Designing a hybrid model for clustering warehouse items and allocating them to storage locations

Management and warehousing operations are one of the essential parts of manufacturing and service organizations. Warehousing is one of the main components of the organization's activities, which has a high cost and deserves more attention from researchers in this field. This research has investigated the storage problem based on the clustering of items, taking into account all the factors affecting the storage of products in warehouse with bulky and varied products. The main objective of this research is to reduce Transport costs of collecting and delivering orders and more efficient use of storage space. The K-mean technique is used for solving the clustering problem and the Generalized Allocation mathematical programming model has been used to solve the problem of assigning categories of items to storage locations. This is an integer programming model with the goal of minimizing transportation costs of collecting and delivering orders.This research has been able to provide a comprehensive approach in clustering and allocation of items by identifying and considering the effective indexes and using the generalized allocation math planning model and formulating the actual conditions of the problem and solving it in an optimal way. Companies managers can use this model to reduce their inventory costs. Using of clustering in the allocation of storage sites to the warehouse items and then their mathematical modeling is innovation of present research. The proposed model was implemented at Mashhad Housebuilding Company. A number of simulated problems are solved from the actual problem with the GAMS software for validation.