CN110134092A - Method and system for dynamic dispatching of rail-type automatic guided vehicles based on harmony search - Google Patents

Abstract

The present disclosure provides a dynamic scheduling method and system for track-type automatic guided vehicles based on harmony search, which sets the initial state parameters, various processing parameters and optimization parameters of each CNC machine tool; the CNC machine tool that will provide services for the RGV trolley N times in the future The number of is encoded as a harmony vector with a length of N. According to the specified length of the harmony vector and the encoding scheme, multiple harmony vectors are constructed to form the initial harmony memory, and the fitness of each harmony vector in the harmony memory is calculated. value; within the range of variable values, randomly select a value to form a new harmony, or generate a new harmony by selecting a harmony in the HM and disturbing the fine-tuning, and calculate the fitness value of the new harmony; according to the new harmony Fitness value, update the harmony memory; judge whether the current number of iterations reaches the maximum number of iterations, if so, select a harmony with the best quality from the harmony memory for decoding, and the decoding result is the RGV car according to the sum The sequence of CNC machine tool numbers in the acoustic vector is the process of providing services for the corresponding CNC machine tools in turn, otherwise return to recompose a new harmony.

Description

Method and system for dynamic dispatching of rail-type automatic guided vehicles based on harmony search

technical field

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

The statements in this section merely provide background information related to the present disclosure and do not necessarily constitute prior art.

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 the corresponding tasks, and these operations need to consume a certain amount of time.

The dynamic scheduling of RGV trolleys is the core of planning the production process and coordinating the activities of the entire manufacturing system. It is the guarantee for fast, low-consumption, and high-quality production of customer-satisfied products. Therefore, how to dispatch RGV trolleys to maximize the production efficiency of the entire system, That is, the maximum amount of materials processed in one shift is the main purpose of the intelligent production system. In the process of studying this problem, more and more solving methods have appeared, which can be roughly divided into two types: exact algorithm and approximate algorithm: the exact algorithm is mainly based on the traditional mathematical method of operations research, and the solution accuracy obtained by it is relatively high, but The calculation is more complex and the evolution rate is relatively slow, so it is only suitable for solving dynamic scheduling problems with low complexity and small scale; approximate algorithms mainly refer to meta-heuristic algorithms, including ant colony algorithm, simulated annealing algorithm, tabu search algorithm, Genetic algorithm, etc. This type of algorithm does not need to address specific job shop scheduling problems, but takes any solution as a starting point, and obtains a high-quality solution through multiple iterations and elite retention strategies.

The existing defects in optimizing the dynamic scheduling of RGV cars are:

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;

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;

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.

Contents of the invention

In order to solve the above problems, this disclosure proposes a dynamic scheduling method and system for track-type automatic guided vehicles based on harmony search. This disclosure improves the standard harmony search algorithm, automatically optimizes the RGV scheduling scheme according to the processing system parameters, and It can adapt to CNC random faults and fault recovery, thereby improving the production and processing efficiency of the intelligent production system.

According to some embodiments, the present disclosure adopts the following technical solutions:

A method for dynamic scheduling of track-type automatic guided vehicles based on harmony search, comprising the following steps:

Set the initial state parameters, various processing parameters and optimization parameters of each CNC machine tool;

Encode the number of the CNC machine tool that the RGV car will provide services for N times in the future into a harmony vector of length N, construct multiple harmony vectors according to the specified harmony vector length and encoding scheme to form an initial harmony memory, and calculate the harmony The fitness value of each harmony vector in the memory bank;

Randomly take values within the range of variable values to form a new harmony, or generate a new harmony by selecting a harmony in the HM and disturbing the fine-tuning, and calculate the fitness value of the new harmony;

According to the fitness value of the new harmony, the harmony memory is updated;

Judging whether the current number of iterations reaches the maximum number of iterations K, if so, select a harmony with the best quality from the harmony memory for decoding, and the decoding result is that the RGV car is in sequence according to the order of the CNC machine number in the harmony vector. The CNC machine provides the service process, otherwise returns to recompose the new harmony.

