• Application of meta-heuristic algorithm for multi-objective optimization of sustainable supply chain uncertainty

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    • Keywords


      sustainable construction supply chain; multi-objective optimization; robust programming; best worst method (BWM); meta-heuristic algorithms.

    • Abstract


      In the present research, a multi-objective mathematical model for construction material supply chain design under uncertainty is investigated. The considered supply chain is made up of a primary supplier and a number of projects (i.e., customers) demanding for different construction materials in different periods of time depending on the technical specifications of the demanded product in terms of life time. Moreover, the rate of product loss due to ill-timed transportation affects the respective managerial decisions. However, the most significant issue to address is the presence of uncertainty, for which we used the robust programming method proposed by Bertsimas and Sim. In order to solve the formulated mathematical model, we used epsilon constraint method and the best-worst method as a multi-criteria decision-making method for small-scale cases, and meta-heuristic algorithms (NSGA-II, PESA, and SPEA) for large-scale problems. According to the obtained numerical results, one can observe that the SPEA algorithm outperformed all other algorithms, making it the optimal choice for addressing real cases. Moreover, a sensitivity analysis on the problem at different levels of the associated uncertainty with the parameters indicated the large impact of the uncertainty on the final outcomes. Results of this model can be used as efficient managerial instruments for optimizing the construction material supply chain design problem in the scope of civil project management.

    • Author Affiliations



      1. Department of Industrial Management, South Tehran Branch, Islamic Azad University, Tehran, Iran
    • Dates

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