Abstract
A convergent iterative aggregation procedure is described. The procedure makes use of both weight updating and reclustering of variables during the iterative process. Scope and purpose During the last two decades, aggregation/disaggregation has become an important tool in operations research, both for modeling purposes and for providing approximate solutions of large-scale mathematical programs. Methods for iteratively improving an aggregate model (iterative aggregation) have recently got a lot of interest. The present paper is a contribution in that context. A convergent iterative aggregation procedure is developed, which in principle can be used not only to find an approximate solution of a large-scale linear program, but also to find the exact solution.
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