As a further limitation, after a round of service, it is judged whether the current system time of the RGV car has not reached the shift time, if not, the harmony search algorithm is used for optimization, otherwise the optimization ends.

As a further limitation, if a sudden failure occurs during the operation, the RGV stops moving, and uses the current CNC machine number and the status information of each CNC machine tool as initial information to re-optimize the next N CNC machine numbers.

As a further limitation, the parameter initialization process includes: setting the time required for the RGV trolley to continuously move different units, RGV is the time required for loading and unloading of odd-numbered CNC machine tools, RGV is the time required for loading and unloading of even-numbered CNC machine tools, cleaning The time required for materials, the processing time T _Total of a shift, the number range of CNC machine tools, the size of the harmony memory in the harmony search algorithm is HMS, the probability of generating a value from the harmony memory is HMCR, and the fine-tuning probability is PAR, the perturbation step size is bw, and the maximum number of iterations is K.

As a further limitation, the specific process of encoding the harmony vector includes:

(1) The number of the CNC machine tool that the RGV trolley is currently providing service is added to the harmony code as the first number, as the first code value in the harmony code;

(2) Randomly generate an integer x representing the number of the CNC machine tool within the number range;

(3) If the harmony encoding length reaches N, the encoding ends, and a harmony is successfully generated, otherwise step (2) is continued;

(4) Repeat steps (1)-(3) to randomly construct a harmony memory until the number of harmony reaches HMS, then the initialization of the harmony memory is completed.

As a further limitation, the specific process of forming a new harmony includes: if the fitness value of the new harmony is greater than the fitness value of the worst harmony in the harmony memory, replace the harmony memory with this new harmony The worst harmony in the chord is used to update the harmony memory, otherwise it remains unchanged.

As a further limitation, the specific decoding scheme is as follows:

(a) Take the first coded number x from the harmony with the best quality. This number represents the number of the CNC machine tool. RGV moves to the CNC to serve it as needed to obtain the system time of the RGV car. If the RGV car is currently If the system time is greater than the shift time T _Total , it ends;

(b) Remove a coded number x from the harmony vector, which represents the number of the CNC machine tool. RGV moves to the CNC machine tool to serve it as needed, and obtains the system time of the RGV car. If the current RGV car If the system time is greater than the shift time, it ends;

(c) Judging whether x is the last digit of the harmony code, if it is not the last digit, then go to step (b) to continue execution, if it is the last digit of the code, then this code will be used as the next initialization of the harmony memory bank The first bit of each harmonic code is coded; otherwise decoding ends.

RGV provides services depending on the status of CNC machine tools, including:

(1) If the CNC machine tool is currently in the state of not processing any material, perform the loading operation according to the processing procedure;

(2) If the CNC machine tool is currently in the state of processing completion and the first process can be processed, the RGV performs the operation of unloading, and then performs the operation of loading new materials;

(3) If the CNC machine tool is currently in the state of finishing processing and can process the second process, the RGV needs to record the quantity of materials that have been processed so far after performing the blanking operation, so as to calculate the fitness value of the harmony vector;

(4) If the CNC machine tool is currently in the working state, the RGV needs to wait. At this time, it is necessary to compare the waiting time T _w with the time T _next that can start providing services for the next numbered CNC machine tool. If the current position is waiting If the time is relatively short, continue to wait, otherwise, move the RGV to provide services for the next numbered CNC machine tool, and make corresponding records.

