Open Access

ARTICLE

Optimized Metaheuristic Strategies for Addressing the Multi-Picker Robot Routing Problem in 3D Warehouse Operations

Thi My Binh Nguyen^#, Thi Hoa Hue Nguyen^#, Thi Ngoc Huyen Do^*

School of Information Communications and Technology, Hanoi University of Industry, Hanoi, 100000, Vietnam

* Corresponding Authors: Thi Ngoc Huyen Do. Email: or or
# These authors contributed equally to this work as the first author

(This article belongs to the Special Issue: Particle Swarm Optimization: Advances and Applications)

Computers, Materials & Continua 2025, 84(3), 5063-5076. https://doi.org/10.32604/cmc.2025.064610

Received 19 February 2025; Accepted 18 June 2025; Issue published 30 July 2025

Abstract

Efficient warehouse management is critical for modern supply chain systems, particularly in the era of e-commerce and automation. The Multi-Picker Robot Routing Problem (MPRRP) presents a complex challenge involving the optimization of routes for multiple robots assigned to retrieve items from distinct locations within a warehouse. This study introduces optimized metaheuristic strategies to address MPRRP, with the aim of minimizing travel distances, energy consumption, and order fulfillment time while ensuring operational efficiency. Advanced algorithms, including an enhanced Particle Swarm Optimization (PSO-MPRRP) and a tailored Genetic Algorithm (GA-MPRRP), are specifically designed with customized evolutionary operators to effectively solve the MPRRP. Comparative experiments are conducted to evaluate the proposed strategies against benchmark approaches, demonstrating significant improvements in solution quality and computational efficiency. The findings contribute to the development of intelligent, scalable, and environmentally friendly warehouse systems, paving the way for future advances in robotics and automated logistics management.

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Keywords

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