Using Multiple Criteria

You can select records on the basis of two or more criteria. Multiple criteria can be combined to produce a logical AND, a logical OR, or a combination of AND and OR. 

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Zheng J, Zhuang W, Yan N, Kou G, Peng H, McNally C, Erichsen D, Cheloha A, Herek S, Shi C (2004) Classification of HIV-1-mediated neuronal dendritic and synaptic damage using multiple criteria linear programming. Neuroinformatics 2 303-326. 

USING MULTIPLE CRITERIA TO COUNT ENTRIES IN A LIST... 

Figure 4-7. Using an array formula to count using multiple criteria.

Ability to subset, merge, transpose, or filter (using multiple criteria) data... 

Papazoglou, LA. and Kolias, J.G. (1997). Establishing protective long measures after severe nuclear accidents using multiple criteria. Health Physics Society, 72 (5), pp. 676-692. 

Wang, Z. D., Fingas, M., and Sigouin, L., Using multiple criteria for fingerprinting unknown oil samples having very similar chemical composition. Environ. Forensics, 3, 251-262, 2002. 

The contribution of this paper is to alert for the importance of maintainabiUty in industrial plants and essentially on the application of a decision tool using multiple criteria to understand the most important mamtainability features in a way to improve the right attributes of a specific equipment, reducing times to restore it and thus improving the availability to its desired values. In a way that every installation is different from all the others (due to different enviroiunental conditions, different exploration conditions and different maintenance policies) the presented method arises as an important technique because it can fit to each particular situation, just changing the criteria or the attributes and considering their relative importance. 

The optimization models discussed in this chapter had a single objective— either to minimize supply chain costs or to maximize supply chain profitability, in case the product prices vary by location or customer. However, customer demand fulfillment and service are also important in designing a supply chain network. More recently, supply chain risk is emerging to be another important criterion (Supply chain risk is discussed in detail in Chapter 7). Hence, recent applications of optimization models have used multiple criteria optimization models for decision making. 

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. 

Relatively few studies have used multiple criteria optimization approaches for improving HA/DR delivery operations and logistics planning. As an exception. Park (2007) develops a multi-objective decision making model to incorporate the decision maker(s) value trade-offs in the disaster relief resource allocation problem. The decision window for resource allocation is the critical first 72 hours after the initial damage assessment has been made. Value-focused thinking was used to capture the value trade-offs, and the... 

The basic idea in discriminating among multiple global solutions of the MILP transshipment model of Papoulias and Grossmann (1983) is to use as criterion the verticality of heat transfer,... 

Although single-channel conductance is a useful diagnostic criterion for the classification of other ionotropic receptors (for instance native NMDA receptors), this does not apply to neuronal nicotinic channels. Conductance levels are not very distinctive, given that even recombinant receptors that should in principle be homogeneous have multiple conductance levels, and these levels overlap considerably for different combinations. In addition, the same combination expressed in different heterologous system can give rise to different... 

Yih and Jones (1992) proposed using multilayer perceptrons in selecting some candidate rules for further evaluation of their performance. In their proposed approach, a multilayer perceptron wiU take the attributes describing the system configuration and the performance measures and wfll output a proper matching score for each dispatching rule. They also used this approach for multiple-criterion objectives. 

The SIC is deduced from Bayesian arguments. It consistently estimates the true order of ARMA(p, q) processes and is probably the most widely used information criterion in univariate time series analysis. The HQIC is the most recent IC and especially designed for multivariate time series models. In practice, multiple ICs are simultaneously calculated which allows the analyst to cross-check the recommendations of the various ICs. Strongly deviating recommendations may indicate an inappropriate model structure. 

The analytic hierarchy process (AHP) was developed by Thomas L. Saaty (1980) and is the well-known and useful method to obtain weights of each alternative in a multiple criteria decision-making problem. AHP requires the decision maker to provide judgments about the relative importance of each criterion, and then, specify a preference for each decision alternative using each criterion. The output of AHP is a prioritized ranking of the decision alternatives based on the overall preferences expressed by the decision maker. 

A criterion which has been mentioned in literature as prerequisite to use multiple regression is the normal distribution of independent and dependent variables (Tabachnick and Fidell 1989). However, scholars point out that normality is oniy important in smaller sample sizes C ait ot al. 1998) or that researchers are... 

Obviously the latter criterion is much more conservative than the former one. This would result in even larger reactors on the larger scale. Moreover a situation could occur where the parameter (p becomes > 1, which would have an adverse effect on the meso-mixing (see section 4,2,2,4), Bourne pointed out however, that a considerable gain in possible reactor capacity is obtained by using multiple feed tubes. When the feed tube diameters are increased proportionally to the scale of the reactor, the scale-up criterion for reactors with feed tubes is... 

Your facility may include multiple establishments that have different primary SIC codes. If so, calculate the value of the products produced or shipped from each establishment within the facility and then use the following rule to determine if your facility meets the SIC code criterion ... 

Emission of light due to an allowed electronic transition between excited and ground states having the same spin multiplicity, usually singlet. Lifetimes for such transitions are typically around 10 s. Originally it was believed that the onset of fluorescence was instantaneous (within 10 to lO-" s) with the onset of radiation but the discovery of delayed fluorescence (16), which arises from thermal excitation from the lowest triplet state to the first excited singlet state and has a lifetime comparable to that for phosphorescence, makes this an invalid criterion. Specialized terms such as photoluminescence, cathodoluminescence, anodoluminescence, radioluminescence, and Xray fluorescence sometimes are used to indicate the type of exciting radiation. 

Figure 3 gives two examples of L and L closeness of two functions. The L closeness leaves open the possibility that in a small region of the input space (with, therefore, small contribution to the overall error) the two functions can be considerably different. This is not the case for L closeness, which guarantees some minimal proximity of the two functions. Such a proximity is important when, as in this case, one of the functions is used to predict the behavior of the other, and the accuracy of the prediction has to be established on a pointwise basis. In these cases, the L error criterion (4) and its equivalent [Eq. (6)] are superior. In fact, L closeness is a much stricter requirement than L closeness. It should be noted that whereas the minimization of Eq. (3) is a quadratic problem and is guaranteed to have a unique solution, by minimizing the IT expected risk [Eq. (4)], one may yield many solutions with the same minimum error. With respect to their predictive accuracy, however, all these solutions are equivalent and, in addition, we have already retreated from the requirement to find the one and only real function. Therefore, the multiplicity of the best solutions is not a problem. 

In multiple linear regression (MLR) we are given an nxp matrix X and an n vector y. The problem is to find an unknown p vector b such that the product y of X with b is as close as possible to the original y using a least squares criterion ... 

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