A dynamic dispatching system for track-type automatic guided vehicles based on harmony search, including:

The setting module is configured to set the initial state parameters, various processing parameters and optimization parameters of each CNC machine tool;

The encoding module is configured to encode the number of the CNC machine tool that the RGV car will provide services for N times in the future into a harmony vector with a length of N, and construct multiple harmony vectors according to the specified length of the harmony vector and the encoding scheme to form the initial harmony Memory bank, calculate the fitness value of each harmony vector in the harmony memory bank;

The harmony building module is configured to randomly take values within the range of variable values to form a new harmony, or generate a new harmony by selecting a harmony in the HM and disturbing the fine-tuning, and calculate the fitness value of the new harmony ;

The update module is configured to update the harmony memory according to the fitness value of the new harmony and the fitness value of the worst harmony in the harmony memory;

The decoding module is configured to judge whether the current number of iterations reaches the maximum number of iterations K, if so, select a harmony with the best quality from the harmony memory for decoding, and the decoding result is the RGV car according to the harmony vector in the CNC machine tool The order of the numbers is the process of providing service for the CNC machine tool in turn.

A computer-readable storage medium, in which a plurality of instructions are stored, and the instructions are suitable for being loaded and executed by a processor of a terminal device to execute the method for dynamic scheduling of track-based automatic guided vehicles based on harmony search.

A terminal device, including a processor and a computer-readable storage medium, the processor is used to implement instructions; the computer-readable storage medium is used to store multiple instructions, and the instructions are suitable for being loaded by the processor and executing the described one A dynamic scheduling method for rail-mounted automatic guided vehicles based on harmony search.

Compared with the prior art, the beneficial effects of the present disclosure are:

This disclosure considers restarting the optimization process when the CNC machine tool suddenly fails or when the fault recovers, so that it can adapt to the random faults and fault recovery of the CNC machine tool, so that the optimization method is more suitable for the actual production workshop. In addition, due to the long operation time of one system, this disclosure adopts a segmented optimization strategy, and the vocoder length is N, that is, considering the efficiency of the RGV serving N CNC machine tools through different moving trajectories. Segmented optimization can simplify the complexity, reduce the optimization time, and adapt to different processing times.

Description of drawings

The accompanying drawings constituting a part of the present disclosure are used to provide a further understanding of the present disclosure, and the exemplary embodiments and descriptions of the present disclosure are used to explain the present disclosure, and do not constitute improper limitations to the present disclosure.

Figure 1 is a flowchart of the present disclosure;

Fig. 2 is a brief schematic diagram of the intelligent processing system of the present disclosure;

Detailed ways:

The present disclosure will be further described below in conjunction with the accompanying drawings and embodiments.

It should be noted that the following detailed description is exemplary and intended to provide further explanation of the present disclosure. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs.

It should be noted that the terminology used herein is only for describing specific embodiments, and is not intended to limit the exemplary embodiments according to the present disclosure. As used herein, unless the context clearly dictates otherwise, the singular is intended to include the plural, and it should also be understood that when the terms "comprising" and/or "comprising" are used in this specification, they mean There are features, steps, operations, means, components and/or combinations thereof.

As shown in Figure 1, a dynamic scheduling method for track-type automatic guided vehicles based on harmony search includes the following steps:

Step 1: Set the initial state parameters and various processing parameters of each CNC. In this embodiment, it is necessary to set the time required for the RGV trolley to continuously move 1 unit, 2 units, and 3 units as t ₁ , t ₂ , t ₃ . RGV is the time required for odd-numbered CNC loading and unloading, RGV is the time required for even-numbered CNC loading and unloading, and the time required for cleaning materials. The processing time for one shift is 8 hours; before executing the harmony search algorithm, the optimization parameters must be specified , which includes CNC numbers 1 to 8. When optimizing for the first time, set the RGV car to be located at the CNC machine tools numbered 1 and 2, and determine the status of each CNC; set the size of the harmony memory library in the harmony search algorithm to HMS , the probability of generating a value from the harmony memory is HMCR, the fine-tuning probability is PAR, the perturbation step is bw, and the maximum number of iterations is K.

