Multi-target AGV task allocation optimization method

Through the multi-objective AGV task allocation optimization method combined with the improved Cheetah optimization algorithm, the problems of load imbalance and slow convergence in AGV task allocation are solved, more efficient and balanced task allocation is achieved, energy consumption is reduced, and system efficiency is improved.

CN120672069APending Publication Date: 2025-09-19NANJING TECH UNIV
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Patent Information

Application Number
CN202510784331.7
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-06-12
Publication Date
2025-09-19

AI Technical Summary

Technical Problem

Existing AGV task allocation methods have limitations in goal setting and fail to fully consider the AGV's driving distance cost and load balancing. Traditional optimization algorithms converge slowly or fall into local optimality in complex scenarios, and mathematical models do not adequately consider load balancing.

Method used

A multi-objective AGV task allocation optimization method is adopted. The task relationship matrix, data matrix and state matrix are generated through integer coding. Combined with the improved Cheetah optimization algorithm, the hyperbolic tangent step size and hierarchical simulated annealing strategy are introduced to optimize the total transportation distance, total energy consumption and load time deviation to generate the optimal task allocation plan.

Benefits of technology

It improves the balance and efficiency of task allocation, shortens task completion time, reduces system energy consumption, and improves the overall operating efficiency of the multi-AGV system.

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Abstract

The invention discloses a multi-target AGV task allocation optimization method, and the method comprises the steps: obtaining the position information, load information, task information and related constraint conditions of an AGV according to a manufacturing workshop environment and order production demands; performing initialization coding, and generating a task relation matrix, a task data matrix and an AGV state matrix by adopting integer coding for representing a task allocation scheme; constructing a multi-target AGV task allocation optimization model by taking the total transportation distance, the total energy consumption and the load time deviation as optimization targets; solving the multi-objective optimization model by adopting an improved hunting optimization algorithm to obtain an optimal task allocation optimization scheme; according to the method provided by the invention, the problems of load unbalance and the like in AGV task allocation can be effectively solved, the balance and efficiency of task allocation are improved, the task completion time is shortened, the energy consumption of the system is reduced, and the overall operation efficiency of the multi-AGV system is improved.
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