Sonia Irshad Mari

Group multi-criteria supplier selection using combined grey systems theory and uncertainty theory

Developing framework for reducing purchasing risks associated with suppliers.Combination of grey system theory and uncertainty theory is used.It neither requires any probability distribution nor fuzzy membership function.It selects the most appropriate suppliers and allocates optimal purchase quantity. Supplier selection in supply chain is critical strategic decision for organizations success and has attracted much attention of both academic researchers and practitioners. Supplier selection problem consists of stochastic and recognitive uncertainties. However, the requirement of large sample size and strong subject knowledge to build suitable fuzzy membership function restrict the applicability of probability and fuzzy theories in supplier selection problem. In response, this study proposed a new tool for supplier selection. In this paper, we applied the combination of grey system theory and uncertainty theory which neither requires any probability distribution nor fuzzy membership function. The objective of this paper is to develop framework for reducing the purchasing risks associated with suppliers. The proposed supplier selection method not only selects the most appropriate supplier(s) but also allocate optimal purchase quantity under stochastic and recognitive uncertainties. An example is shown to highlight the procedure of the proposed model at the end of this paper.

Analysis of Traceability Optimization and Shareholder’s Profit for Efficient Supply Chain Operation under Product Recall Crisis

Product recall gains considerable importance in recent times; the reason may be the huge losses faced by manufacturers because of product recall issues. Furthermore, the revenue of the firm is immensely affected as a result of product recall, which may lead to serious outcomes. Huge recall cost (such as repairing or destroying the recalled products and cost of notification) occurs as a result of large recall. Therefore, in order to minimize the quantity and probability of recalls the traceability systems are widely used and considered as a necessary part of product safety strategies. However, from literature it is clear that manufacturers are still struggling to obtain the significant results. This study helps the managers to understand the importance of recall cost by analysing its impact on shareholders profit. Keeping in view the importance of problem, the paper proposed an integrated optimization model to minimize the expected loss to shareholders in recall crisis using batch dispersion methodology. The analysed results show that reduction in traceability level increases the expected shareholders losses while decreasing the operational costs. This will help managers to optimally set the production batch sizes in order to reduce the product recall impact.

A Combined Grey System Theory and Uncertainty Theory-Based Approach for Supplier Selection in Supply Chain Management

The requirement of large sample size and the strong subject knowledge to build suitable membership function restrict the applicability of probability and fuzzy theories in supplier selection problem. Due to this fact, the combination of grey system theory and uncertainty theory-based approach is applied for supplier selection problem, which requires neither any exact probability distribution nor membership function. The proposed approach is able to consider stochastic and recognitive uncertainties associated with supplier selection decision in supply chain management. This chapter develops framework for reducing the risks associated with suppliers. The novelty of this research is to consider proper uncertainty approaches in different stages of proposed framework instead of solving the whole selection problem using the same uncertainty theory or grey system theory. The proposed framework is based on three stages: identification of supplier selection criteria, defining weights to goals and ratings to supplier attributes as grey linguistic variables, and supplier selection and order allocation using uncertain-goal programming considering uncertain demand and lead time. The proposed model will help the practitioners to effectively evaluate and select suitable set of suppliers and optimal order allocation.

A Model for Optimizing Traceability of Product in a Supply Chain Based on Batch Dispersion

Product recall appears as a nightmare for manufactures as it may lead to bankruptcy. Recent product recalls stimulated manufacturers to enhance product safety in their supply chain. Implementation of traceability system now becomes necessary part of product safety strategies. Product recall crisis dramatically affect the revenue of firms which may lead to serious outcomes. Large recall induces great recall cost such as cost of notification and destroying or repairing recall products. Effective design of traceability system may turn out to be significant tool for managing recall crisis and product safety issues in production system. Traceability systems are widely used to minimize the probability and quantity of recalls however literature shows that manufacturers still not getting substantial results. This chapter develops a model to optimize the traceability based on batch dispersion methodology in order to minimize the expected recall cost and other operational cost aiming to increase shareholder profit. The simulation analysis is also carried out to test the various production strategies and its impact on profit. The analysed result show that expected shareholders profit reduces with reduction in level of traceability. It is also concluded that manufacturers should not only depended on operational costs for batch size optimization but shareholders profit should also be considered during recall crisis.