HF-ELECTRE-I
HF-ELECTRE I - Kararsız Bulanık ELECTRE I (Chen-Xu-Xia 2015)
Kararsız Bulanık Elemanlar için uyum/uyumsuzluk dışlama sıralaması; skor fonksiyonu ve sapma derecesine dayalı HF uyum ve uyumsuzluk indeksleri; seçim için güvenilirlik matrisi.
Formül adımları
Analiz motorunun yöntem bildirimindeki (manifest F.steps) adımlar; raporlardaki formüllerle aynı kaynaktır.
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Collect HFE evaluations h_ij from a group of DMs. Specify criterion importance weights w_k and the four relative weights for strong/weak concordance and discordance sets.
LaTeX
H = [h_ij]_{m×n}; w = (w_1,...,w_n)^T with Σw_k=1; ω = (ω_C, ω'_C, ω_D, ω'_D)^T for concordance/discordance set weights -
Score = mean membership value; deviation = standard deviation of membership values. If two HFEs have different lengths, extend the shorter by repeating its minimum value (pessimistic rule).
LaTeX
s(h_ij) = (1/|h_ij|)·Σ_{γ∈h_ij} γ; σ(h_ij) = sqrt((1/|h_ij|)·Σ_{γ∈h_ij}(γ − s(h_ij))²) -
For each ordered pair (i,j) with i≠j: J^c_ij contains criteria where A_i outperforms A_j with higher consistency (lower deviation); J'^c_ij contains criteria where A_i scores at least as well but with lower or equal consistency.
LaTeX
J^c_ij = {k | s(h_ik) ≥ s(h_jk) AND σ(h_ik) < σ(h_jk)} (Eq.4.19); J'^c_ij = {k | s(h_ik) ≥ s(h_jk) AND σ(h_ik) ≥ σ(h_jk)} (Eq.4.20) -
J^d_ij collects criteria where A_i is inferior to A_j with lower consistency (more discordant); J'^d_ij collects criteria where A_i is inferior but has higher consistency (weak discordance).
LaTeX
J^d_ij = {k | s(h_ik) < s(h_jk) AND σ(h_ik) ≥ σ(h_jk)} (Eq.4.21); J'^d_ij = {k | s(h_ik) < s(h_jk) AND σ(h_ik) < σ(h_jk)} (Eq.4.22) -
The concordance index c_ij ∈ [0,1] measures how much A_i outranks A_j. Weighted sum of criteria in the concordance sets divided by total weights. c_ii is undefined (diagonal excluded).
LaTeX
c_ij = (ω_C·Σ_{k∈J^c_ij} w_k + ω'_C·Σ_{k∈J'^c_ij} w_k) / Σ_{k=1}^{n} w_k; C = [c_ij]_{n×n} (Eqs.4.23-4.24) -
d_ij measures worst-case weighted distance on discordant criteria relative to maximum distance across all criteria. Distance d(·,·) is the HFS distance measure (Def.2.2 in book).
LaTeX
d_ij = max{ω_D·d(w_k h_ik, w_k h_jk): k∈J^d_ij, ω'_D·d(w_k h_ik, w_k h_jk): k∈J'^d_ij} / max_{k=1..n} d(w_k h_ik, w_k h_jk); D = [d_ij]_{n×n} (Eqs.4.25-4.26) -
Threshold c̄ is the average concordance index over all ordered pairs. f_ij=1 indicates A_i concordance-dominates A_j.
LaTeX
c̄ = Σ_{i=1,j≠i}^{n} c_ij / (n(n−1)); f_ij = 1 if c_ij ≥ c̄ else 0; F = [f_ij] (Eqs.4.27-4.29) -
Threshold d̄ is the average discordance index. q_ij=1 indicates A_i is NOT strongly discordant relative to A_j (i.e., discordance is within acceptable range).
LaTeX
d̄ = Σ_{i=1,j≠i}^{n} d_ij / (n(n−1)); q_ij = 1 if d_ij ≤ d̄ else 0; Q = [q_ij] (Eqs.4.30-4.32) -
p_ij=1 iff A_i concordance-dominates A_j AND is not excessively discordant w.r.t. A_j. Interpretation: p_ij=1 → A_i preferred to A_j; p_ij=p_ji=1 → indifferent; p_ij=p_ji=0 → incomparable.
LaTeX
P = F ⊗ Q; p_ij = f_ij · q_ij (Eqs.4.33-4.34) -
Identify the kernel (undominated set) from the aggregation dominance graph. Alternatives in the kernel are the recommended choices.
LaTeX
Draw directed graph from P: edge A_i→A_j iff p_ij=1. Kernel = set of alternatives not dominated by any other selected alternative.
Yöntem ayrıntıları kaynak kütüphanedeki özgün (İngilizce) metindir.
Sezgi
Sonucu okuma: HF-ELECTRE-I ranks alternatives based on performance scores. Higher score = better rank.