PHF-COPRAS - Probabilistic Hesitant extension of COPRAS

Overview

PHF-COPRAS extends COPRAS to handle Probabilistic Hesitant uncertainty. Criteria are split into beneficial and non-beneficial groups; weighted PHFE sums are computed, defuzzified via E[PHFE]=Σγ_k p_k, and aggregated using the COPRAS utility formula Q_i.

Output

utility, higher is better

Data

Hesitant, uncertainty tuples complete

Weights

Needs a weight source

Size

2+ alternatives, 3-10 criteria works best

Used for

Probabilistic Hesitant MCDM, MAGDM under epistemic uncertainty, evaluation with mixed beneficial/non-beneficial criteria

Look elsewhere when

Assumptions to verify

• All PHFE entries satisfy γ_k ∈ [0,1] and Σ p_k ≤ 1
• Criteria correctly partitioned into beneficial and non-beneficial
• Non-beneficial criteria sums s_i^- > 0 (no zero denominators)

Edge cases and pitfalls

• Ensure Σ p_k ≤ 1 for all PHFE entries before aggregation.

Works with

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