Sustainable fertilizer supply chain network design using evolutionary-based resilient robust stochastic programming

  • Motahareh Rabbani
  • , Seyyed Mohammad Hadji Molana
  • , Seyed Mojtaba Sajadi
  • , Mohammad Hossein Davoodi

    Research output: Contribution to journalArticlepeer-review

    29 Citations (Scopus)

    Abstract

    Phosphorus is an unsustainable substance that plays an essential role in modern agricultural systems and crop yield. Due to phosphorus growing demand and the importance of sustainable application of this critical resource, there is increasing concern about its supply chain network sustainability and resiliency. In this paper, a multi-objective, multi-product, multi-period mathematical model is developed for the sustainable phosphorus supply chain management in an uncertain environment. The parametric uncertainties such as demand and supply are aggravated by disruptions with devastating effects on strategic, tactical, and operational decisions. Given the potential adverse effects of the phosphorus supply chain on the environment and human beings, a sustainable-resilient supply chain network of the fertilizer industry is designed by considering the related environmental, social, and economic challenges of the phosphorus managing. A reactive strategy is adapted to encounter the disruptions and breakdowns along with the network, while a robust stochastic programming is extended and solved using genetic algorithm to cope with the real-world uncertainties. The proposed model effectively controls the uncertainty and risk-aversion of output decisions and confronts the adverse effects of disruptions. The effectiveness and applicability of the model are validated through a real case study. Besides, the performance and reliability of the model are proved by the realization under new scenarios. The results indicate that the proposed model performs well in capturing real-world uncertainties and promoting the sustainability and resiliency of the network.

    Original languageEnglish
    Article number108770
    Number of pages22
    JournalComputers and Industrial Engineering
    Volume174
    Early online date5 Nov 2022
    DOIs
    Publication statusPublished - 12 Nov 2022

    Bibliographical note

    © 2022, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/

    Copyright © and Moral Rights are retained by the author(s) and/ or other copyright owners. A copy can be downloaded for personal non-commercial research or study, without prior permission or charge. This item cannot be reproduced or quoted extensively from without first obtaining permission in writing from the copyright holder(s). The content must not be changed in any way or sold commercially in any format or medium without the formal permission of the copyright holders.

    This document is the author’s post-print version, incorporating any revisions agreed during the peer-review process. Some differences between the published version and this version may remain and you are advised to consult the published version if you wish to cite from it.

    Keywords

    • Genetic algorithm
    • Phosphorus fertilizer supply chain
    • Resiliency
    • Robust stochastic programming
    • Sustainability

    ASJC Scopus subject areas

    • General Computer Science
    • General Engineering

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