The second step: encoding, generating the initial harmony memory bank, and calculating the fitness value of the harmony vector. Encode the number of the CNC machine tool that the RGV car will provide services for N times in the future into a harmony code with a length of N, and construct the HMS harmony to form the initial harmony memory. The specific coding scheme is as follows:

Step 2.1: Add the CNC number that the RGV trolley is currently serving as the first number to the harmony code as the first code value in the harmony code;

Step 2.2: Randomly generate an integer x representing the CNC number. Since the CNC number is 1 to 8, the number is any integer in [1,8], that is, but it cannot be the same as the previous number. If they are the same Then discard it, and then randomly generate an integer in [1,8] as the CNC number and add it to the harmony coding;

Step 2.3: If the harmony encoding length reaches N, the encoding ends and a harmony is successfully generated, otherwise, proceed to step 2.2;

Repeat the above steps to randomly build the harmony memory until the number of harmony reaches HMS, then the initialization of the harmony memory is completed.

Step 3: After generating the initial harmony memory, it is necessary to calculate the fitness value of each harmony vector in the HM. The specific calculation method of the fitness value is as follows:

Step 3.1: Take the first coded number in the harmony vector, which indicates the number of the CNC that the RGV will serve, and the system time when the RGV starts to execute the operation at the CNC of this number is taken as the start time, recorded as T _s , and obtain the CNC Current processing status information;

Step 3.2: RGV moves to the CNC with the number corresponding to the number to perform the corresponding operation. After the operation, update the system time of RGV. If the operation is the second process of processing materials, then after completing the blanking operation, it is necessary to record that the processing has been completed The total quantity of materials;

Step 3.3: If the CNC number executed by the RGV car is not the last digit of the harmony code, proceed to step 3.2. If the CNC number executed by the RGV is the last digit of the harmony code, obtain the system’s Time, denoted as T _c , and this number is used as the value of the first variable in the harmony vector in the next initial harmony memory;

Step 3.4: The total amount of processed materials within this processing time is recorded as num, and the fitness of harmony is calculated as: fitness=num/(T _c -T _s ).

In the above step 3.2, the specific operation performed by RGV depends on the current state of CNC:

(1) If the CNC is currently in the state of not processing any material, perform the loading operation according to the process it can process;

(2) If the CNC is currently in the state of finishing processing and can process the first process, the RGV performs the operation of unloading, and then performs the operation of loading new materials;

(3) If the CNC is currently in the state of processing and can process the second process, the RGV performs the blanking operation and completes the cleaning work, and records the number of materials that have been processed so far in order to calculate the fitness of the harmony vector value;

(4) If the CNC is currently working, the RGV needs to wait. At this time, it is necessary to compare the waiting time T _w with the time T _next that can start providing services for the next numbered CNC. If the waiting time of the current position is compared with If it is short, continue to wait, otherwise, the mobile RGV will provide services for the next numbered CNC, and make corresponding records.

When the CNC is in the above (4) state and compares the waiting time T _w with the time T _next to start providing services for the next numbered CNC, T _{next needs to be calculated, and T next depends} on the RGV moving from the current CNC to the next CNC. The required time t _m and the waiting time _{t w} at the next CNC can be calculated according to the position state function defined below:

In the above formula, k, j∈[1,8], k represents the number of the CNC currently served by the RGV, j represents the number of the next CNC that the RGV is expected to serve, t ₁ , t ₂ , and t ₃ represent the RGV moving one, The time required for 2 and 3 positions.

Step 4: Create a new harmony vector. A new harmony vector is generated by selecting the harmony in the harmony library, and then fine-tuning the disturbance. Or directly generate a new harmony vector according to the harmony coding scheme. The specific operation steps are as follows:

Step 4.1: The generation process of the new harmony X ^new . Generate a random number rand within [0,1]. If rand<HMCR, randomly select a harmony X from the harmony memory as the newly generated harmony; if rand≥HMCR, generate a new one according to the encoding scheme Harmony X', namely:

Step 4.2: If the new harmony X ^new comes from the harmony memory, it is necessary to selectively fine-tune the harmony encoding according to the fine-tuning probability PAR. Compare the harmony coded value j with its adjacent previous coded value i one by one, if Then fine-tune the following coded values according to the fine-tuning step size bw=3. When the number of fine-tuning variables reaches PAR*N, the fine-tuning operation ends and goes to step 4.4; if the number of fine-tuning variables does not reach PAR*N after this round ends PAR*N, then go to step 4.3 for the second round of comparison and fine-tuning.

