N-RAWEC: Neutrosophic extension of RAWEC

Overview

Neutrosophic outranking/ranking: Single-Valued Neutrosophic Set (SVNS: T, I, F; T,I,F ∈ [0,1], T+I+F ≤ 3). Output typically utility (higher value = preferred).

Strengths

• •Method-specific: Neutrosophic outranking/ranking: Single-Valued Neutrosophic Set (SVNS: T, I, F; T,I,F ∈ [0,1], T+I+F ≤ 3)
• •Preserves single_valued_neutrosophic uncertainty through the pipeline rather than premature crispification at elicitation
• •Native group-decision support (multi-DM aggregation built into the pipeline)

Limitations

• •Assumes: Decision matrix entries are valid Single-Valued Neutrosophic numbers/tuples
• •Assumes: Underlying crisp method's compensation assumption holds in uncertain space
• •Assumes: All decision-maker(s) and experts use the same linguistic/uncertainty scale

Assumptions to verify

• •Decision matrix entries are valid Single-Valued Neutrosophic numbers/tuples
• •Underlying crisp method's compensation assumption holds in uncertain space
• •All decision-maker(s) and experts use the same linguistic/uncertainty scale

When not to use

• •Crisp data sufficient: use base RAWEC directly (avoid unnecessary uncertainty layer)
• •Aggregation operator (PFWA/PFOWA/etc.) not specified: output ambiguous

Edge cases

• •See F.steps and D.parameters for N-RAWEC-specific edge handling. recommendation_metadata.assumptions_to_verify also lists boundary conditions.

Common pitfalls

• •Hatalı: 'N-RAWEC bu varsayımı kontrol etmeden uygulamak'. Doğrusu: Decision matrix entries are valid Single-Valued Neutrosophic numbers/tuples
• •Hatalı: 'N-RAWEC bu varsayımı kontrol etmeden uygulamak'. Doğrusu: Underlying crisp method's compensation assumption holds in uncertain space
• •Hatalı: 'N-RAWEC bu varsayımı kontrol etmeden uygulamak'. Doğrusu: All decision-maker(s) and experts use the same linguistic/uncertainty scale
• •Hatalı: N-RAWEC'yi 'Crisp data sufficient' durumunda kullanmak: recommendation_metadata.not_recommended_when alternatif öneriyor.
• •Hatalı: N-RAWEC'yi 'Aggregation operator (PFWA/PFOWA/etc.) not specified' durumunda kullanmak: recommendation_metadata.not_recommended_when alternatif öneriyor.

Worked example

1. 1.Adım 1 (F1): NS karar matrisini oluştur, score fonksiyonu ile crispify: s_ij = (1+T-2I-F)/2.
2. 2.Adım 2 (F2): İki yönlü normalizasyon. Fayda: n_ij = s_ij/max_i(s_ij). Non-fayda: n*_ij = min_i(s_ij)/s_ij.
3. 3.Adım 3 (F3): Sapma toplamları. v_i = Σ w_j(1−n_ij), v*_i = Σ w_j(1−n*_ij).
4. 4.Adım 4 (F4): RAWEC indeksi. Q_i = (v*_i − v_i)/(v*_i + v_i). Aralık [−1,1].
5. 5.Adım 5 (F5): Q_i'ye göre azalan sıralama. Paper sonucu: A1=0.188 > A2=−0.024 > A4=−0.082 > A3=−0.193.

Commonly paired with

• •n_a + N-RAWEC (common)

How to cite