Multi-stage hybrid model for supplier selection and order allocation considering disruption risks and disruptive technologies

In recent times, Supply chains are required to undergo the structural changes in order to adapt to the positive events such as Industry 4.0 and negative events such as natural and man-made disasters. Both positive and negative events tend to cause disruptions and affect business operations continuity. Supplier selection, being the critical and foremost activity must ensure that selected suppliers are capable of supporting the organizations against disruptions caused by these events. Hence, supplier selection and order allocation must be restructured considering the dynamics of Industry 4.0 and disaster events to ensure undisrupted flow of materials across supply chain. The paper proposes a multi stage hybrid model for integrated supplier segmentation, selection and order allocation considering risks and disruptions. The suppliers are then evaluated based on set of criteria suitable in Industry 4.0 environment using Data Envelopment Analysis (DEA) and are further prioritized using Fuzzy Analytical Hierarchical Process and Technique for Order of Preference by Similarity to Ideal Solution (FAHP-TOPSIS). The risk associated with each supplier is computed. The paper also proposes a Mixed Integer Program (MIP) as to optimize multi-period, multi item order allocation to suppliers in such a way that overall cost and risk of disruption is simultaneously minimized. In event of any disruption either from supply or demand side, the multi-stage hybrid model tends to reduce its economic impact by allocating emergency orders, thus, ensuring business operations continuity. The proposed multi-stage hybrid model is illustrated using a case of an automobile company.