industrial mathematics

Strategical models in supply chain design through mathematical optimization.

Publication TypeFunded research projects
Year of Publication2016
AuthorsF.-Javier Heredia
Type of participationLeader
Duration11/2016-11/2019
Funding organizationAccenture Technology Labs
PartnersAccenture Technology Labs (Silicon Valley), Accenture Analytics Innovation Center (Barcelona)
Full time researchers2
Budget132.532,43€
Project codeI-01507, I-01508
Key Wordsresearch; supply chain; manufacturing; private; project; Accenture
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Optimización de costos logísticos: Un caso de estudio de una empresa de plásticos

Publication TypeProceedings Article
Year of Publication2016
AuthorsMiguel Mata Perez; F.-Javier Heredia; Claudia Morales Carreon
Conference NameCongreso Internacional de Logística y Cadena de Suministro 2016 CILOG2016
Series TitleSesiones técnicas
Volume2
Pagination38-46
Conference Start Date3-7/09/2016
PublisherAsociación Mexicana de Logística y Cadena de Suministro A.C.
Conference LocationYucatán, México
Key Wordsresearch; supply chain; distribution chain; logistics; paper
AbstractHoy en día los costos logísticos representan una gran oportunidad de mejora para las empresas siendo los costos de transporte y los costos de inventario los más representativos. En este trabajo se presenta un estudio de una empresa ubicada en la región, la cual incurre actualmente en altos costos logísticos en su proceso de importación de materia prima desde Asia hasta su filial en Monterrey, N.L. Por medio de un modelo matemático entero mixto se consigue minimizar los costos antes mencionados. El modelo tiene las siguientes características: es de ubicación de facilidades en cuatro etapas, multiproducto, multiperiodo y multitransporte.
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Optimización de costos logísticos: Un caso de estudio de una empresa de plásticos.

Publication TypeConference Paper
Year of Publication2016
AuthorsClaudia Morales Carreon; F.-Javier Heredia; Miguel Mata Perez
Conference NameCongreso Internacional de Logística y Cadena de Suministro 2016
Conference Date3-7/09/2016
Conference LocationYucatán, Máxico
Type of Workcontributed
Key Wordsresearch; supply chain; distribution chain; logistics
AbstractHoy en día los costos logísticos representan una gran oportunidad de mejora para las empresas siendo los costos de transporte y los costos de inventario los más representativos. En este trabajo se presenta un estudio de una empresa ubicada en la región, la cual incurre actualmente en altos costos logísticos en su proceso de importación de materia prima desde Asia hasta su filial en Monterrey, N.L. Por medio de un modelo matemático entero mixto se consigue minimizar los costos antes mencionados. El modelo tiene las siguientes características: es de ubicación de facilidades en cuatro etapas, multiproducto, multiperiodo y multitransporte.
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Contribution to CILOG2016, Congreso Internacional de Logística y Cadena de Suministro 2016

 El estudio Optimización de costos logísticos: Un caso de estudio de una empresa de plásticos se presentó el pasado octubre 2016 en el Congreso Internacional de Logística y Cadena de Suministro 2016 por Claudia Morales Carreón. El trabajo fué realizado durante la estancia de Claudia en el grupo de investigación GNOM. En este trabajo se presenta un estudio de una empresa ubicada en la región, la cual incurre actualmente en altos costos logísticos en su proceso de importación de materia prima desde Asia hasta su filial en Monterrey, N.L. Por medio de un modelo matemático entero mixto se consigue minimizar los costos antes mencionados. El modelo tiene las siguientes características: es de ubicación de facilidades en cuatro etapas, multiproducto, multiperiodo y multitransporte.

