Abstract
We present an improved decomposition algorithm for solving the global optimization problem where X, Y are polyhedral convex sets in Rp, Rq respectively and f is a continuous concave function over X (p is assumed to be small as compared to n = p+q). This algorithm is a variant of Tuy's decomposition algorithm, with, however, a major improvement in the construction of the linear subproblems to be solved in each step. To take advantage of this improvement, the lay-out planning problem with concave cost and the case of bounded variable y are also considered.
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