Step 4.3: Compare the harmony coded value j with its adjacent previous coded value i one by one, if Then fine-tune the latter variable value according to the fine-tuning step size bw=2 (the variables that have been fine-tuned in the first round are skipped), stop when the number of fine-tuned variables reaches PAR*N, and go to step 4.4 to continue execution.

Step 4.4: Follow the method in Step 3 to calculate the fitness value of the newly created harmony.

In the above step 4.1, the HMCR is set to gradually decrease with the increase of the number of iterations k. A larger HMCR at the beginning of the iteration helps to achieve a local optimum, and a smaller value of the HMCR in the later iteration can make the population more diverse. Thus jumping out of the local optimum:

In the above step 4.2 and step 4.3, the PAR is set to gradually increase with the increase of the number of iterations k, so that the PAR value is small at the initial stage of the iteration, and the local area is fully searched to mine local information, and the PAR increases in the later stage It can speed up the search speed, expand the search range for global search, and help jump out of local optimum:

The specific operation of the fine-tuning is as follows: Assume that the former of two adjacent coded values is i and the latter is j, fine-tune the latter bit according to the following formula, and the new value of the latter coded value is

Step 5: After generating the new harmony variable, update the harmony memory according to the fitness value of the new harmony vector and the fitness value of the worst harmony in the harmony memory. The specific steps for updating are as follows:

Step 5.1: Compare the fitness value of the new harmony vector with the fitness value of the worst harmony in the harmony memory, if the fitness value of the new harmony vector is greater than the fitness value of the worst harmony in the harmony memory , then use this new harmony vector to replace the worst harmony in the harmony memory to update the harmony memory, otherwise it remains unchanged;

Step 5.2: Determine whether the current number of iterations reaches the maximum number of iterations K, and if so, select a harmony vector with the best quality from the HM for decoding; otherwise, go to step 4 and continue.

Step 6: When the number of iterations reaches the maximum number of iterations, select the harmony vector with the largest fitness value in the harmony memory for decoding, and the decoding means that the RGV car provides services for the CNC in sequence according to the order of the CNC numbers in the harmony vector The specific decoding scheme is as follows:

Step 6.1: Take the first coded number x from the harmony with the best quality. This number represents the CNC number. The RGV moves to the CNC to serve it as needed, and then obtains the system time of the RGV car. If the current RGV car When the system time is greater than the shift time T _Total , it ends;

Step 6.2: Remove a coded number x from the harmony vector, this number represents the CNC number, the RGV moves to the CNC to serve it as needed, and then obtains the system time of the RGV car, if the current system time of the RGV car If it is greater than the shift time T _Total , it ends;

Step 6.3: Judging whether x is the last digit of the harmony code, if it is not the last digit, go to step 6.2 and continue to execute, if it is the last digit of the code, then this code will be used as the sum when the harmony memory bank is initialized next time First bit encoding in vocoding; go to step 6.4;

Step 6.4: Decoding ends.

Step 7: Use the Harmony Search Algorithm in a loop to optimize segment by segment. After decoding, if the current system time of the RGV car does not reach the shift time T _Total , the last CNC number of the previous round of optimization will be used as the first number in the harmony coding of the next round of optimization, and go to the second step to continue implement.

If the RGV trolley has a sudden failure during the operation of the CNC number sequence in the harmony vector, the RGV stops moving, and uses the current CNC number and the status information of each CNC as the initial information to re-execute the next N CNC numbers. optimization.

After a shift time is over, the dynamic scheduling strategy of RGV within T _Total time is sequentially output according to the results of subsection optimization. According to this scheme, dispatching RGV cars to provide services for corresponding CNC can maximize the production efficiency of the workshop.

