An improved largest gap routing heuristic for order picking

The largest-gap policy is a routing heuristic for order picking systems. In this paper we develop an improved largest gap routing method. A simulation approach is used to demonstrate the superior performance of the improved largest gap routing over traditional largest gap. Moreover, this paper tests the performance impact of storage assignment rules on largest gap routings. Several scenarios with various order sizes and different item popularity proportions are tested. Monte-Carlo simulation is used to carry out the experiments. The numerical results from the computational analysis show that our improved largest gap routing always outperforms the traditional largest gap routing, i.e. for all order sizes. The effect is the most distinct when the order size is smaller. Finally the study demonstrates that the optimal storage assignment rule to be combined with largest gap routing is within-aisle storage.

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