally efficient. In this work,

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