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OASIS: An integrated optimisation framework for activity scheduling

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Streamflow recession analysis characterizes the storage-outflow relationship in catchments. This relationship, which typically follows a power law, summarizes all catchment-scale subsurface hydrological processes and has long been known to be a key descrip ...

2019

Wasserstein Distributionally Robust Optimization: Theory and Applications in Machine Learning

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Many decision problems in science, engineering and economics are affected by uncertain parameters whose distribution is only indirectly observable through samples. The goal of data-driven decision-making is to learn a decision from finitely many training s ...

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Hybrid, Job-Aware, and Preemptive Datacenter Scheduling

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Scheduling in datacenters is an important, yet challenging problem. Datacenters are composed of a large number, typically tens of thousands, of commodity computers running a variety of data-parallel jobs. The role of the scheduler is to assign cluster reso ...

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A Framework Based on Predictive Maintenance, Zero-Defect Manufacturing and Scheduling Under Uncertainty Tools, to Optimize Production Capacities of High-End Quality Products

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Nowadays exploiting the full potential of the humongous amount of data that manufactures can produce with their production means is a real challenge. Moreover, increasing production capabilities without large investments is a recurring objective for them. ...

SPRINGER-VERLAG BERLIN2018

Optimizing transshipment workloads in less-than-truckload cross-docks

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Elsevier Science Bv2016

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A novel sequential approach is proposed for the multiperiod synthesis of Heat Exchanger Networks (HEN) and Utility Systems of chemical processes and energy systems. The framework can be used also for single period problems. Given the set of hot and cold pr ...

American Chemical Society2015

Likelihood Estimation for the INAR(p) Model by Saddlepoint Approximation

Anthony Christopher Davison

Saddlepoint techniques have been used successfully in many applications, owing to the high accuracy with which they can approximate intractable densities and tail probabilities. This article concerns their use for the estimation of high-order integer-value ...

American Statistical Association2015

Beyond Allan Variance - GMWM Framework For Sensor Calibration

Jan Skaloud, Stéphane Guerrier

Proposed 50 years ago for studying stability of oscillators, Allan Variance (AV) was accepted by IEEE as a standard for characterizing behavior of sensors. However, the inverse mapping, i.e. the estimation of noise-parameters from Allan Variance is less st ...

2015

Online Energy-Efficient Task-Graph Scheduling for Multicore Platforms

David Atienza Alonso, Karim Kanoun

Numerous Directed-Acyclic Graph (DAG) schedulers have been developed to improve the energy efficiency of various multi-core platforms. However, these schedulers make a priori assumptions about the relationship between the task dependencies, and they are un ...

Institute of Electrical and Electronics Engineers2014

Activity pattern modeling: A path choice approach

Michel Bierlaire, Antonin Danalet

In Switzerland, the largest railway stations are called "RailCities" by the Swiss Railways. It emphasizes their transformation into place to live and perform several different activities, similar to a small-scale city. Similar concerns than in urban areas ...

2014