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Hydrocarbon and chemical logistics optimization under uncertainty via stochastic optimization

Objectif

The ability to solve large (in terms of the number of decision variables) and stochastic (in terms of parameters whose values cannot be controlled by the decision maker and are uncertain) industrial problems in practice depends on the sophistication of the tools and techniques available. The project will remedy the inadequacies of the tools currently available by developing flexible software for Supply, Transformation and Distribution (STD) logistics scheduling under uncertainty with access to new, more powerful methods capable of solving problems currently considered intractable. Specifically, the project aims to confer the ability to solve vital revenue critical problems for the industrial partners, namely, STD logistics scheduling under uncertainty for the Hydrocarbon and Chemical sector.

The project addresses improvements in both quality (better scheduling, lower costs) and efficiency (shorter response times) in STD scheduling through parallel computing algorithm implementations. This will have a direct bearing on the industrial partners' competitiveness world-wide as they face the challenges of deregulation and market globalization; Furthermore, the software developments which result will be of benefit to other industrial end-users beyond the consortium. HPC offers the means to obtain solutions very quickly, which can mean the difference between obtaining a practical solution and one which is too late for industrial purposes or is not the best solution that can be provided. The project will synthesise existing technology in the following domains:
high level model generation,
automatic uncertain data scenario generation,
optimization through recursion to deal with uncertainty and very large-scale problems, and
advanced data structures to benefit from the opportunity to use parallel computing

Champ scientifique (EuroSciVoc)

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Appel à propositions

Data not available

Coordinateur

Iberdrola Ingenieria y Consultoria, S.A.
Contribution de l’UE
Aucune donnée
Adresse
C/Gardoqui 8
48008 Bilbao
Espagne

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Coût total
Aucune donnée

Participants (4)