In most industries, most of the resources are spent investing in warehousing systems. The goal of warehouse management systems is to store and provide items appropriately, as well as make them easily accessible. There will be a disruption in the workflow and activities of that organization if the required items are not prepared on time. Specifically, in large industries like the steel industry, handling heavy and bulky items in storage presents a major challenge. In the case of warehousing and storage, loading and unloading are simple concepts that are often overlooked, and therefore a lack of proper planning will make it time-consuming and expensive. In addition, in warehouse systems, location assignment and arrangement is an iterative process that can have a significant impact on productivity. To improve warehousing processes, proper planning must be done in order to estimate the location assignment and schedule moves in the shortest time with the lowest cost possible. Multiple studies have been conducted on the problem of location assignment and retrieva‎l of products in the warehouse, as well as planning the transportation of products by different kinds of equipment, such as cranes, forklifts, and trucks. In this study, after reviewing and analyzing one of these problems, the location assignment and retrieving products in the warehouse were investigated, where the relocation of items is done with overhead cranes. The novelty of this study is that the weight of the items is different due to the limitation of their multilevel arrangement on top of each other, maintaining a safe distance between the cranes and observing their non-interference while moving, as well as the difference in speed of the cranes in the integrated location assignment and scheduling of overhead cranes. The objective function of the problem is to minimize the weighted total cost of allocating goods to the location, the penalty for violating the weight limit of items in a multilevel arrangement, and the sum of the delays created in the delivery of items. Two mathematical models with two consecutive and integrated solution approaches and a meta-heuristic algorithm were presented for solving this problem. The approach used in the meta-heuristic algorithm, a combination of genetic algorithms and refrigeration simulation, is problem-specific. In order to review and compare the performance of the proposed solution methods, in addition to examples of problems in the literature, a number of new examples have been designed and studied. The results of the solution show that out of 135 samples in the subject literature, 106 samples have been solved by a sequential mathematical model and 134 samples by a meta-heuristic algorithm. The integrated mathematical model was not able to solve these examples but was able to solve 20 of the 30 new examples of small-scale problems.

قاسم مصلحي

محمد رئيسي نافچي

مهدي علينقيان، مهدي ايرانپور مباركه