Research on design and optimization of green warehouse system based on case analysis

Abstract

Climate warming is a common concern around the world. Achieving carbon reduction within the warehouse is a problem that needs to be addressed in the layout of the green warehouse. This paper builds a soft path model to study the impact of the improved systematic layout planning method on carbon reduction in warehouses from a low carbon economy perspective. This paper considers two main warehouse layout factors: logistic and nonlogistic factors. A dual-objective warehouse optimization model is designed by quantifying the relationship between logistic and nonlogistic factors, and the heuristic algorithm is used for simulation optimization. Finally, the functional warehouse area is comprehensively evaluated using fuzzy constraint theory. The results show that the established soft path solution optimizes and improves logistics activities such as internal warehouse layout, material handling strategy, and warehouse management by comparing with the traditional layout method. The efficiency of warehouse operation, warehouse space utilization, and energy are improved. The goal of reducing carbon footprints from the warehouse is thus achieved. It is demonstrated that the soft path solution can minimize warehouse carbon emissions and generate positive synergy in terms of environmental impact. This study enriches green warehouse layout design procedures and provides a facility optimization technique with the potential to minimize warehouse carbon emissions, which can help planners combine other green warehouse management tools to optimize operations and reduce carbon in daily practice.