Supplier Selection Problem

Portions of this chapter have been adapted with permission from Ravindran and Wadhwa 

In most instances, buyers have to choose among a set of suppliers by using some predetermined criteria such as, quality, reliability, technical capability, lead-times, etc., even before building long-term relationships. To accomplish these goals, two basic and interrelated decisions must be made by a firm. The firm must decide which suppliers to do business with and how much to order from each supplier. Weber et al. (1991) refer to this pair of decisions as the supplier selection problem. 

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Most of the publications in the area of supplier selection have focused on final selection. In the final selection step (Figme 6.3), the buyer identifies the suppliers to do business with and allocates order quantities among the chosen supplier(s). In reviewing the literature, there are basically two kinds of supplier selection problem, as stated by Ghodsypour and O Brien (2001) ... 

To illustrate the LWP method, consider a simple supplier selection problem with two suppliers and five criteria (Quality, service, capacity, price, and risk) as shown in Table 6.3. Each criterion is measured over a scale of 1-10, with higher numbers preferred over lower ones. Note that Supplier A has higher quality, service, and capacity but costs more and has higher risk of supply disruptions. The ideal values in Table 6.3 represent the best values for each criterion. However, the ideal values are not achievable simultaneously for all the criteria, because the criteria conflict with one another. 

Finally, the business is awarded to the supplier with the lowest total cost. General Electric Wiring Devices have developed a total cost supplier selection method that takes into account risk factors, business desirable factors, and measurable cost factors (Smytka and Clemens, 1993). TCO approach has also been used by Ellram (1995), Degreave and Roodhoft (1999, 2000, 2004). Example 6.2 illustrates the TCO approach for a simple supplier selection problem. 

Many organizations have a large pool of suppliers to select from. The supplier selection problem can be solved in ttvo phases. The first phase reduces the large number of candidate suppliers to a manageable size (pre-qualification of suppliers). In Phase 11, a multiple criteria optimization... 

Consider a supplier selection problem with m suppliers and n criteria, where/iy denotes the value of criterion for supplier i. Let F denote the supplier criteria matrix. 

Consider a supplier selection problem with 3 suppliers A, B, C and three selection criteria—Total Ownership Cost (TCO), Service, and Experience. 

In this GP model, the DM only specifies the goals/targets for each objective. The model minimizes the maximum deviation from the stated goals. For the supplier selection problem the Tchebycheff goal program becomes ... 

Pre-qualification reduces a large set of initial suppliers to a smaller set of acceptable suppliers for further assessment. De Boer et al. (2001) have cited many different techniques for pre-qualification. Some of these techniques are categorical methods, data envelopment analysis (DEA), cluster analysis, case-based reasoning (CBR) systems, and multi-criteria decision making method (MCDM). Several authors have worked on pre-qualification of suppliers. Weber and Ellram (1992) and Weber et al. (2000) have developed DEA methods for pre-qualification. Hinkel et al. (1969) and Holt (1998) used cluster analysis for pre-qualification and finally Ng and Skitmore (1995) developed CBR systems for pre-qualification. Mendoza et al. (2008) developed a three phase multi-criteria method to solve a general supplier selection problem. The paper combines analytic hierarchy process (AHP) with goal programming for both pre-qualification and final order allocation. 

Besides goal programming, there are other approaches to solve the multicriteria optimization model for the supplier selection problem formulated in Section 6.4.2. They include weighted objective method, compromise programming, and interactive approaches. Interested readers can refer to Wadhwa and Ravindran (2007), Masudand Ravindran (2008, 2009) for more details. Masudand Ravindran (2008, 2009) also provide information on the computer software available for the MCDM methods. 

Xia and Wu (2007) AHP with multi-objective mathematical programming Formulated a multi-criteria supplier selection problem with supplier price breaks. Incorporates AHP to calculate criteria weights to be used in the model... 

Chen et al. (2006) Fuzzy TOPSIS Used fuzzy numbers to handle linguistic judgments and applied TOPSIS MCDM technique to address the supplier selection problem... 

