Multi-Type Equipment Selection and Quantity Decision Optimization in Intelligent Warehouse

Abstract

The distribution warehouse in the field of trade express is still dominated by manual operation, which has disadvantages in terms of accuracy, timeliness and economy. Choosing intelligent logistics equipment that can meet different operation links and reasonably setting the number of logistics equipment will help to improve the warehouse operation efficiency and reduce the warehouse operation cost. This paper proposes a multi-objective optimization method to solve this problem. We build a collaborative optimization model of multi-type logistics equipment selection and quantity decision to meet the whole process of intelligent distribution warehouse. The model takes the total equipment cost, return on investment and warehouse operation efficiency as the optimization objectives, and considers the constraints of workload satisfaction, equipment utilization, area occupation and selection rules. We use genetic algorithm combined with penalty function to solve the model. The example shows that this method can meet the requirements of intelligent warehouse operation, and realize the economic selection and quantity decision of logistics equipment for loading and unloading, storage, sorting, palletizing and film winding. And furthermore, it is concluded that the shelf access operation can be completed by both loading and unloading equipment, and the total cost is better.

Keywords

• Intelligent warehouse
• equipment selection
• equipment technical parameters
• quantity decision
• model configuration
• genetic algorithm