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Armin Jabbarzadeh - One of the best experts on this subject based on the ideXlab platform.

  • sustainable design of a municipal solid waste management system considering waste separators a real World Application
    Sustainable Cities and Society, 2019
    Co-Authors: Razieh Heidari, Reza Yazdanparast, Armin Jabbarzadeh
    Abstract:

    Abstract Enhancing sustainability in Municipal Solid Waste (MSW) management requires options that alleviate environmental issues and provide economic and social benefits. Though, the social aspect of sustainability has not been thoroughly investigated in the related literature. Therefore, this paper proposes a new multi-objective mathematical programming model considering new employment opportunities as the social side of sustainability. Furthermore, due to ineffective public participation in the waste management processes in the developing countries, incorporating waste separation after collection in the waste management practices is the suggestion of this study to contribute to the social sustainability. Other aspect of the proposed model is uncertainty that is inevitable and should be acknowledged to guarantee reliability in the decision-making process. To handle the uncertain model coefficients and stipulations, we utilize the robust possibilistic programming approach. The Application of the proposed model is demonstrated in a real case study associated with the Tehran MSW system. The obtained results indicate that composting is the worst waste final disposal alternative, while anaerobic digestion and incineration have better performance in terms of the sustainability indicators. Moreover, the preliminary findings of a sensitivity analysis show that the waste recovery percentage has a direct influence on rates of waste reuse and recycling.

  • closed loop supply chain network design under disruption risks a robust approach with real World Application
    Computers & Industrial Engineering, 2018
    Co-Authors: Armin Jabbarzadeh, Michael Haughton, Amir Khosrojerdi
    Abstract:

    Abstract In today’s globalized and highly uncertain business environments, supply chains have become more vulnerable to disruptions. This paper presents a stochastic robust optimization model for the design of a closed-loop supply chain network that performs resiliently in the face of disruptions. The proposed model is capable of considering lateral transshipment as a reactive strategy to cope with operational and disruption risks. The objective is to determine facility location decisions and lateral transshipment quantities that minimize the total supply chain cost across different disruption scenarios. A Lagrangian relaxation algorithm is developed to solve the robust model efficiently. Important managerial insights are obtained from the model implementation in a case study of glass the industry.

  • Robust supply chain network design: an optimization model with real World Application
    Annals of Operations Research, 2017
    Co-Authors: Shiva Zokaee, Armin Jabbarzadeh, Behnam Fahimnia, Seyed Jafar Sadjadi
    Abstract:

    This paper presents a robust optimization model for the design of a supply chain facing uncertainty in demand, supply capacity and major cost data including transportation and shortage cost parameters. We first present a base model that aims to determine the strategic ‘location’ and tactical ‘allocation’ decisions for a deterministic four-tier supply chain. The model is then extended to incorporate uncertainty in key input parameters using a robust optimization approach that can overcome the limitations of scenario-based solution methods in a tractable way, i.e. without excessive changes in complexity of the underlying base deterministic model. The Application of the approach is investigated in an actual case study where real data is utilized to design a bread supply chain network. Numerical results obtained from model implementation and sensitivity analysis experiments arrive at important managerial insights and practical implications.

  • dynamic supply chain network design for the supply of blood in disasters a robust model with real World Application
    Transportation Research Part E-logistics and Transportation Review, 2014
    Co-Authors: Armin Jabbarzadeh, Behnam Fahimnia, Stefan Seuring
    Abstract:

    This paper presents a robust network design model for the supply of blood during and after disasters. A practical optimization model is developed that can assist in blood facility location and allocation decisions for multiple post-disaster periods. The Application of the proposed model is investigated in a case problem where real data is utilized to design a network for emergency supply of blood during potential disasters. Our analysis on the tradeoff between solution robustness and model robustness arrives at important practical insights. The performance of the proposed ‘robust optimization’ approach is also compared with that of an ‘expected value’ approach.

Stefan Seuring - One of the best experts on this subject based on the ideXlab platform.

