Ranking of Suppliers

The problem of ranking suppliers (pre-qualification) represents a class of multiple criteria optimization problems that deal with the ranking of a finite number of alternatives, where each alternative is measured by several conflicting criteria. Several ranking methods have been developed in the multiple criteria optimization literature to solve the problem (Masud and Ravindran, 2008, 2009). In this section, we present several multiple criteria ranking approaches for fhe supplier ranking problem, namely, the pre-qualification of suppliers. 

In the pre-qualification process (Phase I), readily available qualitative and quantitative data are collected for the various suppliers. This data can be obtained from frade journals, Infernet, and pasf transactions to name a few sources. Once fhis dafa is gafhered, these suppliers are evaluated using multiple criteria ranking methods. The decision maker (DM) then selects a portion of the suppliers for exfensive evaluation in Phase II. 

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One of the most commonly used metrics is the L2 metric (p = 2), which measures the Euclidean distance between two vectors. The ranking of suppliers is done by calculating the metric between the Ideal solution (H) and each vector representing the supplier s ratings for the criteria. The Ideal solution represents the best values possible for each criterion from the initial list of suppliers. Since no supplier will have the best values for all criteria (e.g., a supplier with minimum cost may have poor quality and delivery time), the ideal solution is an artificial target and cannot be achieved. The Lp metric approach computes the distance of each supplier s attributes from the ideal solution and ranks the supplier s based on that distance (the smaller... 

Some approaches to quality management suggest that companies reduce the total number of suppliers for a service or material to just a few high quality entities. This allows the companies to symbi-otically develop relationships. Both parties can benefit greatly by using a system designed to rank preferred tollers. However, do not let the motivation to reduce the number of suppliers inhibit the critical review of potential tollers capable of performing the toll successfully. 

Go to the Web and develop a list of suppliers along with unit costs for some of the various types of flocculants described in this chapter. Also obtain the MSDS (Material Safety Data Sheets) for these chemicals. Once you have collected the information, develop a relative ranking of unit cost and health risk associated with each. For question 2 you will need information of recommended doses. 

The team has developed an evaluation sheet from the rankings of the attributes (see Figure 5.1). Each team member (and visitor, if the team chooses) can rate the supplier s answers to each attribute from zero to five after the interview is completed. 

In this chapter, we discuss supplier selection models and the multiple conflicting criteria used in supplier selection. Multi-criteria ranking methods for the prequalification of suppliers are discussed in detail. Next, multi-criteria optimization models are presented to determine the optimal order alloca-hon among the shortlisted suppliers. Several variants of goal programming methods for solving multiple criteria mathematical programming models are presented with a case study. 

Pre-qualification (Figure 6.3) is defined as the process of reducing a large set of potential suppliers to a smaller manageable number by ranking the suppliers under a pre-defined set of criteria. The primary benefits of prequalification of suppliers are (Holt, 1998) as follows ... 

Pre-qualification is an orderly process of ranking various suppliers under conflicting criteria. It is a multiple-criteria ranking problem that requires the buyer to make trade-off among the conflicting criteria, some of which may be qualitative. There are a number of multiple criteria ranking methods available for pre-qualification of suppliers. Section 6.3 discusses in detail the various ranking methods available for supplier selection. 

Recall Example 6.5 discussed in Section 6.3.6. Determine the ranking of the suppliers using the following methods ... 

The objective of Phase 1 is to shortlist suppliers by ranking them under conflicting criteria. Optimal order quantities are allocated among short-listed suppliers in Phase 2. A set of criteria to be used in the evaluation of the candidate suppliers is required to perform Phase 1 calculations. These criteria then have to be presented to the decision makers (DMs) to capture their preferences in two ways first, the importance of each criterion and attribute with respect to one another (input 1) and second, the evaluations of each candidate supplier with respect to each attribute (input 2). These input data from the DMs are then analyzed using several MCDM methods, which provide the ranking of the suppliers as an output. Figure 7.13 illustrates the flow of activities that take place in Phase 1. 

Note that additional data on the evaluation of suppliers with respect to each attribute is needed to determine the supplier rankings. This is given in Table 7.17. (Data is scaled such that all attributes are maximized)... 

It is to be noted that the exact ranking of the suppliers can vary by different methods. However, the objective of Phase 1 is to short-list the promising suppliers. Hence, the list can be expanded when there are conflicts in the rankings. 

In quality control, the proximate analysis of coal and coke is of importance. Thermogravimetry provides a convenient method for performing a proximate analysis, usually in 10-20 min. Proximate analysis covers the determination of moisture, volatile matter, fixed carbon and ash in coals and cokes and is used to establish the rank of coals, to determine the ratio of combustible to incombustible constituents, or to provide the basis for commercial trading and otherwise evaluating coal for various purposes. Hence it is important to both the suppliers and users of coal to have a rapid, accurate and reliable procedure for proximate analysis. 

Step 6 Compute the total score (TS) for each alternative as follows TS( ,yi) = S( xn)W( xi), where W is the weight vector obtained after Steps 3 and 4. Using the total scores, the alternatives are ranked. The total scores and the final rankings of the suppliers obtained by AHP for Case Study 1 are given in Table 2.12. 

The methodology followed here is based on the lead market concept elaborated on earlier. The study is an international comparison of lead market factors for the case of mobile telephony. It is examined whether the rank of adoption of the dominant design in mobile telephony is correlated with the degree of markedness of the lead market factors. For some lead market factors quantitative indicators could be found, for other factors the international comparison has to be qualitative. In addition, the roles of supply factors for the international diffusion of mobile telephony, such as technological knowledge leads and suppliers, are discussed. 

Price Cost-to-serve Supplier rank Share of customer wallet (SCW) Overall satisf. Satisf. with competition Operating margin Total sales ( k) Share costs Competitor share costs... 

In order to identify the success factors for custom manufacturing, an antagonistic approach is recommended the selection criteria for outsourcing partners, as established by a major pharmaceutical company, are listed in Appendix A.6. Those fine-chemical companies, which best comply with the 28 criteria, obviously have the best chance to become suppliers. The ranking is typically based on an extensive audit of the prospective supplier. 

The data collected is then used to prioritize waste streams and operations for assessment. Each waste stream is assigned a priority based on corporate pollution-prevention goals and objectives. Once waste origins are identified and ranked, potential methods to reduce the waste stream are evaluated. The identification of alternatives is generally based on discussions with the facility staff review of technical literature and contacts with suppliers, trade organizations, and regulatory agencies. 

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