In order to verify the effectiveness of the technical solution of this application, the following is optimized in combination with the schematic diagram and data of the intelligent production system:

Figure 2 is a schematic diagram of an intelligent processing system, which consists of 8 computer numerical control machine tools (ComputerNumberController, CNC), 1 track-type automatic guided vehicle (RailGuideVehicle, RGV), 1 RGV linear track, 1 feeding conveyor belt, and 1 lower conveyor belt. Conveyor belt and other auxiliary equipment. RGV is an unmanned intelligent vehicle that can run freely on a fixed track. It can automatically control the moving direction and distance according to the instructions, and it comes with a robotic arm, two robotic claws and a material cleaning tank, which can complete tasks such as loading and unloading and cleaning materials.

Since the structure of the track-type automatic guided vehicle and the computer numerical control machine tool are all prior art, no more introductions will be made here.

RGV has an intelligent control function. It moves and stops on a linear track according to receiving or sending command signals. It can continuously move 1 unit (the distance between two adjacent CNCs), 2 units (the distance between three adjacent CNCs) distance) and 3 units (the distance between four adjacent CNCs). RGV can only perform one of the operations of moving, stopping and waiting, loading and unloading and cleaning at the same time. The loading and unloading conveying belt is composed of 4 sections, each of which has 1 section in front of each CNC, which is controlled by the system sensor and can only be driven in one direction, which can be linked or independent.

Assuming that the material processed in the intelligent processing system has two processes, the first and second processes are respectively processed by two CNCs equipped with different tools, and the tools cannot be replaced during the process; the CNC has 1 process during the process. Faults may occur with a 100% probability, and the time for each troubleshooting (manual processing, scrapping of unfinished materials) is between 10 and 20 minutes, and the job sequence will be added immediately after the troubleshooting.

Combined with the production background of the above intelligent processing system and the following system parameters, the optimized RGV trolley dynamic scheduling method proposed in this implementation plan is verified:

After optimizing the dynamic scheduling of RGV cars based on the harmony search algorithm, the specific scheduling process and fault information of RGV cars within a shift time are as follows:

The first group of data corresponds to the specific information in the scheduling process:

The first set of data corresponds to the fault information during the RGV scheduling process:

The second group of data corresponds to the specific information in the scheduling process:

The second set of data corresponds to the fault information during the RGV scheduling process:

Through the analysis of the above experimental data and results, it can be seen that when the system parameters are the first set of data, 223 pieces of materials are processed in one shift, and the first process of CNC processing materials numbered 1, 3, 5, number The second process of CNC processing materials for 2, 4, 6; when the system parameter is the second set of data, 208 materials are processed, and the first process of CNC processing materials with numbers 1, 2, 4, 5, 7, 8 The first process, the second process of CNC processing materials numbered 3 and 6. The processing time of the two processes in the first group of system parameters is similar, and the number of CNCs allocated is the same; in the second group of system parameters, because the second processing process takes less time than the first processing process, the first processing process is allocated The number of CNCs in the process is small, and the number of CNCs allocated is almost proportional to the time spent in the two processing processes, which is in line with the actual situation. Two sets of different system parameters and experimental data show that the algorithm can adapt to CNC random faults and fault recovery, and can automatically adjust the RGV dynamic scheduling scheme according to the system parameters, which verifies the optimization of the RGV car dynamic scheduling method based on the harmony search algorithm. effectiveness.

Those skilled in the art should understand that the embodiments of the present disclosure may be provided as methods, systems, or computer program products. Accordingly, the present disclosure can take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present disclosure may take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.

The present disclosure is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the present disclosure. It should be understood that each procedure and/or block in the flowchart and/or block diagram, and a combination of procedures and/or blocks in the flowchart and/or block diagram can be realized by computer program instructions. These computer program instructions may be provided to a general purpose computer, special purpose computer, embedded processor, or processor of other programmable data processing equipment to produce a machine such that the instructions executed by the processor of the computer or other programmable data processing equipment produce a An apparatus for realizing the functions specified in one or more procedures of the flowchart and/or one or more blocks of the block diagram.

These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing apparatus to operate in a specific manner, such that the instructions stored in the computer-readable memory produce an article of manufacture comprising instruction means, the instructions The device realizes the function specified in one or more procedures of the flowchart and/or one or more blocks of the block diagram.