Optimal Supply Chain Strategy through Stochastic Programming

Publication TypeTesis de Grau i Màster // BSc and MSc Thesis
Year of Publication2016
AuthorsDaniel Ramon Lumbierres
DirectorF.-Javier Heredia
Tipus de tesiMSc Thesis
TitulacióMaster in Statistics and Operations Research
CentreFaculty of Mathematics and Statistics
Data defensa27/07/2016
Nota // mark9.5 Excel·lent MH (A+ with Honors)
Key Wordsteaching; supply chain; 3D printing; Postponment; stochastic programming; Accenture; MSc Thesis
AbstractIn this project, a new two-stage stochastic programming decision model has been developed to assess: (a) the convenience of introducing 3D printing into any generic manufacturing process, both single and multi-product; and (b) the optimal degree of postponement known as the customer order decoupling point (CODP) while also assuming uncertainty in demand for multiple markets. To this end, we propose the formulation of a generic supply chain through an oriented graph that represents all the deployable alternative technologies. These are defined through a set of operations for manufacturing, assembly and distribution, each of which is characterized by a lead time and cost parameters. Based on this graph, we develop a mixed integer two-stage stochastic program that finds the optimal manufacturing technology to meet the demand of each market, the optimal production quantity for each operation, and the optimal CODP for each technology. The results obtained from several case studies in real manufacturing companies are presented and analyzed. The work presented in this master’s thesis is part of an ongoing research project between UPC and Accenture.
DOI / handlehttp://hdl.handle.net/2117/88818
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Optimal Supply Chain Strategy and Postponement Degree with 3D Printing

Publication TypeConference Paper
Year of Publication2016
AuthorsDaniel Ramon Lumbierres; Asier Muguruza; Robert Gimeno Feu; Ping Guo; Mary Hamilton; Kiron Shastry; Sunny Webb; Joaquim Minguella; F.-Javier Heredia
Conference Name28th European Conference on Operational Research
Series TitleConference Handbook
Pagination330
Conference Date3-6/07/2016
Conference LocationPoznan, Poland
Type of Workcontributed presentation.
Key Wordsresearch; supply chain; 3D printing; stochastic programming; postponment; modeling; additive manufacturing
AbstractIn this contribution we would like to present the results of a research project developed by Accenture and BarcelonaTech aiming at studying the advantages of ultra-postponement with 3D printing using the analytical tools of operational research. In this project a new two-stage stochastic programming decision model has been developed to assess (a) the convenience of the introduction of 3D printing in any generic supply chain and (b) the optimal degree of postponement, the so called Customer Order Decoupling Point (CODP), assuming uncertainty in demand for multiple markets. To this end we propose the formulation of a generic supply chain through an oriented graph that represents all the alternative technologies that can be deployed, defined through a set of operations for manufacturing, assembly and distribution, each one characterized by a lead time and cost parameters. Based on this graph we develop a mixed integer two-stage stochastic program that finds the optimal manufacturing technology to meet the demand of each market, the optimal production quantity for each operation and the optimal CODP for each technology. The results obtained with several case studies from real manufacturing companies are presented and analyzed.
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Digitalizing Supply Chain Strategy with 3D Printing

Publication TypeFunded research projects
Year of Publication2015
AuthorsF.-Javier Heredia; Joaquim Minguella
Type of participationleader
Duration06/2015-07/2016
Funding organizationAccenture Technology Labs
PartnersAccenture Technology Labs (Silicon Valley), Accenture Analytics Innovation Center (Barcelona), Fundació CIM-UPC
Budget25.000$
Project codeI-01326
Key Wordsresearch; supply chain optimization; manufacturing; 3D printing; project; private; competitive; Accenture
AbstractThe aim of this research project is to study the advantages of the ultra-postponement with 3D printing (UP3DP) using the analytical tools of operational research (OR). 3D printing (3DP) is a revolutionary technology that is changing the paradigm of the supply chain management allowing delayed and tailored production under demand. However it is still to determine to which extend producers can take profit of the massive integration of this technology in their supply chain strategy: how to distribute 3DP devices among the different production plants? Which kind of technology is more appropriate? What are the benefits of this integration, both from the point of view of the manufacturer’s profit and client’s experience? We expect to find answers to all these questions with the help of the mathematical optimization models and algorithms of the operational research.
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Accenture Open Innovation university grant

As a part of the Accenture Open Innovation  initiative,  Accenture - Tech Labs has awarded 11 research grants to top universities  around the world to significantly broaden and deepen the relationships between Accenture’s technology research and development (R&D) groups and leading university researchers.

The project "Digitalizing Supply Chain Strategy with 3D Printing", lead by professor F.-Javier Heredia (GNOM-UPC) and professor Joaquim Minguella, (Fundació CIM-UPC), was one of 11 awarded projects. This research project aims at studying the advantages of ultra-postponement with 3D printing by using analytical tools and mathematical optimization models and algorithms, exploring how to transform supply chain management by allowing delayed and tailored production in the location where demand occurs. The project will be developped in collaboration with the Accenture Analytics Innovation Center (Barcelona) and Accenture Technology Labs (Silicon Valley). In the image, the attendants to the first in person meeting, held at the Faculty of Matematics and Statistics  and Fundació CIM, with representants from Accenture Analytics, Accenture Technology Labs, GNOM-UPC and FCIM-UPC.

