ELECTRE

One of the famous outranking methods is ELimination Et Choix Traduisant la REalité (ELECTRE). The ELECTRE is a family of MCDM methods containing ELECTRE I, ELECTRE II, ELECTRE III, ELECTRE IV, ELECTRE IS and ELECTRE TRI. The two main procedures in ELECTRE methods are: a multiple criteria aggregation procedure that builds one or several outranking relation(s) in order to compare each pair of alternatives in a comprehensive way; an exploitation procedure that can provide results based on how the problem is being addressed: choosing, ranking or sorting (Figueira, Mousseau, & Roy, 2005). ELECTRE I was first presented by B. Roy in 1968 (Roy, 1968), which triggered the development of other ELECTRE methods in order to deal with different types of decision problems: ELECTRE I is made for selection problems; ELECTRE TRI for assignment problems; ELECTRE II, III and IV for ranking problems. ELECTRE III is the most popular of the ELECTRE methods and a well-established partial ranking method, as it considers imprecise data and uncertainties (Kabir, Sadiq, & Tesfamariam, 2014) (Salminen, Hokkanen, & Lahdelma, 1998) and has many successful real-world applications such as environmental and energy management (Figueira, Mousseau, & Roy, 2005) (Karagiannidis & Papadopoulos, 2008), strategic planning (Kangas & Pykäläinen,

2001), water and wastewater management (Carriço, Covas, Almeida, Leitão, & Alegre, 2012).

4.4.1ELECTRE III Procedure in Theory

ELECTRE III constructs and exploits outranking relations between alternatives based on the weights of the criteria, the indifference, the preference and the veto thresholds provided by DMs. An outranking relation, where a outranks b (denoted by aSb), indicates that there are sufficient reasons to prove that a is at least as good as b and there are no important arguments disproving this (Roy, 1974). An outranking degree S(a, b) between

a and b measures the power of the statement “a outranks b”. It is a grade between 0 and

1, where the closer S(a, b) is to 1, the more a outranks b. This outranking degree S(a, b)

is computed with two perspectives: the concordance and the discordance of the statement that a outranks b. The concordance and discordance are evaluated separately while incorporating the decision maker’s preference on various (often conflicting) criteria. DMs need to provide the indifference and preference thresholds for calculating the concordance index and the veto threshold for the discordance index (Ishizaka & Nemery, 2013) (Tzeng & Huang, 2011).

All the criteria have to be maximized without loss of generality. Let’s define A = (a, b, c, … , n) to be a set of alternatives and n criteria, denoted as (g₁, g₂, … , g_n) for a MCDM problem; g_j(a) represents the performance or the outcome of the alternative a ∈ A for the criterion g_j; thus, the multi-criteria evaluation of alternative a is represented by the vector g(a) = (g₁(a), g₂(a), … , g_n(a)). Let q(g) and p(g) be the indifference and preference thresholds, respectively. For one pair of alternatives if g(a) ≥ g(b), then

𝑔(𝑎) ≻ 𝑔(𝑏) + 𝑝(𝑔(𝑏)) ⟺ 𝑎𝑃𝑏

𝑔(𝑎) + 𝑞(𝑔(𝑏)) ≺ 𝑔(𝑎) ≺ 𝑔(𝑏) + 𝑝(𝑔(𝑏)) ⟺ 𝑎𝑄𝑏 𝑔(𝑏) ≺ 𝑔(𝑎) ≺ 𝑔(𝑏) + 𝑞(𝑔(𝑏)) ⟺ 𝑎𝐼𝑏

where 𝑃 represents a strong preference, 𝑄 represents a weak preference, 𝐼 represents indifference.

With all the denotations introduced so far, the ELECTRE III procedure is presented below (Ishizaka & Nemery, 2013), (Roy & Bouyssou, 1993).

Step 1. The partial concordance index 𝐶_𝑗(𝑎, 𝑏) measures the statement “𝑎 outranks 𝑏” or “𝑎 is at least as good as 𝑏” on the specific criterion 𝑔_𝑗 and is calculated by

𝐶𝑗(𝑎, 𝑏) = { 0 𝑖𝑓 𝑔_𝑗(𝑏) − 𝑔_𝑗(𝑎) > 𝑝_𝑗 1 𝑖𝑓 𝑔_𝑗(𝑏) − 𝑔𝑗(𝑎) ≤ 𝑞𝑗 𝑝𝑗−(𝑔𝑗(𝑏)−𝑔𝑗(𝑎)) 𝑝𝑗−𝑞𝑗 𝑜𝑡ℎ𝑒𝑟𝑤𝑖𝑠𝑒 (4.8)

where 𝑝_𝑗, 𝑞_𝑗 (𝑝_𝑗 > 𝑞_𝑗) denote respectively the preference and indifference thresholds for criterion 𝑔_𝑗. The higher 𝐶_𝑗(𝑎, 𝑏), the more 𝑎 outranks 𝑏 on criterion 𝑔_𝑗. It is a value between 0 and 1. When 𝐶𝑗(𝑎, 𝑏) = 0, this means that the performance of alternative 𝑏 on

𝑔𝑗 is higher than the performance of 𝑎 augmented with preference threshold 𝑝𝑗 and there

is a strict preference for 𝑏 over 𝑎, i.e., 𝑎 does not outrank 𝑏; when it equals 1, the performance of 𝑏 on 𝑔_𝑗 is less than the performance of 𝑎 augmented with indifference threshold 𝑞_𝑗 and 𝑎 and 𝑏 are indifferent, i.e., 𝑎 is at least as good as 𝑏; when it is between 0 and 1, the performance of b on 𝑔_𝑗 is between the performance of 𝑎 augmented with indifference threshold 𝑞𝑗 and the performance of 𝑎 augmented with preference threshold

𝑝_𝑗 and 𝑏 is slightly preferred to 𝑎.

