Abstract: A system and method includes a computer network system configured to provide output to a plurality of distribution centers for a retailer, an inputting system configured to allow ordering of a quantity of an item from a vendor having a minimum order quantity (MOQ) and vendor pack size for the item, an allocation system configured to allocate the order quantity based on an allocation policy including specific distribution centers and allocation percentages associated with the specific distribution centers, and an inventory allocation tool (IAT) configured to receive the allocation policy, order quantity, MOQ, and vendor pack size as inputs, optimizes distribution of the order quantity among the specific distribution centers so that MOQ and vendor pack size according to the allocation policy are respected, and outputs an executable purchase order over the computer network system for each specific distribution center.

Abstract: A method of determining an inventory mirroring plan for a set of distinct items in a fulfillment network. The fulfillment network can include a plurality of distribution centers. The method can include determining, for each distinct item of the set of distinct items and for each demand zone of a set of demand zones, a location-specific demand. The method also can include determining, for each of a number of clusters ranging from 1 to a predetermined maximum number of clusters, a k-cluster profile that partitions the plurality of distribution centers in the fulfillment network into k distribution center clusters. The method further can include determining, for each of the number of clusters and for each demand zone of the set of demand zones, a closest distribution center cluster of the k distribution center clusters that is nearest to the demand zone.

Abstract: In many embodiments, a method can comprise receiving an online order for an item from a user and receiving an estimate of a network stockout cost of a network associated with the item, the network comprising at least a first fulfillment center and a second fulfillment center. In some embodiments, the method further can comprise updating a first local stockout cost and updating a second local stockout. In various embodiments, the method further can comprise executing a first stocking plan for the item at the first fulfillment center based at least in part on the updated first local stockout cost, executing a second stocking plan for the item at the second fulfillment center based at least in part on the updated second local stockout cost, and selecting the first fulfillment center to deliver the item pursuant to the online order from the user based at least in part on the first stocking plan. Other embodiments of related methods and systems are also provided.

Abstract: A system and method for selecting an deployment of goods for shipping purposes is presented. An affinity network representing the deployment of goods is created. A first and second set of goods in the affinity network are created, the first set of goods representing an initial set of goods to be placed in a first location and the second set of goods representing a set of goods that are constrained to be placed in a second location. An objective function is iteratively operated to determine an optimum deployment of goods between the first location and second location. Other embodiments are disclosed.

Abstract: Various examples of methods and systems for prioritizing identifier in cost-based inventory allocation are described. In one implementation, a method may determine a shipping cost sensitivity of each identifier of a plurality of identifiers of a plurality of items in an inventory, the shipping cost sensitivity of each identifier related to sales volume, billable weight and shipping zone associated with the respective identifier. The method may also rank the plurality of identifiers based at least in part on the shipping cost sensitivity of each identifier. The method may further determine an order of allocation of the inventory of the plurality of items based at least in part on the ranking of the plurality of identifiers.

Abstract: Various examples of methods and systems for prioritizing identifier in cost-based inventory allocation are described. In one implementation, a method may determine a shipping cost sensitivity of each identifier of a plurality of identifiers of a plurality of items in an inventory, the shipping cost sensitivity of each identifier related to sales volume, billable weight and shipping zone associated with the respective identifier. The method may also rank the plurality of identifiers based at least in part on the shipping cost sensitivity of each identifier. The method may further determine an order of allocation of the inventory of the plurality of items based at least in part on the ranking of the plurality of identifiers.

Abstract: In many embodiments, a method can comprise receiving an online order for an item from a user and receiving an estimate of a network stockout cost of a network associated with the item, the network comprising at least a first fulfillment center and a second fulfillment center. In some embodiments, the method further can comprise updating a first local stockout cost and updating a second local stockout. In various embodiments, the method further can comprise executing a first stocking plan for the item at the first fulfillment center based at least in part on the updated first local stockout cost, executing a second stocking plan for the item at the second fulfillment center based at least in part on the updated second local stockout cost, and selecting the first fulfillment center to deliver the item pursuant to the online order from the user based at least in part on the first stocking plan. Other embodiments of related methods and systems are also provided.

