Computer Science

Computer Science ›› 2026, Vol. 53 ›› Issue (4): 88-100.doi: 10.11896/jsjkx.250200035

• Interdisciplinary Integration of Artificial Intelligence and Theoretical Computer Science • Previous Articles     Next Articles

Multi-objective Intelligent Warehousing Path Planning Based on Conflict Free Path Algorithm

GONG Jing1,2, YANG Yufa3, ZHENG Yifan3, SUN Zhixin1,2   

  1. 1 Engineering Research Center of Post Big Data Technology and Application of Jiangsu Province, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
    2 Research and Development Center of Post Industry Technology of the State Posts Bureau(Internet of Things Technology), Nanjing University of Posts and Telecommunications, Nanjing 210003, China
    3 Modern Postal College, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
  • Received:2025-02-10 Revised:2025-06-05 Online:2026-04-15 Published:2026-04-08
  • About author:GONG Jing,born in 1977,Ph.D,associate professor.Her main research in-terests include data network security technology,data mining technology and modern logistics technology.
    SUN Zhixin,born in 1964,Ph.D,professor,doctoral supervisor.His main research interests include the theory and technology of network communication,computer network and security.
  • Supported by:
    National Natural Science Foundation of China(62272239),Jiangsu Agriculture Science and Technology Innovation Fund(CX(22)1007) and Guizhou Provincial Key Technology R & D Program([2023]272).

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Abstract: The research on warehouse path planning plays a crucial role in intelligent warehousing,as reasonable path planning can effectively avoid AGV path conflicts and improve in-warehouse transportation efficiency.To address the limitations of simplistic warehouse layouts and the lack of effective path conflict resolution strategies for complex environments,this paper proposes a multi-objective AGV path planning algorithm based on a coordinate reservation table and conflict classification.Firstly,a grid-based fish-bone layout scheme for intelligent warehousing is constructed.A distance calculation model between storage nodes is developed using a partition mechanism,forming a unidirectional directed graph representing the storage path network.Next,an AGV coordinate reservation table and a path conflict classification method are established,followed by the formulation of a hierarchical conflict resolution strategy.Then,a multi-objective intelligent warehouse path planning model is constructed with the goals of minimizing the total transportation distance,minimizing the maximum single transportation distance,and minimizing the waiting time for conflict resolution.Based on the proposed conflict resolution mechanism,a set of mutation operators and crossover operations is designed under an evolutionary genetic search framework.On top of the preference-guided multi-objective combinatorial optimization(P-MOCO) algorithm,an enhanced algorithm named CF-MOWVRP is proposed.This algorithm integrates preference-driven stochastic strategies,multi-objective dimensionality reduction,and reinforcement learning to obtain approximate Pareto-optimal solutions to the conflict-free multi-objective path planning model.Experimental results demonstrate that the proposed algorithm achieves faster convergence and better solution quality,successfully resolves AGV path conflicts,and provides feasible conflict-free path planning solutions.

Key words: Path planning, Intelligent warehousing, Path conflict, Multi objective optimization, Reinforcement learning, AGV

CLC Number: 

  • TP242
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