A two-stage stochastic programming model for biofuel supply chain network design with biomass quality implications

Nur, Farjana; Aboytes–Ojeda, Mario; Castillo-Villar, Krystel K.; Marufuzzaman, Mohammad

doi:10.1080/24725854.2020.1751347

Cited by 28 publications

(8 citation statements)

References 51 publications

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“…Two studies, Castillo-Villar et al ( 2017), Nur et al (2021), incorporated the quality-related costs into a two-stage stochastic model. The quality costs impacted the decisions made in production planning.…”

Section: Network Desing In Biorefineiesmentioning

confidence: 99%

A production planning model for biorefineries with biomass perishability and biofuel transformation

Razm

Brahimi

Hammami

et al. 2023

International Journal of Production Economics

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Section: Network Desing In Biorefineiesmentioning

confidence: 99%

A production planning model for biorefineries with biomass perishability and biofuel transformation

Razm

Brahimi

Hammami

et al. 2023

International Journal of Production Economics

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“…y ∈ {0, 1}, x ≥ 0 (30) where the confidence level of chance constraints could be greater than 0.5. The required number of experiments regarding the number of chance constraints for defining appropriate confidence levels may be increased.…”

Section: Solution Approachmentioning

confidence: 99%

“…Zarei et al [29] presented a multi-period, multi-feedstocks MIP model to design second-and third-generation BSCN to minimize total costs. Nur et al [30] manipulated a two-stage stochastic MIP model by considering the biomass quality parameters for the optimal design of the biofuel supply chain. In addition, a parallelized hybrid decomposition algorithm based on the sample average approximation was developed to refine the optimization model.…”

Section: Introductionmentioning

confidence: 99%

A Robust Possibilistic Bi-Objective Mixed Integer Model for Green Biofuel Supply Chain Design under Uncertain Conditions

et al. 2022

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In recent years, concerns regarding issues such as climate change, greenhouse gas emissions, fossil reserve dependency, and petroleum price fluctuation have led countries to focus on renewable energies. Meanwhile, in developing countries, designing an appropriate biofuel supply chain network regarding environmental competencies is an important problem. This paper presents a new bi-objective mixed integer mathematical model aiming to minimize CO2 emission and total costs in the process of the biofuel supply chain, creating a suitable green supply chain network. In this respect, CO2 emission and biofuel demand are regarded as uncertain data to address the real complex cases. Moreover, the SAUGMECON approach was implemented to construct a single objective model, and the obtained Pareto optimal points were depicted and analyzed. Thereby, a robust possibilistic programming approach was implemented to the proposed model to handle existing imprecise data. Furthermore, the applicability and performance of the proposed model were demonstrated based on an experimental example. In this respect, the obtained results from the proposed robust possibilistic programming model were compared with its crisp form to show the robustness and reliability of the proposed uncertain mathematical model.

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“…They developed the two-stage two-ordering model and employed dynamic programming to obtain an optimal ordering policy. Nur et al ( 2021 ) proposed a novel TSP model for a biofuel SCN design incorporating related uncertain parameters such as biomass quality. Lin et al ( 2020 ) designed a vaccine SCN, including manufacturers, distributors, and retailers (e.g., hospitals).…”

Section: Literature Reviewmentioning

confidence: 99%

Design and optimization of a sustainable and resilient mask supply chain during the COVID-19 pandemic: A multi-objective approach

Alizadeh-Meghrazi

Tosarkani

Amin

et al. 2022

Environ Dev Sustain

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Wearing a mask or a face covering became mandatory in indoor public spaces to reduce the spread of coronavirus disease 2019 (COVID-19). The Ontario government (i.e., a province of Canada) encouraged medical supply producers to switch their operations to produce personal protective equipment (e.g., masks) during the COVID-19 pandemic. In this regard, there are several uncertain parameters (e.g., operational costs, market demand, and capacity levels of facilities) affecting the performance of producers in a medical supplies market. In this study, we propose a flexible optimization model to configure a robust mask supply chain network under uncertainty. Furthermore, companies are supposed to undertake their operations based on sustainable manners, in compliance with provincial policy, in Ontario. Therefore, the proposed flexible optimization model is extended to a robust multi-objective model to investigate sustainable strategies in a mask supply chain network design problem. The applicability of this model is demonstrated for the Greater Toronto Area, Canada.

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A two-stage stochastic programming model for biofuel supply chain network design with biomass quality implications

Cited by 28 publications

References 51 publications

A production planning model for biorefineries with biomass perishability and biofuel transformation

A production planning model for biorefineries with biomass perishability and biofuel transformation

A Robust Possibilistic Bi-Objective Mixed Integer Model for Green Biofuel Supply Chain Design under Uncertain Conditions

Design and optimization of a sustainable and resilient mask supply chain during the COVID-19 pandemic: A multi-objective approach

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