These computer program instructions can also be loaded onto a computer or other programmable data processing device, causing a series of operational steps to be performed on the computer or other programmable device to produce a computer-implemented process, thereby The instructions provide steps for implementing the functions specified in the flow chart or blocks of the flowchart and/or the block or blocks of the block diagrams.

The above descriptions are only preferred embodiments of the present disclosure, and are not intended to limit the present disclosure. For those skilled in the art, the present disclosure may have various modifications and changes. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present disclosure shall be included within the protection scope of the present disclosure.

Although the specific implementation of the present disclosure has been described above in conjunction with the accompanying drawings, it does not limit the protection scope of the present disclosure. Those skilled in the art should understand that on the basis of the technical solutions of the present disclosure, those skilled in the art do not need to pay creative work Various modifications or variations that can be made are still within the protection scope of the present disclosure.

Claims (10)

1. a kind of rail mounted automatic guide vehicle dynamic dispatching method based on harmony search, it is characterized in that: the following steps are included:

Original state parameter, various machined parameters and the Optimal Parameters of each numerically-controlled machine tool are set；

There is provided RGV trolley future n times to the harmony vector for being encoded to a length as N of the numerically-controlled machine tool of service, according to Specified harmony vector length and encoding scheme construct multiple harmony vectors and constitute initial harmony data base, calculate harmony data base In each harmony vector fitness value；

Randomly value forms a new harmony within the scope of variable-value, or is produced by selecting harmony in HM and disturbing fine tuning A raw new harmony, calculates the fitness value of new harmony；

According to the fitness value of new harmony, harmony data base is updated；

Judge whether current iteration number reaches maximum number of iterations, if it is selects a quality most from harmony data base Good harmony is decoded, and decoding result is that RGV trolley according to the sequence that numerically-controlled machine tool in harmony vector is numbered is followed successively by phase The numerically-controlled machine tool answered provides the process of service, otherwise returns and reformulates new harmony.

2. a kind of rail mounted automatic guide vehicle dynamic dispatching method based on harmony search as described in claim 1, feature It is: after a wheel service, judges whether the current system time of RGV trolley is not up to length of shift, recycling if not up to makes It is optimized with harmonic search algorithm, otherwise optimization terminates；

Or, RGV stops movement, and if occurring catastrophic failure in operation with today's numerical control lathe numbering and each number of units The status information for controlling lathe again optimizes next N number of numerically-controlled machine tool number as initial information.

3. a kind of rail mounted automatic guide vehicle dynamic dispatching method based on harmony search as described in claim 1, feature Be: the process of parameter initialization includes: setting RGV trolley continuous moving not time required for commensurate, and RGV is odd-numbered Numerically-controlled machine tool loading and unloading need time, RGV be even-numbered numerically-controlled machine tool loading and unloading need time, clean material institute The time needed, a shift process time T_Total, the Serial Number Range of numerically-controlled machine tool, the harmony data base in harmonic search algorithm Size is HMS, and the probability that a value is generated from harmony data base is HMCR, and fine tuning probability is PAR, and disturbance step-length is bw, most Big the number of iterations is K.

4. a kind of rail mounted automatic guide vehicle dynamic dispatching method based on harmony search as described in claim 1, feature Be: the detailed process for carrying out the coding of harmony vector includes:

(1) by RGV trolley currently providing service numerically-controlled machine tool number as first digit be added to in sound encoder, As with first encoded radio in sound encoder；

(2) the integer x for indicating numerically-controlled machine tool number is randomly generated in Serial Number Range；

(3) if harmony code length reaches N, end-of-encode is successfully generated a harmony, otherwise continues to execute step (2)；

(4) step (1)-(3) building harmony data base at random is repeated, until the number of harmony reaches HMS, then harmony data base Initialization finishes.

