SPOTIS: Stable Preference Ordering Towards Ideal Solution

Overview

Normalised distance to ideal (rank-reversal free). Output typically utility (higher value = preferred).

Strengths

• •Method-specific: Normalised distance to ideal (rank-reversal free)

Limitations

• •Assumes: Criteria preferences are independent (no synergistic interactions)
• •Assumes: Compensation is acceptable: high score on one criterion can offset low on another
• •Assumes: Decision matrix is complete (no missing values)

Assumptions to verify

• •Criteria preferences are independent (no synergistic interactions)
• •Compensation is acceptable: high score on one criterion can offset low on another
• •Decision matrix is complete (no missing values)

When not to use

• •Criteria strongly correlated → consider DEMATEL/ANP for interdependence
• •Non-compensatory preferences → consider outranking (ELECTRE/PROMETHEE)

Edge cases

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

Common pitfalls

• •Hatalı: 'SPOTIS bu varsayımı kontrol etmeden uygulamak'. Doğrusu: Criteria preferences are independent (no synergistic interactions)
• •Hatalı: 'SPOTIS bu varsayımı kontrol etmeden uygulamak'. Doğrusu: Compensation is acceptable: high score on one criterion can offset low on another
• •Hatalı: 'SPOTIS bu varsayımı kontrol etmeden uygulamak'. Doğrusu: Decision matrix is complete (no missing values)
• •Hatalı: SPOTIS'yi 'Criteria strongly correlated → consider DEMATEL/ANP for interdependence' durumunda kullanmak: recommendation_metadata.not_recommended_when alternatif öneriyor.
• •Hatalı: SPOTIS'yi 'Non-compensatory preferences → consider outranking (ELECTRE/PROMETHEE)' durumunda kullanmak: recommendation_metadata.not_recommended_when alternatif öneriyor.

Worked example

1. 1.Adım 1 (F1): Step 1: Define bounds S_j^{min}, S_j^{max} per criterion (Stable Preference). Formül: S_{j} = [S_{j}^{\min}, S_{j}^{\max}],\quad S_{j}^{*}=S_{j}^{\max}\ (J^{+})\ \text{or}\ S_{j}^{\min}\ (J^{-}) Anchor: Dezert 2020, p.3 Eq.(1)
2. 2.Adım 2 (F2): Step 2: Normalised distance from ideal δ_ij = |x_ij − S_j*| / (S_j^max − S_j^min). Formül: \delta_{ij} = \dfrac{|x_{ij} - S_{j}^{*}|}{S_{j}^{\max} - S_{j}^{\min}} Anchor: Dezert 2020, p.3 Eq.(2)
3. 3.Adım 3 (F3): Step 3: Weighted aggregated distance D_i = Σ w_j δ_ij; ASCENDING ranking (smaller is better). Formül: D_{i} = \sum_{j=1}^{n} w_{j}\,\delta_{ij},\quad \text{rank ascending} Anchor: Dezert 2020, p.3 Eq.(3)

Commonly paired with

• •AHP + SPOTIS (high)
• •BWM + SPOTIS (high)
• •ENTROPY + SPOTIS (high)
• •CRITIC + SPOTIS (high)
• •SWARA + SPOTIS (high)

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