Uu and Wu (2005) AHP and DEA Developed an integrated method by combining AHP and DEA, applied to the supplier selection problem... 

Chan (2003) AHP Developed an interactive technique to facilitate data collection prior to AFIP implementation in supplier selection problems... 

Consider a supplier selection problem where the five most important criteria are identified as follows ... 

Barbarosoglu, G. and T. Yazgac. 1997. An apphcation of the analytic hierarchy process to the supplier selection problem. Product and Inventory Management Journal. 38(1) 14-21. 

Ding, H., L. Benyoucef, and X. Xie. 2005. A simulation optimization methodology for supplier selection problem. International Journal of Computer Integrated Manufacturing. 18(2-3) 210-224. 

Mendoza, A., A. Ravindran, and E. Santiago, E. 2008. A three phase multi-criteria method to the supplier selection problem. International Journal of Industrial Engineering. 15(2) 195-210. 

The objective of this section is to develop optimization models for supplier selection incorporating disruption and operational risks of the supplier and apply them to a real company. The presentation is based on the work of Ravindran et al. (2010). We model the risk-adjusted supplier selection problem as a Multiple Criteria Decision Making (MCDM) problem and solve it in two phases. 

Four GP models discussed in Section 7.14.4 were used to solve the multiobjective supplier selection problem. Ideal solutions, obtained by optimizing each objective separately in the model, given by Equations 7.23 through 7.32, are given in Table 7.24. Optimal solutions obtained by each GP model are discussed next. 

Vanteddu G, Chinnam RB, Gushikin O (2011) Supply chain focus dependent supplier selection problem. Int J Prod Econ 129 204—216... 

The supplier selection problem is adopted from Weber et al. (2000). It concerns procurement of one major raw material. Suppliers are selected for the length of a relatively long planning horizon. The number of suppliers to be selected is... 

The standalone optimization of this supplier selection problem is complicated by different dimensions of supplier selection criteria. The simulation model is used for evaluating the impact of delivery performance and quality of materials on manufacturing costs. It represents the actual manufacturing system at an appropriate level of abstraction. If all selection criteria are expressed in terms of the manufacturing costs incurred, then the multi-criteria problem is transformed into... 

The supplier selection problem description defines the list of supplier selection criteria. The minimum and maximum values of supplier data that characterize the selection criteria constitute lower and upper bounds on the range of plausible values, respectively. 

The supplier selection problem is solved for each set of parameters of the manufacturing system. The fuU factorial experimental design needed to develop the meta-model is created for each set. It is developed by pairing the upper and lower values of A and identified in Table 9.3. Fifty replications are executed for each experimental cell, and a meta-model for each set is fitted. The R-squared values for all meta-models exceed 0.85. 

The above-described approach can be expanded to other supply chain configuration problems in addition to the supplier selection problem. However, it is more suitable, if the supply chain structure is partially fixed. 

Few authors have also worked on supplier selection problem, pricing and inventory decision, distributor location, relationship between buyer-supplier partnership quality, etc. They have worked on supply chain performance in the presence of uncertain environment (e.g. Srinivasan et al. 2011 Huang and Huang 2012 Sadigh et al. 2013, etc.). This paper aims to incorporate various aspects that are responsible for the uncatainty from supplier s side and then to model the same in order to minimize the cost. 

The combined grey system theory and uncertainty theory-based approach for supplier selection is proposed to solve the multi-attribute supplier selection problem. The grey system theory is employed because ffie selection of supplier attributes... 

Supplier selection problem concerns with how to choose the optimum supplier and how much quantity of material should be purchased. In the proposed model, both quantitative and qualitative attributes are included in the proposed model. The quantitative attributes are considered as uncertain purchase cost and lead time. The qualitative attributes are quality of material, delivery time, logistics service, sustainability factor, and risk. The information loss of these attributes due to lack of knowledge about suppliers and subjective judgment of DMs will be covered by using grey system theory. Notations used in the proposed model are as follows ... 

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