Single or Multiple Sourcing: A Method for Determining the Optimal Size of the Supply Base (original) (raw)
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How many suppliers are best? A decision-analysis approach
Omega-international Journal of Management Science, 2004
As more supply chains are becoming dependent upon suppliers, an interruption of supply networks can obstruct the functionality of the entire supply chain. The purpose of this paper is to present what we believe is a useful way to think about the number of suppliers needed in the presence of risks. We model the decision-making process using a decision tree approach. We consider catastrophic, "super-events," which a ect many/all suppliers, as well as "unique events" that a ect only a single supplier. The probabilities of these events, the ÿnancial loss caused by disasters, and the operating cost of working with multiple suppliers are captured by decision trees, from which the expected cost function is obtained and the optimal number of suppliers is determined. Our methodology will help purchasing managers, materials management, as well as academics that are considering such issues. ?
Today's supply chains are becoming not only more efficient with the aid of advanced information technologies, but also riskier due to the tight interconnectedness of numerous chain links that are prone to breakdowns, disruptions or disasters. Although many studies focusing on business risks in various contexts have been presented in the literature over the years, research effort devoted to understanding the risks associated with suppliers and the supply market has been limited, especially from a quantitative point of view. In this chapter, we first, through extensive literature view, present a taxonomy of supply-side risks, a four-step supply risk management process, and a list of techniques that help accomplish each step. Then we propose two optimization-based decision tree models that effectively formulate two decision-making situations in which the questions of how many suppliers should be used and whether to use standby suppliers are addressed. Future research directions are also suggested.
Multiple sourcing and order allocation problem under supplier disruption risk and quantity discount
International Journal of Services, Economics and Management, 2018
In this paper, we developed two stochastic mixed integer linear programs. The objective is to determine the optimal order quantities for each supplier in order to maximise the expected net profit (ENP) under disruption risk. In fact, to model this situation, overall combination of disruption probability under different settings is calculated first, and then the expected profit function for neutral risk setting is developed. Afterward, this model is extended to minimise the operational loss to model the risk averse behaviour. Discount on total quantity and on business volume are considered. The two models are illustrated through a numerical study and sensitivity analysis. The result shows that the expected profit and expected losses are very influenced by failure probability and discount levels. In fact, in presence of disruption risk, it is better to allocate order quantity from supplier who offers large discount level.
OPSEARCH, 2020
Supplier selection and order allocation are important keys for reverse logistics and closed-loop supply chain networks especially with the presence of demand-supply imbalance risks. If such uncertainties and risks are not foreseen in the chain, and corresponding appropriate measures are not taken to handle them, irreparable damages would be expected consequently. The importance of this issue in closed-loop supply chains is more appreciated due to the importance and the effect of this chain on the environment. In this research, the disruption risk and the uncertainties related to the demand, market price, and the number of returned products are simultaneously considered. Purchasing from the backup suppliers and spot market are considered, to take the proper measures in case of uncertainties. Two-stage stochastic programming model is used to express the uncertainty. The decisions on the purchase from the uncertain suppliers, and reserving from backup suppliers are made in the first step. Then, after determining the uncertainties, return decisions (purchasing from the backup suppliers, spot market and the use of returned products) are made. Besides, we develop our model with CVaR risk measurement tool, and assess risk neutral and risk averse models. We also investigate how changes in the key problem parameters can affect sourcing strategies of a firm.
International Journal of Risk Assessment and Management, 2022
In this paper, we develop two stochastic mixed integers linear programming (SMILP) models for supplier selection under disruption risk considering different capacity, failure probability, uncertain demand and quantity discounts. The suppliers are assumed domestic suppliers and global suppliers. The obtained combinatorial stochastic optimisation problem is formulated as a mixed integer program with conditional value-at-risk technique (CVaR). Numerical examples and computational results are presented. The proposed models can optimise the present problem through an estimated value at risk (VaR) and minimised CVaR simultaneously. The computational results reveal that the proposed models allow the decision maker to make an efficient selection of suppliers under disruption risk. Results also show that the decisions are not univocal because they depend on the risk proneness of the decision maker.
Optimization of supply portfolio in context of supply chain risk management: Literature review
2014 International Conference on Advanced Logistics and Transport (ICALT), 2014
Selection supplier in context of risk management supply chain has increasingly becoming a more popular research area recently. This repercussion is return to the high level of complexity of supply chains and the inherent risks that exist at any link of supply chain. Various papers, with different focus and approaches, have been published since a few years ago. This paper aimed to survey selection supplier in context of supply chain risk management (SCRM) literature. Papers collected will be analyzed and classified into two categories: the first is relatives to qualitative approach, while the second is oriented to regrouped the quantitative approach for selection supplier based on supply chain risk management
Single or dual sourcing: decision-making in the presence of supply chain disruption risks
Omega-international Journal of Management Science, 2009
The focus of this paper is placed on evaluating the impacts of supply disruption risks on the choice between the famous single and dual sourcing methods in a two-stage supply chain with a non-stationary and price-sensitive demand. The expected profit functions of the two sourcing modes in the presence of supply chain disruption risks are first obtained, and then compared so that the critical values of the key factors affecting the final choice are identified. Finally, the sensitivity of the buyer's expected profit to various input factors is examined through numerical examples, which provide guidelines for how to use each sourcing method.
Incorporating uncertainty into a supplier selection problem
Supplier selection is an important strategic supply chain design decision. Incorporating uncertainty of demand and supplier capacity into the optimization model results in a robust selection of suppliers. A two-stage stochastic programming (SP) model and a chance-constrained programming (CCP) model are developed to determine a minimal set of suppliers and optimal order quantities with consideration of business volume discounts. Both models include several objectives and strive to balance a small number of suppliers with the risk of not being able to meet demand. The SP model is scenario-based and uses penalty coefficients whereas the CCP model assumes a probability distribution and constrains the probability of not meeting demand. Both formulations improve on a deterministic mixed integer linear program and give the decision maker a more complete picture of tradeoffs between cost, system reliability and other factors. We present Pareto-optimal solutions for a sample problem to demonstrate the benefits of the SP and CCP models. In order to describe the tradeoffs between costs and risks in an analytical form, we use multi-parametric programming techniques to more completely analyze the alternative Pareto-optimal supplier selection solutions in the CCP model. This analysis gives insights into the robustness of the solutions with respect to number of suppliers, costs and probability of not meeting demand.
An effective method to supplier selection and order quantity allocation
International Journal of Business and Systems Research, 2008
Supplier selection is an essential task within the purchasing function. A well-selected set of suppliers makes a strategic difference to an organization's ability to reduce costs and improve the quality of its end products. This realization drives the search for new and better ways to evaluate and select suppliers.