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Placing items optimally to keep up with the fast-paced operations in e-commerce warehouses where humans and automation need to work in a symphony requires complex analysis and a well-defined strategy. This paper introduces a method that combines the strengths of the Slotting Location Assignment Problem (SLAP), Discrete Event Simulation (DES), and Mixed Integer Linear Programming (MILP) to address this issue. SLAP efficiently organizes products within the warehouse, DES models operational flows, including human and automated interactions, and MILP optimizes cost and efficiency, together providing a comprehensive solution to improve warehouse operations. Our results demonstrate notable improvements in operational efficiency and cost savings, indicating the potential of this integrated approach to enhance warehouse management practices in the e-commerce sector.

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Optimizing E-Commerce Warehouse Item Placement: A Three-Pronged Approach

  • 会议论文

  • 发表日期：

    2025年

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  • Aakash Bhatt,
  • Matthew Jurado,
  • Amith Tarigonda

摘要

Placing items optimally to keep up with the fast-paced operations in e-commerce warehouses where humans and automation need to work in a symphony requires complex analysis and a well-defined strategy. This paper introduces a method that combines the strengths of the Slotting Location Assignment Problem (SLAP), Discrete Event Simulation (DES), and Mixed Integer Linear Programming (MILP) to address this issue. SLAP efficiently organizes products within the warehouse, DES models operational flows, including human and automated interactions, and MILP optimizes cost and efficiency, together providing a comprehensive solution to improve warehouse operations. Our results demonstrate notable improvements in operational efficiency and cost savings, indicating the potential of this integrated approach to enhance warehouse management practices in the e-commerce sector.