دانلود رایگان مقاله لاتین ارزیابی عملکرد آب و برق از سایت الزویر
عنوان فارسی مقاله:
کیفیت خدمات: ارزیابی عملکرد کلی برای آب و برق
عنوان انگلیسی مقاله:
The quality of service: An overall performance assessment for water utilities
سال انتشار : 2016
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بخشی از مقاله انگلیسی:
2. The ELECTRE TRI-nC method
In this section, we present the ELECTRE TRI-nC method [22], a multiple criteria sorting based method of the ELECTRE family methods [28], which were designed into two main phases: (1) construction of one or several outranking relations, aimed at comparing each pair of actions; and (2) exploitation of these outranking relations (for more details, see [29]). This method follows a decision aiding constructive approach, through the interaction between the analyst(s) and the decision-maker(s) (DMs). 2.1. Concepts, definitions and notation In what follows, let A = {a1, ..., ai, ...} denote a set of potential actions, and g a given criterion. A coherent family of criteria, F = {g1, ..., gj , ..., gm}, is defined in order to evaluate the potential actions to be assigned to a certain category [29]. A set of completely ordered categories, C = {C1, ..., Ch, ..., Cq}, is defined, in which C1 is the worst category and Cq is the best one, with q 2. Let B = {B1, ..., Bh, ..., Bq} denote a set of characteristic reference actions that define the categories, and Bh = {br h, r = 1, ... , mh} the subset of the reference actions that define the category Ch, such that mh 1 and h = 1,...,q (at least one mh is greater than one). Note that if mh = 1, for all h, then the considered method is the ELECTRE TRI-C [30]. Generally, the ELECTRE TRI-nC method takes into account more than one reference action to characterize each category. The two particular subsets of reference 3 actions, denoted B0 = b1 0 and Bq = b1 q+1 , contain a reference action, such that gj(b1 0) is the worst possible performance on criterion gj, and gj (b1 q+1) is the best possible performance on the same criterion gj , for all gj ∈ F, respectively. The worst and the best possible performances must be chosen such that, for any action a, one has gj(b1 0) < gj (a) < gj (b1 q+1) , for all gj ∈ F. The imperfect character of the data from the computation of the performances g j (a), ∀a ∈ A and ∀gj ∈ F, and the arbitrariness that can affect the definition of the criteria, are taken into account by introducing two thresholds, the preference threshold (cf. Definition 1) and the indifference threshold (cf. Definition 2). Even though these thresholds can vary according to the performances gj (a) and gj (a ), in this paper, we solely consider constant thresholds (for more details, see [31]). Let us consider that each criterion gj will be taken as a pseudo-criterion (cf. Definition 3). Definition 1 (Preference threshold). The preference threshold between two performances, denoted by p, is the smallest performance difference that when exceeded is judged significant of a strict preference in favour of the action having the best performance. Definition 2 (Indifference threshold). The indifference threshold between two performances, denoted by q, is the largest performance difference that is judged compatible with an indifference situation between two actions having different performances. Definition 3 (Pseudo-criterion with constant thresholds). A criterion g j is considered as a pseudo-criterion when two thresholds are associated to gj : an indifference threshold, qj , and a preference threshold, pj , such that pj qj 0. Let us consider two actions a and a , where gj (a) gj (a ), for a given criterion gj to be maximized. The following binary relations can be derived for each criterion: 1. |gj (a) − gj (a )| qj represents a non-significant advantage of one of the two actions over the other, meaning that a is indifferent to a according to gj , denoted aIja ; 2. gj (a) − gj(a ) > pj represents a significant advantage of a over a , meaning that a is strictly preferred to a according to gj, denoted aPja ; 3. qj < gj(a) − gj (a ) pj represents an ambiguous zone. There is a hesitation between indifference and strict preference, meaning that a is weakly preferred to a , denoted aQja . In what follows, it is needed the following notation: • C(aIa ) denotes the subset of criteria such that aIja ; • C(aP a ) denotes the subset of criteria such that aPja ; • C(aQa ) denotes the subset of criteria such that aQja . According to the criterion gj, “a outranks a ”, denoted aSja , if “a is at least as good as a ” on such a criterion gj. In order to construct a fuzzy outranking relation, it is necessary to introduce three concepts: concordance, nondiscordance, and a degree of credibility [32]. 4
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