<![CDATA[Selecting an optimal retail store location is a complex multi-criteria decision-making problem involving conflicting factors such as cost, accessibility, demographics, competition, and market potential. This study proposes an integrated approach combining the LODECI (Logarithmic Decomposition of Criteria Importance) method and the ERVD (Election based on Relative Value Distances) method to improve the objectivity, accuracy, and stability of decision results. LODECI is applied to determine criterion weights based on data distribution characteristics using logarithmic decomposition, reducing subjectivity in the weighting process. Subsequently, ERVD is utilized to evaluate and rank alternatives based on their relative distances to ideal and non-ideal solutions, enabling a more comprehensive assessment of each location. The research results show that the proposed integration effectively produces consistent and discriminative rankings, with Location F having a value of 0.9759 identified as the best alternative, followed by Location E with a value of 0.8461 and Location C with a value of 0.7882. Overall, the integration of LODECI and ERVD provides a robust decision-making framework that enhances reliability in selecting optimal retail store locations in complex and heterogeneous environments.]]>
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