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This paper addresses the spatial distribution of mammography equipment through a capacitated location-allocation model that incorporates inequality aversion based on the Kolm-Pollak equally distributed equivalent. The model minimizes an exponential aggregation of demand-weighted social access costs, placing a stronger penalty on high costs and thereby prioritizing underserved regions without requiring additional equity constraints or a multiobjective formulation. To solve the resulting problem, we propose an outer-approximation method accelerated by tabu search. Computational experiments compare the proposed approach with the classical p-median formulation and with the solution of the exponential cone formulation obtained using a state-of-the-art commercial solver. The results show that the proposed approach yields more equitable solutions with limited efficiency losses, while the outer-approximation algorithm outperforms the direct solution of the exponential cone formulation in most test instances.
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