El almacenamiento de la electricidad

Publication TypeConference/School/Seminar attendance
Year of Publication2015
AuthorsF.-Javier Heredia
Event TypeSeminar
Conference OrganiserFundación gas Natural fenosa
Conference Dates17/02/2015
Conference LocationMadrid, Spain
Key Wordsresearch; MTM2013-48462-C2-1; electricity storage systems
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Forecasting and optimization of wind generation in energy markets

Publication TypeFunded research projects
Year of Publication2014
AuthorsF.- Javier Heredia; Ma. Pilar Muñoz; Josep Anton Sánchez; Maria Dolores Márquez; Eugenio Mijangos; Marlyn Dayana Cuadrado Guevara
Type of participationPrincipal Investigator (IP)
Duration01/2014-12/2016
CallPROGRAMA ESTATAL DE INVESTIGACIÓN, DESARROLLO E INNOVACIÓN ORIENTADA A LOS RETOS DE LA SOCIEDAD
Funding organizationMinistry of Economy and Competitivity, Government of Spain
PartnersUniversitat Politècnica de Catalunya; Universitat Autònoma de Barcelona (Catalonia) Euskal Herriko Unibersitatea (Basc Country) Universidad Pontificia de Comillas (Madrid) Universidade Paulista Júlia de Mesquita Filho (Brasil) North Carolina State University (USA) Electrical Utilities: Iberdrola, Gas Natural - Fenosa. Research centers: Catalonia Institute for Energy Research.
Full time researchers4,5
Budget49.000€
Project codeMTM2013-48462-C2-1-R
Key Wordsresearch; MTM2013-48462; forecasting, optimization, wind generation, energy markets; mineco; competitive; public; project; energy
Abstract

The coordinated project " Forecasting and Optimization of Wind Generation in Energy Markets" ( FOWGEM) aims at aplying a global approach to the problem of the optimal integration of the wind-enery generation of a generation company in the wholesale electricity market through the combination of statistical forecasting models, mathematical programming models for electricity markets and optimization algorithms. In the framework of the Spanish Strategy for Science and Technology and Innovation 2013-2020 this project contributes fundamentally to challenge 3, " safe, sustainable and clean energy ." Indeed, the forecasting and optimization models and procedures that will be developed in this project, are the necessary mechanisms to allow the competitive and safe integration of wind-energy generation in the multiple-markets based wholesale national energy production system. The FOWGEM project adopts an original and global approach to this problem that combines advanced methodologies in the area of statistics, mathematical modeling of energy markets and theoretical and computatitonal optimization that were developed in several previous projects of the Plan Nacional by the groups of the Universidad Politècnica de Catalunya and the Universidad Pontificia de Comillas . The main objecives of the project are:

  1. To develop forecasting models for wind-enregy generation and electricity prices for the spot and ancillary electricity markets as a base for the optimal planning of a generation companys production.
  2. To develop mathematical programming models for the optimal integration of wind-energy production of the generation companies in the wholesale spot and ancillary services electricity market based on the results of the forecasting models for the wind-energy generation and market prices.
  3. To develop and implement efficient optimization algorithms for the large scale mixed linear and quadratic programming problems arising in real instances of the models for the integration of wind-energy production.
Regarding the social and economic impact of this project, the predictive models for wind-energy generation and market prices, together with the optimization models for the optimal integration of the wind-energy, will indicate power companies how to optimally coordinate their dispatchable generation with the estocastic wind-energy generation. As a result, the expected cost of the total production will be minimized (which means less fossil fuel consumption with the consequent positive impact on the environment ) and also the wind-energy spillage will be minimized. From the point of view of scientific and technical impact , the main feature of this project is its global an multidiciplinar approach through a methodological cycle that combines statistical methods, mathematical modeling of electricity markets and optimization techniques, in order to tackle with an actual problem concerning generation companies with real impacts on the national economy and environment. It is to mention the collaboration as EPO of two of the major Spanish gneration companies, Gas Natural Fenosa and Iberdrola, together with  the Institute for Energy Research (IREC ), the major research institution in Catalonia in the field of energy.
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