Supplier Evaluation Models

The AHP divides a complex decision problem into a hierarchical system of decision elements. A pairwise comparison matrix of these elements is constructed, and then the normalized principal eigenvector is calculated for the priority vector, which provides a measure of the relative importance (weight) of each element. Consider the example in Nydick and Hill (1992), where four suppliers are evaluated based on the factors of quality, price, service, and delivery. 

the buyer carries out a pairwise comparison of the four factors as shown in Table 4.4, which shows that the buyer considers supplier quality twice as important as price, four times as important as service, and three times as important as the delivery performance. Price is three times as important as both the service and delivery performances, and service is two times as important as the delivery performance. The buyer then determines the adjusted weights by dividing each column in Table 4.4 by the column total. The adjusted weights of the factors are shown in Fig. 4.8. 

the buyer repeats the above procedure to determine the pairwise rankings and the adjusted weights of the suppliers (last row in each table), for each of the four performance factors. These are shown in Tables 4.5, 4.6, 4.7, and 4.8. 

Denoting w, as the weight of factor i, and Sp as the weight of supplier j with respect to factor i, we can express the factor-moderated weight of suppliers as. 

Supplier Weight = (factor weight)(supplier weight for the factor)  

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Supplier selection - specification of desired supplier attributes, and indication of their relative importance, often through a supplier evaluation model (Figure 4.3). 

To illustrate the supplier selection method for tactical items with product bundling and to evaluate the effectiveness of GP as a solution method, we solved several supplier selection models with varying parameters and compared their solutions. This section describes how the problems were generated, computational results, and our recommendation on which GP method works better. In the case study, we assume that every supplier is... 

In Table 13-13 we list several suppliers of column simulation models that are available commercially, without in any way claiming that this list is exhaustive or providiug au endorsement of any particular package. We recommeud that users interested in any of these (or other) packages cany out au iudepeudent evaluation that focuses on the ability of the package to tackle the simulation problems of direct interest. The simulations described in this subsection were carried out with ChemSep. 

The apparatus described herein has been installed and operated in perhaps the most familiar basic glovebox, the Vacuum/Atmospheres Co. (VAC) Model HE-43-2.(2) However, it should be no less feasible to assemble the same or similar equipment into any other rigid wall inert atmosphere enclosure. Most of the systems described here contain components which are available from a number of manufacturers and distributors. In the interest of clarity, and to provide ready access to additional information, a supplier is occasionally identified. Such information does not necessarily imply a recommendation, and the interested reader is encouraged to consider alternate sources and make current cost comparisons. Finally, there is no intent to suggest that the use of these systems is any more or less safe than conventional procedures outside of a glovebox, and as always the chemist must evaluate each alternative (when planning a specific reaction or procedure) on a case by case basis. 

Outcomes and Feedback Whatever type of supplier partnership is implemented, the effectiveness of the relationship must be evaluated and possibly adjusted. The key to effective measurement and feedback is how well the drivers of partnership were developed at the outset. At this beginning point, the measurement and metrics of relating to each driver should have been made explicit. These explicit measures then become the standard in evaluation of the partnership outcomes. Feedback can loop back to any step in the model. Feedback can take the form of periodic updating of the status of the drivers, facihtators, and components. 

A five-level model that can be used to evaluate where a company is in the handling of supply chain management has been developed. Each of the levels describes different customer-supplier situations. 1 am suggesting a... 

Let us now consider how our models may be used to evaluate shipping alternatives. In this case, we consider an alternative to the Oakland supplier, specifically a supplier that is much closer to our Atlanta EXT, with commensurate differences in the item cost, freight charges, and transportation service parameters. 

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... 

Amid A, Ghodsypour SH, O Brien C (2006) Fuzzy multiobjective linear model for supplier selection in a supply chain. Int J Prod Econ 104(2) 394-407 Amid A, Ghodsypour SH, O Brien C (2011) A weighted max-min model for fiizzy multi-objective supplier selection in a supply chain. Int J Prod Econ 13I(I) I39-I45 Arbos LC (2002) Design of a rapid response and high efBciency service by lean production principles methodology and evaluation of variability of performance. Int J Prod Econ 80 (2) 169-183... 

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