F.-Javier Heredia - Academic web site
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New paper published in International Journal of Production Research.
printable page
Tue, 07/21/2020 - 16:46 — admin
The paper entitled
Optimal Postponement in Supply Chain Network Design Under Uncertainty: An Application for Additive Manufacturing
(
preprint
)
has been published in the International Journal of Production Research. This paper is the result of projects
Strategical Models in Supply Chain Design
, and
Digitalizing Supply Chain Strategy with 3D Printing
a successful collaboration between GNOM with
Accenture Technology Labs
(Silicon Valley),
Accenture Analytics Innovation Center
(Barcelona) and the
Fundació CIM-UPC
. This study
This study presents a new two-stage stochastic programming decision model for assessing how to introduce some new manufacturing technology into any generic supply and distribution chain. It additionally determines the optimal degree of postponement, as represented by the so-called customer order decoupling point (CODP), while assuming uncertainty in demand for multiple products. Finally, it presents and analyses a case study for introducing additive manufacturing technologies.
‹ Research project funded by the Governement of Spain
Research project with Top Cable on multiperiod one-dimensional cutting stock problem. ›
Notícies
3D printing
Accenture
AMPL
Industry 4.0
modeling languages
modellization
Postponment
stochastic programming
Supply Chain Network Design
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New publications
Speculation – postponement strategies in supply chain network design problems: a modelling framework for new supply chain strategies through stochastic optimization
Optimal Participation of Energy Communities in Electricity Markets under Uncertainty. A Multi-Stage Stochastic Programming Approach
Optimal Participation of Energy Communities in Electricity Markets under Uncertainty. A Multi-Stage Stochastic Programming Approach
Enhancing Shopping Centre Profitability through Optimized Tenant Mix and Synergistic Placement
A model to optimize the tenant mix in a shopping centre
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