  • dynamic supply chain network design for the supply of blood in disasters a robust model with real World Application
    Transportation Research Part E-logistics and Transportation Review, 2014
    Co-Authors: Armin Jabbarzadeh, Behnam Fahimnia, Stefan Seuring
    Abstract:

    This paper presents a robust network design model for the supply of blood during and after disasters. A practical optimization model is developed that can assist in blood facility location and allocation decisions for multiple post-disaster periods. The Application of the proposed model is investigated in a case problem where real data is utilized to design a network for emergency supply of blood during potential disasters. Our analysis on the tradeoff between solution robustness and model robustness arrives at important practical insights. The performance of the proposed ‘robust optimization’ approach is also compared with that of an ‘expected value’ approach.

Behnam Fahimnia - One of the best experts on this subject based on the ideXlab platform.

  • Robust supply chain network design: an optimization model with real World Application
    Annals of Operations Research, 2017
    Co-Authors: Shiva Zokaee, Armin Jabbarzadeh, Behnam Fahimnia, Seyed Jafar Sadjadi
    Abstract:

    This paper presents a robust optimization model for the design of a supply chain facing uncertainty in demand, supply capacity and major cost data including transportation and shortage cost parameters. We first present a base model that aims to determine the strategic ‘location’ and tactical ‘allocation’ decisions for a deterministic four-tier supply chain. The model is then extended to incorporate uncertainty in key input parameters using a robust optimization approach that can overcome the limitations of scenario-based solution methods in a tractable way, i.e. without excessive changes in complexity of the underlying base deterministic model. The Application of the approach is investigated in an actual case study where real data is utilized to design a bread supply chain network. Numerical results obtained from model implementation and sensitivity analysis experiments arrive at important managerial insights and practical implications.

  • dynamic supply chain network design for the supply of blood in disasters a robust model with real World Application
    Transportation Research Part E-logistics and Transportation Review, 2014
    Co-Authors: Armin Jabbarzadeh, Behnam Fahimnia, Stefan Seuring
    Abstract:

    This paper presents a robust network design model for the supply of blood during and after disasters. A practical optimization model is developed that can assist in blood facility location and allocation decisions for multiple post-disaster periods. The Application of the proposed model is investigated in a case problem where real data is utilized to design a network for emergency supply of blood during potential disasters. Our analysis on the tradeoff between solution robustness and model robustness arrives at important practical insights. The performance of the proposed ‘robust optimization’ approach is also compared with that of an ‘expected value’ approach.

Marc P Bonaca - One of the best experts on this subject based on the ideXlab platform.

Razieh Heidari - One of the best experts on this subject based on the ideXlab platform.

  • sustainable design of a municipal solid waste management system considering waste separators a real World Application
    Sustainable Cities and Society, 2019
    Co-Authors: Razieh Heidari, Reza Yazdanparast, Armin Jabbarzadeh
    Abstract:

    Abstract Enhancing sustainability in Municipal Solid Waste (MSW) management requires options that alleviate environmental issues and provide economic and social benefits. Though, the social aspect of sustainability has not been thoroughly investigated in the related literature. Therefore, this paper proposes a new multi-objective mathematical programming model considering new employment opportunities as the social side of sustainability. Furthermore, due to ineffective public participation in the waste management processes in the developing countries, incorporating waste separation after collection in the waste management practices is the suggestion of this study to contribute to the social sustainability. Other aspect of the proposed model is uncertainty that is inevitable and should be acknowledged to guarantee reliability in the decision-making process. To handle the uncertain model coefficients and stipulations, we utilize the robust possibilistic programming approach. The Application of the proposed model is demonstrated in a real case study associated with the Tehran MSW system. The obtained results indicate that composting is the worst waste final disposal alternative, while anaerobic digestion and incineration have better performance in terms of the sustainability indicators. Moreover, the preliminary findings of a sensitivity analysis show that the waste recovery percentage has a direct influence on rates of waste reuse and recycling.