5. a kind of rail mounted automatic guide vehicle dynamic dispatching method based on harmony search as described in claim 1, feature It is: if the fitness value that the detailed process of one new harmony of composition includes: new harmony is greater than worst harmony in harmony data base Fitness value, then replace harmony worst in harmony data base to realize harmony data base more with this new harmony Newly, it otherwise remains unchanged.

6. a kind of rail mounted automatic guide vehicle dynamic dispatching method based on harmony search as described in claim 1, feature Be: specific decoding scheme is as follows:

(a) first coding number x, the number of the digital representation numerically-controlled machine tool are taken from top-quality harmony, RGV is moved to As needed for its service at the CNC, the system time of RGV trolley is obtained, if the current system time of RGV trolley is greater than class Secondary time T_Total, then terminate；

(b) next bit is taken to encode number x, the number of the digital representation numerically-controlled machine tool from the harmony vector, RGV is moved to the number It controls at lathe as needed for its service, obtains the system time of RGV trolley, if the current system time of RGV trolley is greater than Length of shift then terminates；

(c) judge that x is and last position of sound encoder then goes to step (b) and continue to execute if not last position, It is encoded if it is last position, then the coding is as first volume when initializing harmony data base next time in each and sound encoder Code；Otherwise decoding terminates.

7. a kind of rail mounted automatic guide vehicle dynamic dispatching method based on harmony search as described in claim 1, feature Be: RGV provides service dependent on the state of numerically-controlled machine tool, specifically includes:

(1) it if the numerically-controlled machine tool is currently in the state for not processing any material, is executed according to the process of its processing Material operation；

(2) if the numerically-controlled machine tool is currently in the state of process finishing and can process the first procedure, RGV is held Then the operation of row blanking executes the operation of new material again；

(3) if the numerically-controlled machine tool is currently in the state of process finishing and can process second operation work, RGV is held Need to record the quantity of the material completed the process at present after row blanking operation, to calculate the fitness of harmony vector Value；

(4) if the numerically-controlled machine tool is currently in the state to work, RGV needs to wait, and at this moment needs to compare waiting Time T_wStart to provide the time T of service with the numerically-controlled machine tool that can be next number_nextIf the time that current location waits It is shorter, it continues waiting for, moves RGV otherwise as the numerically-controlled machine tool of next number and service is provided, and carry out respective record.

8. a kind of rail mounted automatic guide vehicle dynamic scheduling system based on harmony search, it is characterized in that: including:

Setup module is configured as that the original state parameter of each numerically-controlled machine tool, various machined parameters and Optimal Parameters are arranged；

Coding module, be configured as the number for the numerically-controlled machine tool that RGV trolley future n times provide service being encoded to a length be The harmony vector of N constructs multiple harmony vectors according to specified harmony vector length and encoding scheme and constitutes initial and sound memory Library calculates the fitness value of each harmony vector in harmony data base；

Harmony constructs module, is configured as within the scope of variable-value randomly value and forms a new harmony, or by HM Middle selection harmony simultaneously disturbs fine tuning one new harmony of generation, calculates the fitness value of new harmony；

Update module is configured as the fitness value pair of worst harmony in fitness value and harmony data base according to new harmony Than being updated to harmony data base；

Decoder module is configured as judging whether current iteration number reaches maximum number of iterations, if it is from and sound memory A top-quality harmony is selected to be decoded in library, decoding result is RGV trolley according to numerically-controlled machine tool in harmony vector Number sequence be followed successively by numerically-controlled machine tool provide service process.

9. a kind of computer readable storage medium, it is characterized in that: being wherein stored with a plurality of instruction, described instruction is suitable for being set by terminal Standby processor load and perform claim require a kind of rail mounted based on harmony search described in any one of 1-7 to guide automatically Vehicle dynamic dispatching method.

10. a kind of terminal device, it is characterized in that: including processor and computer readable storage medium, processor is for realizing each Instruction；Computer readable storage medium is for storing a plurality of instruction, and described instruction is suitable for by processor load and perform claim is wanted Seek a kind of rail mounted automatic guide vehicle dynamic dispatching method based on harmony search described in any one of 1-7.