The part arrangement optimizing method of the present invention is a part arranging method capable of obtaining part arrangements having smaller evaluation function values rapidly, and the method improves block arrangements so that evaluation function values such as total route lengths become small as much as possible by replacing plural blocks or block sets to determine the arrangements of parts on the basis of the arrangements of the blocks. Furthermore, as aforementioned improving method of the blocks, such a method as assigns expected positional coordinate to each part and arranges a block to a block arranging position near to the expected positional coordinate while renewing the expected positional coordinate so as to be located at the position where the evaluation function value becomes smaller.
The present invention relates to inventory management systems and processes at the retail, wholesale and/or distributor level. The present invention particularly involves a system, method and article of manufacture that optimizes inventory and merchandising shelf space utilization based upon cost and lost sales, with or without considering physical space constraints. In an exemplary embodiment, the system includes a bank of memory, a processor, an input and an output, and a computer program. The system optimizes inventory or store facings using various data and extrapolated computations. The system optimizes inventory using facing optimization which is an approach to shelf inventory management that minimizes the sum of expected annual cost of lost sales and expected annual inventory holding cost. The process of facing optimization requires the assimilation of relevant data for each particular item to be evaluated. The data to be collected include store-level point-of-sale (a.k.a., POS) data, frequency of shelf replenishment, shelf-level order cycle time, space available, space required per SKU, number of units per facing, cost to the retailer of one unit of SKU, price they sell it for, the inventory holding cost factor, and the unit cost of a lost sale. Store-level POS is used to measure the mean of daily sales and the variability of daily sales (a.k.a., standard deviation of demand). The system evaluates these variables when determining the optimal solution for an unconstrained space or a constrained space of a particular facility.
