Title of article :
Resilient supplier selection in complex products and their subsystem supply chains under uncertainty and risk disruption: A case study for satellite components
Author/Authors :
Solgi, O School of Industrial Engineering - Iran University of Science and Technology - Tehran, Iran , Gheidar-Kheljani, J Management and Industrial Engineering Department - Malek Ashtar University of Technology - Tehran, Iran , Dehghani, E National Elites Foundation of Iran - Tehran, Iran , Taromi, A School of Industrial Engineering - Islamic Azad University - Science and Research Branch - Tehran, Iran
Abstract :
Recently, the manufacture of complex products and their subsystems has faced
disruption and troublesome behavior in supplying goods and items. Likewise, suppliers in
this area are more likely to be aected by external problems, resulting in disturbances.
Selecting resilient and expedient suppliers dramatically decreases delay time and costs and
contributes to the competitiveness and development of companies and organizations in
this eld. In this regard, this paper aims at proposing a bi-objective robust mathematical
model to provide resilient supplier selection and order allocation for complex products and
their subsystems in response to uncertainty and disruption risks. In the proposed model,
a robust optimization approach is deployed, providing stable decisions for the proposed
problem. Also, dierent resilience strategies, including restoring a supply from occurred
disruptions, fortication of suppliers, using backup suppliers, and utilizing extra production
capacity for suppliers, have been devised to tolerate disruptions. Meanwhile, the augmented
"-constraint method is used, ensuring optimal strong Pareto solutions and preventing weak
ones for the proposed bi-objective model. Evaluation of the eectiveness and desirability of
the developed model is explored by discussing a real case study, via which helpful managerial
insights are gained.
Keywords :
Complex products and subsystems , Robust optimization , Disruption , Supplier selection , Uncertainty , Supply chain design , Resiliency
Journal title :
Scientia Iranica(Transactions E: Industrial Engineering)