Results 61 to 70 of about 1,501,275 (273)
An approximation scheme for stochastic linear programming and its application to stochastic integer programs [PDF]
Journal of the ACM, 2006 Stochastic optimization problems attempt to model uncertainty in the data by assuming that the input is specified by a probability distribution. We consider the well-studied paradigm of 2-stage models with recourse: first, given only distributional information about (some of) the data one commits on initial actions, and then once the actual data is ...
David B. Shmoys, Chaitanya Swamy
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Applied Economic Perspectives and Policy, EarlyView.ABSTRACT We conducted two framed field economic experiments with citrus farmers in Florida, United States and soybean farmers in Argentina to investigate their willingness to coordinate pest and weed management efforts. Despite the contrast between these two agricultural contexts, we find striking behavioral commonalities.
Ariel Singerman, Sergio H. Lence
wiley +1 more source
Planning of a supply chain for anti-personal landmine disposal by means of robots
Innovar: Revista de Ciencias Administrativas y Sociales, 2012 The current paper presents a Mixed-Integer-Linear Programming Model (MIP) which incorporates strategic and tactical management decisions into the supply chain of an anti-personal landmine robotic detection and disposal system.
Rafael Guillermo García-Cáceres +2 more
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IET Renewable Power Generation, 2021 Mixed‐integer linear programming is widely used in hydropower reservoirs operation optimisation because of its modelling flexibility, solution stability, and global search capability.
Zhipeng Zhao +2 more
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Advanced Intelligent Systems, EarlyView.A volatile‐switching compact model of electrochemical metallization memory cells for neuromorphic architecture is developed and validated by reliable reproduction of device characterization measurements: I−V sweeps, SET kinetics, relaxation dynamics.
Rana Walied Ahmad +4 more
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Chemical Engineering Transactions, 2017 This work addresses the life cycle economic and environmental optimisation of a supply chain network considering both design and operational decisions under uncertainty.
J. Gao, F. You
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Advanced Intelligent Systems, EarlyView.An agentic AI‐driven decision‐support framework for prosumers is proposed, integrating PV generation, load profiling, and multihorizon optimization within a four‐agent architecture. The approach significantly reduces grid dependence, enhances self‐sufficiency and prevents system oversizing.
Adela BÂRA, Simona‐Vasilica OPREA
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International Journal of Electrical Power & Energy SystemsInvestment in technologies that allow for dynamic formation of microgrids, such as distributed energy resources to provide power and switches to adapt network topology, can improve the reliability of distribution networks.
Ramsey Rossmann +2 more
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Energy‐Aware Perturbation Optimization for Memristor‐Array Convolutional Neural Networks
Advanced Intelligent Systems, EarlyView.Memristor‐array inference becomes more energy efficient when layer inputs are reshaped before computation. Sinusoidal perturbation encoding with dual‐threshold screening reduces active voltage pulses and contracts ADC input‐current ranges, jointly lowering crossbar and peripheral energy while preserving accuracy across hardware MNIST validation, deep ...
Ao Xu +6 more
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A Scalable and Resource‐Efficient Pipelined p‐Computer for Probabilistic Ising Machines
Advanced Intelligent Systems, EarlyView.(a) Block diagram of the portfolio optimization problem: given M assets, the goal is to determine the optimal weights w that maximize the expected return (based on the mean historical assets return u), while minimizing the risk, quantified by the assets covariance matrix S.
Deborah Volpe +9 more
wiley +1 more source