A Multilayer Model Predictive Control Methodology Applied to a Biomass Supply Chain Operational Level
Forest biomass has gained increasing interest in the recent years as a renewable source of energy in the context of climate changes and continuous rising of fossil fuels prices. However, due to its characteristics such as seasonality, low density, and high cost, the biomass supply chain needs furthe...
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| Format: | Article |
| Language: | English |
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Wiley
2017-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2017/5402896 |
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| author | Tatiana M. Pinho João Paulo Coelho Germano Veiga A. Paulo Moreira José Boaventura-Cunha |
| author_facet | Tatiana M. Pinho João Paulo Coelho Germano Veiga A. Paulo Moreira José Boaventura-Cunha |
| author_sort | Tatiana M. Pinho |
| collection | DOAJ |
| description | Forest biomass has gained increasing interest in the recent years as a renewable source of energy in the context of climate changes and continuous rising of fossil fuels prices. However, due to its characteristics such as seasonality, low density, and high cost, the biomass supply chain needs further optimization to become more competitive in the current energetic market. In this sense and taking into consideration the fact that the transportation is the process that accounts for the higher parcel in the biomass supply chain costs, this work proposes a multilayer model predictive control based strategy to improve the performance of this process at the operational level. The proposed strategy aims to improve the overall supply chain performance by forecasting the system evolution using behavioural dynamic models. In this way, it is possible to react beforehand and avoid expensive impacts in the tasks execution. The methodology is composed of two interconnected levels that closely monitor the system state update, in the operational level, and delineate a new routing and scheduling plan in case of an expected deviation from the original one. By applying this approach to an experimental case study, the concept of the proposed methodology was proven. This novel strategy enables the online scheduling of the supply chain transport operation using a predictive approach. |
| format | Article |
| id | doaj-art-73c0e5212bfa44398d19461d847e1acd |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2017-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-73c0e5212bfa44398d19461d847e1acd2025-02-03T01:31:35ZengWileyComplexity1076-27871099-05262017-01-01201710.1155/2017/54028965402896A Multilayer Model Predictive Control Methodology Applied to a Biomass Supply Chain Operational LevelTatiana M. Pinho0João Paulo Coelho1Germano Veiga2A. Paulo Moreira3José Boaventura-Cunha4Escola de Ciências e Tecnologia, Universidade de Trás-os-Montes e Alto Douro, Quinta de Prados, 5001-801 Vila Real, PortugalInstituto de Engenharia de Sistemas e Computadores, Tecnologia e Ciência (INESC TEC), Campus da FEUP, 4200-465 Porto, PortugalInstituto de Engenharia de Sistemas e Computadores, Tecnologia e Ciência (INESC TEC), Campus da FEUP, 4200-465 Porto, PortugalInstituto de Engenharia de Sistemas e Computadores, Tecnologia e Ciência (INESC TEC), Campus da FEUP, 4200-465 Porto, PortugalEscola de Ciências e Tecnologia, Universidade de Trás-os-Montes e Alto Douro, Quinta de Prados, 5001-801 Vila Real, PortugalForest biomass has gained increasing interest in the recent years as a renewable source of energy in the context of climate changes and continuous rising of fossil fuels prices. However, due to its characteristics such as seasonality, low density, and high cost, the biomass supply chain needs further optimization to become more competitive in the current energetic market. In this sense and taking into consideration the fact that the transportation is the process that accounts for the higher parcel in the biomass supply chain costs, this work proposes a multilayer model predictive control based strategy to improve the performance of this process at the operational level. The proposed strategy aims to improve the overall supply chain performance by forecasting the system evolution using behavioural dynamic models. In this way, it is possible to react beforehand and avoid expensive impacts in the tasks execution. The methodology is composed of two interconnected levels that closely monitor the system state update, in the operational level, and delineate a new routing and scheduling plan in case of an expected deviation from the original one. By applying this approach to an experimental case study, the concept of the proposed methodology was proven. This novel strategy enables the online scheduling of the supply chain transport operation using a predictive approach.http://dx.doi.org/10.1155/2017/5402896 |
| spellingShingle | Tatiana M. Pinho João Paulo Coelho Germano Veiga A. Paulo Moreira José Boaventura-Cunha A Multilayer Model Predictive Control Methodology Applied to a Biomass Supply Chain Operational Level Complexity |
| title | A Multilayer Model Predictive Control Methodology Applied to a Biomass Supply Chain Operational Level |
| title_full | A Multilayer Model Predictive Control Methodology Applied to a Biomass Supply Chain Operational Level |
| title_fullStr | A Multilayer Model Predictive Control Methodology Applied to a Biomass Supply Chain Operational Level |
| title_full_unstemmed | A Multilayer Model Predictive Control Methodology Applied to a Biomass Supply Chain Operational Level |
| title_short | A Multilayer Model Predictive Control Methodology Applied to a Biomass Supply Chain Operational Level |
| title_sort | multilayer model predictive control methodology applied to a biomass supply chain operational level |
| url | http://dx.doi.org/10.1155/2017/5402896 |
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