Abstract
There has been much work in establishing a joint replenishment policy to minimize the total cost of inventory replenishment. Most of this work uses the indirect grouping method. Little research has been done with direct grouping methods. In this paper we develop an evolutionary algorithm (EA) that uses direct grouping to solve the joint replenishment problem (JRP). We test the EA and compare these results with results with the best available algorithm. The EA is shown to find a replenishment policy that incurs a lower total cost than the best available algorithm for some problem parameters.
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