Dynamic scheduling method and system of orbital automatic guided vehicles based on harmony search

Abstract

The invention provides a dynamic scheduling method and system of orbital automatic guided vehicles based on harmony search. The method comprises the steps of: setting initial state parameters, variousprocessing parameters and optimization parameters of various numerically-controlled machine tools; encoding the serial numbers of the numerically-controlled machine tools served by an RGV trolley forN times in the future as a harmony vector with a length N, constructing a plurality of harmony vectors according to a specified harmony vector length and an encoding scheme to form an initial harmonymemory vault, and calculating a fitness value of each harmony vector in the harmony memory vault; randomly taking values within a variable value taking range to form a new harmony, or selecting the harmony in HM and performing disturbance and fine tuning to calculate a new harmony, and calculating the fitness value of the new harmony; updating the harmony memory vault according to the fitness value of the new harmony; and judging whether the current number of iterations reaches the maximum number of iterations, and if so, selecting a harmony with the best quality from the harmony memory vaultfor decoding, and the using the decoding result as the process in which the RGV trolley sequentially provide services for the corresponding numerically-controlled machine tools according to the sequence of the serial numbers of the numerically-controlled machine tools in the harmony vector, or otherwise, returning to the step of forming the new harmony.

Description

technical field [0001] The present disclosure relates to the field of intelligent control, in particular to a method and system for dynamic scheduling of track-type automatic guided vehicles based on harmony search. Background technique [0002] The statements in this section merely provide background information related to the present disclosure and do not necessarily constitute prior art. [0003] The intelligent production system is usually composed of rail-type automatic guided vehicles, RGV linear rails, multiple CNC machine tools, feeding conveyor belts, unloading conveyor belts and other auxiliary equipment. Different computer numerical control machine tools (Computer Number Controller, CNC) can be installed with different tools to process For different processes of materials, the RGV trolley can automatically control the moving direction and distance according to the instructions, and comes with matching tools (such as robotic arms, manipulators, etc.) to complete th...

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Problems solved by technology

[0006] 1. The advantages of the above meta-heuristic algorithm in terms of convergence speed, evolution speed, local search ability, etc. cannot be perfectly reflected in one algorithm, and further improvements to this type of algorithm are needed to better solve RGV Dynamic scheduling problem;

[0007] 2. The production and processing of the actual intelligent production system is a very complicated process, which will involve various emergencies, such as machine failures, etc. Therefore, how to apply intelligent algorithms to solve the scheduling model that is closer to the actual production is a problem currently facing;

[0008] 3. The above meta-heuristic algorithms are not universal, and specific solutions need to be designed for specific workshop scheduling problems. This is the main problem to be solved in optimizing the dynamic scheduling of RGV cars

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