Analysis of centroid aggregation for the Euclidean distance p-median problem

Demand data aggregation results in loss of information and thereby induces errors in the locational decision being made, both in the facility location con®gurations (optimality error) and in the computed value of the objective function (cost error). The aggregation e€ect is quite problem-speci®c, depending on the aggregation scheme used and on the demand pattern. In this paper, we perform a theoretical analysis for the centroid aggregation e€ect on the Euclidean distance p-median location problem. We study the worst case and average case errors, and in the multi-facility location model Source C error is closely examined. The results of the paper are illustrated via numerical examples and some empirical ®ndings of previous work are interpreted using our analytical results. Ó 1999 Elsevier Science B.V. All rights reserved.