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이웃 적응형 가중 평균법 (neighbourhood-adaptive Ordered Weighted Averaging)×기준 제거 효과 기반 방법×
분야의사결정의사결정
계열MCDMMCDM
기원 연도20142021
창시자Malczewski, J.; Liu, X.Keshavarz Ghorabaee, M., Amiri, M., Zavadskas, E. K., Antucheviciene, J., Turskis, Z.
유형Range-sensitive neighbourhood-local OWA — criterion weights w^q_k scale with local criterion variance within each spatial neighbourhood; order weights λ_k remain global, encoding a single risk attitude applied everywhereRemoval-effect objective weighting (logarithmic utility)
원전Malczewski, J., Liu, X. (2014). Local ordered weighted averaging in GIS-based multicriteria analysis. Annals of GIS DOI ↗Keshavarz Ghorabaee, M., Amiri, M., Zavadskas, E. K., Antucheviciene, J., Turskis, Z. (2021). Determination of objective weights using a new method based on the removal effects of criteria (MEREC). Informatica DOI ↗
별칭
관련88
요약LOCAL-OWA (neighbourhood-adaptive Ordered Weighted Averaging) is a ranking multi-criteria decision-making (MCDM) method introduced by Malczewski, J.; Liu, X. in 2014. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.MEREC (MEthod based on the Removal Effects of Criteria) is a weight objective multi-criteria decision-making (MCDM) method introduced by Keshavarz Ghorabaee, M., Amiri, M., Zavadskas, E. K., Antucheviciene, J., Turskis, Z. in 2021. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.
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