Abstract: A system and method for selecting an deployment of goods for shipping purposes is presented. An affinity network representing the deployment of goods is created. A first and second set of goods in the affinity network are created, the first set of goods representing an initial set of goods to be placed in a first location and the second set of goods representing a set of goods that are constrained to be placed in a second location. An objective function is iteratively operated to determine an optimum deployment of goods between the first location and second location. Other embodiments are disclosed.

Abstract: A system and method includes a computer network system configured to provide output to a plurality of distribution centers for a retailer, an inputting system configured to allow ordering of a quantity of an item from a vendor having a minimum order quantity (MOQ) and vendor pack size for the item, an allocation system configured to allocate the order quantity based on an allocation policy including specific distribution centers and allocation percentages associated with the specific distribution centers, and an inventory allocation tool (IAT) configured to receive the allocation policy, order quantity, MOQ, and vendor pack size as inputs, optimizes distribution of the order quantity among the specific distribution centers so that MOQ and vendor pack size according to the allocation policy are respected, and outputs an executable purchase order over the computer network system for each specific distribution center.

Abstract: Various examples of methods and systems for prioritizing identifier in cost-based inventory allocation are described. In one implementation, a method may determine a shipping cost sensitivity of each identifier of a plurality of identifiers of a plurality of items in an inventory, the shipping cost sensitivity of each identifier related to sales volume, billable weight and shipping zone associated with the respective identifier. The method may also rank the plurality of identifiers based at least in part on the shipping cost sensitivity of each identifier. The method may further determine an order of allocation of the inventory of the plurality of items based at least in part on the ranking of the plurality of identifiers.

Abstract: A method of determining an inventory mirroring plan for a set of distinct items in a fulfillment network. The fulfillment network can include a plurality of distribution centers. The method can include determining, for each distinct item of the set of distinct items and for each demand zone of a set of demand zones, a location-specific demand. The method also can include determining, for each of a number of clusters ranging from 1 to a predetermined maximum number of clusters, a k-cluster profile that partitions the plurality of distribution centers in the fulfillment network into k distribution center clusters. The method further can include determining, for each of the number of clusters and for each demand zone of the set of demand zones, a closest distribution center cluster of the k distribution center clusters that is nearest to the demand zone.

Abstract: A method for computing a demand probability for one or more products. The method can include establishing one or more similarities between one or more regional segments and combining the one or more regional segments into one or more clusters based on the one or more similarities. The method can also include executing one or more computer instructions on one or more processors for determining a demand probability distribution across the one or more clusters for the one or more products based on historical data and delivering the one or more products to the one or more clusters based on the demand probability distribution.

Abstract: A method of limiting cross-channel splits in a supply chain network based at least in part on an additional distinct item capacity of a first channel. The method can include determining a target order set from historical order data, which can include orders each having at least one first item that was fulfilled from the first channel and at least one second item that was fulfilled from a second channel in the supply chain network that is different from the first channel. The method also can include determining, for each order of the target order set, a non-owned item combination, which can include distinct items that were not fulfilled from the first channel when the order was fulfilled. The method further can include determining a non-owned item combination set and a split item set. The method also can include determining, for each of the non-owned item combinations, a combination profit.

Abstract: A computer-implemented method is disclosed for optimizing a flow network. In the method, a computer system may obtain first data characterizing supply sites, demand sites, and lanes of a distribution network. The computing system may also obtain second data characterizing supply and demand for an item distributed within the distribution network. Using the first and second data, a computer system may determine a maximum possible flow of the item within the distribution network. Subsequently, the computer system may use the maximum possible flow as a benchmark in determining which lanes of the distribution network are required to achieve the maximum possible flow and which lanes of the distribution network are redundant lanes. From among a remaining set of required, non-redundant lanes, a computer system may select a lowest cost solution for achieving the maximum possible flow.