Matheuristic approach and a mixed-integer linear programming model for biomass supply chain optimization with demand selection
It is crucial to identify alternative energy sources owing to the ever-increasing demand for energy and the other environmental problems associated with using fossil fuels. Biomass as a source of bioenergy is considered a promising alternative to fossil fuels. This study aims to optimize th...
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| Format: | Article |
| Language: | English |
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Growing Science
2024-01-01
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| Series: | International Journal of Industrial Engineering Computations |
| Online Access: | http://www.growingscience.com/ijiec/Vol15/IJIEC_2023_44.pdf |
| _version_ | 1797379883611979776 |
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| author | Mohammad A. M. Abdel Aal |
| author_facet | Mohammad A. M. Abdel Aal |
| author_sort | Mohammad A. M. Abdel Aal |
| collection | DOAJ |
| description | It is crucial to identify alternative energy sources owing to the ever-increasing demand for energy and the other environmental problems associated with using fossil fuels. Biomass as a source of bioenergy is considered a promising alternative to fossil fuels. This study aims to optimize the biomass supply chain by developing an integrated model incorporating typical tactical supply chain decisions based on market or demand selection decisions. To this end, a novel mixed-integer linear programming (MILP) model is proposed to maximize the profit of the corresponding biomass supply chain and to commercialize electricity production by selecting electricity demand and making supply chain decisions regarding power plant operations, biomass feedstock purchase and storage, and biomass transport trucks. Owing to the intricacy of the MILP model, a fix-and-optimize-based solution strategy is developed and validated by applying it to several instances of a real-world case study. The results demonstrate that the proposed strategy can significantly reduce computational time while preserving high solution quality. Additionally, it helps improve planning and decision-making as it reveals the effect of essential biomass logistics characteristics on routing outcomes. |
| first_indexed | 2024-03-08T20:29:29Z |
| format | Article |
| id | doaj.art-e9cb890a5e4243a49961c20388b47501 |
| institution | Directory Open Access Journal |
| issn | 1923-2926 1923-2934 |
| language | English |
| last_indexed | 2024-03-08T20:29:29Z |
| publishDate | 2024-01-01 |
| publisher | Growing Science |
| record_format | Article |
| series | International Journal of Industrial Engineering Computations |
| spelling | doaj.art-e9cb890a5e4243a49961c20388b475012023-12-22T14:28:37ZengGrowing ScienceInternational Journal of Industrial Engineering Computations1923-29261923-29342024-01-0115123525410.5267/j.ijiec.2023.10.001Matheuristic approach and a mixed-integer linear programming model for biomass supply chain optimization with demand selectionMohammad A. M. Abdel Aal It is crucial to identify alternative energy sources owing to the ever-increasing demand for energy and the other environmental problems associated with using fossil fuels. Biomass as a source of bioenergy is considered a promising alternative to fossil fuels. This study aims to optimize the biomass supply chain by developing an integrated model incorporating typical tactical supply chain decisions based on market or demand selection decisions. To this end, a novel mixed-integer linear programming (MILP) model is proposed to maximize the profit of the corresponding biomass supply chain and to commercialize electricity production by selecting electricity demand and making supply chain decisions regarding power plant operations, biomass feedstock purchase and storage, and biomass transport trucks. Owing to the intricacy of the MILP model, a fix-and-optimize-based solution strategy is developed and validated by applying it to several instances of a real-world case study. The results demonstrate that the proposed strategy can significantly reduce computational time while preserving high solution quality. Additionally, it helps improve planning and decision-making as it reveals the effect of essential biomass logistics characteristics on routing outcomes.http://www.growingscience.com/ijiec/Vol15/IJIEC_2023_44.pdf |
| spellingShingle | Mohammad A. M. Abdel Aal Matheuristic approach and a mixed-integer linear programming model for biomass supply chain optimization with demand selection International Journal of Industrial Engineering Computations |
| title | Matheuristic approach and a mixed-integer linear programming model for biomass supply chain optimization with demand selection |
| title_full | Matheuristic approach and a mixed-integer linear programming model for biomass supply chain optimization with demand selection |
| title_fullStr | Matheuristic approach and a mixed-integer linear programming model for biomass supply chain optimization with demand selection |
| title_full_unstemmed | Matheuristic approach and a mixed-integer linear programming model for biomass supply chain optimization with demand selection |
| title_short | Matheuristic approach and a mixed-integer linear programming model for biomass supply chain optimization with demand selection |
| title_sort | matheuristic approach and a mixed integer linear programming model for biomass supply chain optimization with demand selection |
| url | http://www.growingscience.com/ijiec/Vol15/IJIEC_2023_44.pdf |
| work_keys_str_mv | AT mohammadamabdelaal matheuristicapproachandamixedintegerlinearprogrammingmodelforbiomasssupplychainoptimizationwithdemandselection |