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Development of an integrated scenario-based stochastic rolling-planning multistage logistics model considering various risks
In this study, a new integrated scenario-based stochastic rolling-planning multistage logistics model is proposed to reduce overall logistics costs. To achieve this goal, two phases were considered in the model. In the first phase, a multi-criteria group decision-making model was developed to select...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10679504/ https://www.ncbi.nlm.nih.gov/pubmed/38027593 http://dx.doi.org/10.1016/j.heliyon.2023.e22289 |
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author | Islam, Md. Mohibul Arakawa, Masahiro |
author_facet | Islam, Md. Mohibul Arakawa, Masahiro |
author_sort | Islam, Md. Mohibul |
collection | PubMed |
description | In this study, a new integrated scenario-based stochastic rolling-planning multistage logistics model is proposed to reduce overall logistics costs. To achieve this goal, two phases were considered in the model. In the first phase, a multi-criteria group decision-making model was developed to select a trustworthy supplier. In the second stage, the selected suppliers were integrated with other stakeholders to develop a rolling-planning-based logistics model using a variety of risky scenarios. Several risk factors including price variability, demand, and quality risks were considered in the model. By considering these risk factors, a new risk-embedded rolling-planning logistics method was established that regulates inventory, stock-out, and overstock problems by constantly controlling the production volume at the manufacturing site based on actual demands. In this model, the supplier's side material quality, price fluctuation risks, and customer-side demand risks were considered simultaneously. To evaluate the performance of the proposed model, a numerical example was set up, and the obtained results were compared with those of another model where fixed volume production and delivery approach was used instead of the rolling-planning approach. To verify the superiority and robustness of the proposed model, its performance was verified through a sensitivity analysis under different experimental conditions. The findings show that in a risk environment, the proposed model estimates lower logistics costs of 2697648.00 units compared to another model whose costs were 2721843.00 units. |
format | Online Article Text |
id | pubmed-10679504 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-106795042023-11-14 Development of an integrated scenario-based stochastic rolling-planning multistage logistics model considering various risks Islam, Md. Mohibul Arakawa, Masahiro Heliyon Research Article In this study, a new integrated scenario-based stochastic rolling-planning multistage logistics model is proposed to reduce overall logistics costs. To achieve this goal, two phases were considered in the model. In the first phase, a multi-criteria group decision-making model was developed to select a trustworthy supplier. In the second stage, the selected suppliers were integrated with other stakeholders to develop a rolling-planning-based logistics model using a variety of risky scenarios. Several risk factors including price variability, demand, and quality risks were considered in the model. By considering these risk factors, a new risk-embedded rolling-planning logistics method was established that regulates inventory, stock-out, and overstock problems by constantly controlling the production volume at the manufacturing site based on actual demands. In this model, the supplier's side material quality, price fluctuation risks, and customer-side demand risks were considered simultaneously. To evaluate the performance of the proposed model, a numerical example was set up, and the obtained results were compared with those of another model where fixed volume production and delivery approach was used instead of the rolling-planning approach. To verify the superiority and robustness of the proposed model, its performance was verified through a sensitivity analysis under different experimental conditions. The findings show that in a risk environment, the proposed model estimates lower logistics costs of 2697648.00 units compared to another model whose costs were 2721843.00 units. Elsevier 2023-11-14 /pmc/articles/PMC10679504/ /pubmed/38027593 http://dx.doi.org/10.1016/j.heliyon.2023.e22289 Text en © 2023 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Research Article Islam, Md. Mohibul Arakawa, Masahiro Development of an integrated scenario-based stochastic rolling-planning multistage logistics model considering various risks |
title | Development of an integrated scenario-based stochastic rolling-planning multistage logistics model considering various risks |
title_full | Development of an integrated scenario-based stochastic rolling-planning multistage logistics model considering various risks |
title_fullStr | Development of an integrated scenario-based stochastic rolling-planning multistage logistics model considering various risks |
title_full_unstemmed | Development of an integrated scenario-based stochastic rolling-planning multistage logistics model considering various risks |
title_short | Development of an integrated scenario-based stochastic rolling-planning multistage logistics model considering various risks |
title_sort | development of an integrated scenario-based stochastic rolling-planning multistage logistics model considering various risks |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10679504/ https://www.ncbi.nlm.nih.gov/pubmed/38027593 http://dx.doi.org/10.1016/j.heliyon.2023.e22289 |
work_keys_str_mv | AT islammdmohibul developmentofanintegratedscenariobasedstochasticrollingplanningmultistagelogisticsmodelconsideringvariousrisks AT arakawamasahiro developmentofanintegratedscenariobasedstochasticrollingplanningmultistagelogisticsmodelconsideringvariousrisks |