Step 2. The global concordance index 𝐶(𝑎, 𝑏) combines all the partial concordance indices on the different criteria together with their corresponding criteria weights. Hence,

it is the weighted sum of all the partial concordance indices and measures the concordance of the statement “a is at least as good as b” with all the criteria:

𝐶(𝑎, 𝑏) =∑ 𝑤𝑗𝐶𝑗(𝑎,𝑏)

𝑛 𝑗=1

∑𝑛𝑗=1𝑤𝑗

(4.9)

Step 3. The partial discordance index 𝑑_𝑗(𝑎, 𝑏) measures the discordance with the statement “𝑎 is at least as good as 𝑏” for criterion 𝑔_𝑗 and is computed as follows:

𝑑𝑗(𝑎, 𝑏) = { 1 𝑖𝑓 𝑔_𝑗(𝑏) − 𝑔_𝑗(𝑎) > 𝑣_𝑗 0 𝑖𝑓 𝑔_𝑗(𝑏) − 𝑔𝑗(𝑎) ≤ 𝑝𝑗 𝑔𝑗(𝑎)−𝑔𝑗(𝑏)−𝑝𝑗 𝑣𝑗−𝑝𝑗 𝑜𝑡ℎ𝑒𝑟𝑤𝑖𝑠𝑒 (4.10)

where 𝑣_𝑗 (satisfying 𝑣_𝑗 > 𝑝_𝑗) is the veto threshold for criterion 𝑔_𝑗. The higher the discordance index, the more discordant this statement. Its value is between 0 and 1. When

𝑑_𝑗(𝑎, 𝑏) = 1, it means that 𝑔_𝑗(𝑏) is higher than 𝑔_𝑗(𝑎) + 𝑣_𝑗, the difference between 𝑏 and

𝑎 exceeds the veto threshold and the statement “𝑎 is at least as good as 𝑏” is completely discordant. When 𝑑𝑗(𝑎, 𝑏) = 0, the statement “𝑎 is at least as good as 𝑏” is correct and

there is no discordance. When 𝑑_𝑗(𝑎, 𝑏) is between 0 and 1, the performance of 𝑏 is between 𝑔_𝑗(𝑎) + 𝑝_𝑗 and 𝑔_𝑗(𝑎) + 𝑣_𝑗; therefore, 𝑏 is slightly preferred to 𝑎.

Step 4. The outranking degree 𝑆(𝑎, 𝑏) is ready to be computed. It summarizes the concordance and discordance index into one measurement of the statement “𝑎 outranks 𝑏” as below: 𝑆(𝑎, 𝑏) { 𝐶(𝑎, 𝑏) 𝑖𝑓 𝐶(𝑎, 𝑏) ≥ 𝑑𝑗(𝑎, 𝑏) 𝐶(𝑎, 𝑏) ∙ ∏ [1−𝑑𝑗(𝑎,𝑏) 1−𝐶(𝑎,𝑏)] 𝑖𝑓𝐶(𝑎, 𝑏) < 𝑑𝑗(𝑎, 𝑏) (4.11)

Step 5. To obtain the ranking order of the alternatives, descending distillation and ascending distillation must first be determined, then the final ranking is obtained by combining both orders.

Descending distillation

• Determine the maximum value of the credibility index: 𝜆𝑚𝑎𝑥 = max 𝑆(𝑎, 𝑏);

• Calculate 𝜆 = 𝜆_𝑚𝑎𝑥− (0.3 − 0.15𝜆_𝑚𝑎𝑥). where -0.15 and 0.3 are the preset up values of distillation coefficients, 𝛼 and 𝛽;

• For each alternative 𝑎, determine its 𝜆-strength, i.e. the value of alternative 𝑏 with

𝑆(𝑎, 𝑏) > 𝜆;

• For each alternative 𝑎, determine its 𝜆-weakness, i.e. the value of alternative 𝑏 with

(1 − (0.3 − 0.15𝜆)) ∗ 𝑆(𝑎, 𝑏) > 𝑆(𝑏, 𝑎);

• For each alternative, determine its qualification, i.e. the difference between 𝜆- strength and 𝜆-weakness;

• The set of alternatives with the largest qualification is called the first distillate (𝐷₁); • If 𝐷1 has more than one alternative, repeat the process on the set 𝐷1 until all

alternatives have been classified. If there is a single alternative, then this is the most preferred one. Then continue with the original set of alternatives minus the set 𝐷₁, repeating until all alternatives have been classified;

Ascending distillation

• This is computed in the same way as descending distillation but the lowest qualification is used to form the first distillate.

ELECTRE III has many advantages for decision-making problems. Compared to ELECTRE II, the ELECTRE III implements a structured procedure to extract the relationship between decision alternatives. Its main advantage is that ELECTRE III is an interactive method, which means DMs directly participate in the decision process. Another advantage is that ELECTRE III avoids compensation between criteria and any

normalization process, which distorts the original data; the drawback is that it requires various technical parameters such that it is not always easy to fully understand them (Ishizaka & Nemery, 2013).