This paper discusses the problem of predicting the length of Traveling Salesman Problem (TSP) tour in dynamic and uncertain environments. Our findings, which are guided by extensive simulation runs, provide statistical estimations for the tour length under different scenarios. One of the applications that can benefit from these estimates includes warehouse order picking, which has seen increased importance due to online shopping. The utility of statistical estimates for TSP tour length for order picking is demonstrated on a common warehouse layout.
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