An Integrated Implementation Framework for Warehouse 4.0 Based on Inbound and Outbound Operations

Jizhuang Hui, Shaowei Zhi, Weichen Liu, Changhao Chu and Fuqiang Zhang ()
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Jizhuang Hui: Key Laboratory of Road Construction Technology and Equipment of MOE, Chang’an University, Xi’an 710064, China
Shaowei Zhi: Key Laboratory of Road Construction Technology and Equipment of MOE, Chang’an University, Xi’an 710064, China
Weichen Liu: Key Laboratory of Road Construction Technology and Equipment of MOE, Chang’an University, Xi’an 710064, China
Changhao Chu: Key Laboratory of Road Construction Technology and Equipment of MOE, Chang’an University, Xi’an 710064, China
Fuqiang Zhang: Key Laboratory of Road Construction Technology and Equipment of MOE, Chang’an University, Xi’an 710064, China

Mathematics, 2025, vol. 13, issue 14, 1-26

Abstract: Warehouse 4.0 adopts automation, IoT, and big data technologies to establish an intelligent warehousing system for efficient, real-time management of storage, handling, and picking. Addressing challenges like unreasonable storage allocation and inefficient order fulfillment, this paper presents an integrated framework that utilizes swarm intelligence algorithms and collaborative scheduling strategies to optimize inbound/outbound operations. First, for inbound processes, an algorithm-driven storage allocation model is proposed to solve stacker crane scheduling problems. Then, for outbound operations, a “1+N+M” mathematical model is developed, optimized through a three-stage algorithm addressing order picking and distribution scheduling. Finally, a case study of an industrial warehouse validates the proposed methods. The improved mayfly algorithm demonstrates excellent performance, achieving 64.5–74.5% faster convergence and 20.1–24.7% lower fitness values compared to traditional algorithms. The three-stage approach reduces order fulfillment time by 12% and average processing time by 1.8% versus conventional methods. These results confirm the framework’s effectiveness in enhancing warehouse operational efficiency through intelligent automation and optimized resource scheduling.

Keywords: Warehouse 4.0; implementation framework; improved mayfly algorithm; three-stage algorithm (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
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