Abstract: The present invention generally relates to a method, apparatus, and computer program product for optimizing article or bin location in an automated storage device to increase the efficiency of article retrieval in filling an order. Methods of example embodiments may determine a number of touches of each of a plurality of bins of a storage system, where the touches are calculated over a predetermined period of time, identify a bin with more touches than a bin at a first location, where the bin with more touches is at a second location, and direct the bin with more touches than the bin at the first location to be swapped with the bin at the first location. Identifying a bin with more touches may include identifying a bin with a number of touches that exceeds the number of touches of the bin in the first location by a predetermined amount.

Abstract: The present invention generally relates to a method, apparatus, and computer program product for optimizing article or bin location in an automated storage device to increase the efficiency of article retrieval in filling an order. Methods of example embodiments may determine a number of touches of each of a plurality of bins of a storage system, where the touches are calculated over a predetermined period of time, identify a bin with more touches than a bin at a first location, where the bin with more touches is at a second location, and direct the bin with more touches than the bin at the first location to be swapped with the bin at the first location. Identifying a bin with more touches may include identifying a bin with a number of touches that exceeds the number of touches of the bin in the first location by a predetermined amount.

Abstract: Systems and methods for detecting diversion in drug dispensing transactions are provided. The systems and methods described provide an integrated platform for collecting and analyzing data that describes a user's drug dispensing transactions and determines a diversion score for the user that indicates the relative severity of the user's diversion activities. The diversion score may be weighted to reflect the relative importance of a respective category of diversion activity to the identification of drug diverters with respect to other categories. Furthermore, in determining a user's diversion score, the user's transaction data may be compared with transaction data regarding the user's peers. In this way, for example, high diversion scores may indicate a high occurrence of suspicious activity, and users having high diversion scores may be further monitored and investigated to determine whether the particular user is indeed diverting drugs for illegitimate use.