| CPC G06Q 10/0832 (2013.01) [G06Q 10/0875 (2013.01); B65G 1/16 (2013.01); G06Q 10/04 (2013.01); G06Q 30/0283 (2013.01)] | 9 Claims |
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1. A system for carton optimization, comprising:
at least one computer with computer-readable program code stored thereon, the at least one computer in communication with a carton-making machine, a computerized warehouse management system, and a data store, the data store in communication with the computerized warehouse management system, and the data store storing goods order data associated with past goods orders received by a shipper;
wherein the computer-readable program code is configured to:
receive from the data store a data sample containing a number of the past goods orders;
perform a pre-order cubing adjustment operation to calculate a reduced number of feasible cartons that will fit the goods orders contained in the data sample;
perform an order cubing operation to calculate a best fitted carton for each goods order contained in the data sample, which results in a set of optimally fitted cartons for all goods orders in the data sample;
perform an optimal carton set searching step by applying a specialized genetic algorithm with the reduced number of feasible cartons resulting from the previous pre-order cubing adjustment operation serving as an input;
identify an optimized carton set containing a plurality of cartons of different dimensions that collectively fit all goods orders in the data sample;
calculate a number/percent of future orders that will use each carton size within the optimized carton set;
instruct the automated carton-making machine to produce various shipping cartons of the optimized carton set in the predicted required quantities thereof; and
wherein the size of the data sample is based on an equation selected from the group consisting of:
 where W is in the range of sample values, and
 where E is the maximum error, σ is the standard deviation, and Z is the critical cutoff value, resulting in a 1−α confidence level that the sample mean will fall within the maximum error E around the population mean.
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