Local WLC — neighbourhood-adaptive weighted linear combination
LOCAL-WLC (Local WLC — neighbourhood-adaptive weighted linear combination) is a ranking multi-criteria decision-making (MCDM) method introduced by Malczewski, J. in 2011. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.
Key highlights
- Follows a transparent, reproducible computational procedure that can be audited step by step.
- Handles multiple criteria of differing scales and units within a single decision matrix.
Intuition
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How it works
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When to use it
V(A^q_i) reflects both criterion performance and how important each criterion is within the alternative's spatial neighbourhood. An alternative that excels on a criterion which is locally highly variable (high r^q_k/r_k) benefits more than one that excels on a criterion where all neighbours are similar. Always inspect the local weight table (output G.local_weights) and the range-ratio table (output G.range_ratios) to understand what drove the ranking in each neighbourhood.
Strengths & limitations
- Follows a transparent, reproducible computational procedure that can be audited step by step.
- Handles multiple criteria of differing scales and units within a single decision matrix.
- May exhibit rank reversal when alternatives are added to or removed from the set.
- Assumes full compensation — a strong score on one criterion can offset a weak score on another.
Common pitfalls
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Sources
- 1.Malczewski, J. (2011). Local weighted linear combination. Transactions in GIS
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Cite this page
ScholarGate. (2026, June 2). LOCAL-WLC. ScholarGate. https://scholargate.app/decision-making/local-wlc