A dual command retrieval sequencing method for an automated dispensing system

Abstract

The present application relates to a double command retrieval sequencing method suitable for an automatic dispensing system, belonging to the technical field of intelligent warehousing. The present application first constructs an automatic dispensing system under two inbound / outbound configurations; then, based on the retrieval mode of double command cycles, the travel time of the machine arm accessing the medicine box is depicted; finally, aiming at the randomness of the pharmacist service time, a double command retrieval sequencing model under the human-machine cooperation environment is constructed to optimize the retrieval order of the medicines in adjacent prescription orders. In this model, the prescription orders arrive continuously and are processed according to the first-come-first-served rule. The present application can be widely applied to medical institutions such as pharmacies to improve the performance of the automatic dispensing system and the efficiency of medicine dispensing. By optimizing the retrieval sequencing, this method can reduce the travel time of the machine arm and improve the efficiency of medicine picking, thereby shortening the waiting time of patients and improving the operation efficiency of the entire automatic dispensing system.

Description

Technical Field

[0001] This invention relates to a dual-command retrieval and sorting method suitable for automated dispensing systems, belonging to the field of intelligent warehousing technology. Background Technology

[0002] In the field of smart warehousing, particularly smart pharmacies, the demand for automated dispensing systems is increasing. Compared to traditional pharmacies, these systems can automate various tasks such as drug storage, retrieval, and distribution, thereby improving the efficiency of prescription order processing. However, these systems still face challenges in handling dual-command retrieval and sorting problems, resulting in longer waiting times for patients to pick up their medications. Therefore, new optimization solutions are urgently needed to improve the current state of smart pharmacies.

[0003] Performance optimization of automated dispensing systems largely relies on the order picking problem, which plays a crucial role in improving system throughput. The automated dispensing system involved in this invention is structurally and functionally similar to a small-scale automated storage and retrieval system. Previous studies on the order picking problem in automated storage and retrieval systems have been based on the assumption of a single inlet / outlet station. However, in practical applications, many automated picking systems are configured with multiple inlet / outlet stations. Therefore, this invention focuses on automated dispensing systems with a two-inlet / outlet station configuration.

[0004] The order picking problem in automated dispensing systems mainly refers to the sorting of retrieved medications by the robotic arm. Specifically, since the automated dispensing system involved in this invention is not yet fully automated, pharmacists are still required to assist in picking prescription orders, thus the random sorting time of pharmacists needs to be considered. Based on this, this invention explores the dual-command retrieval and sorting problem in an automated dispensing system with two inbound / outbound stations in a human-machine collaborative environment. However, the order picking problem in current automated dispensing systems does not fully consider the influence of human factors. Summary of the Invention

[0005] The technical problem to be solved by this invention is for an automated dispensing system in a human-machine collaborative environment. By establishing a dual-command retrieval and sorting model, the average picking time of prescription orders is minimized, thereby solving the above-mentioned problem.

[0006] The technical solution of this invention is: to address the randomness of pharmacist service time and minimize the average picking time of prescription orders, a drug sorting model based on a dual-command cycle retrieval mode is established to optimize the retrieval path of drugs in adjacent prescription orders, thereby improving the picking efficiency of prescription orders.

[0007] A dual-command retrieval and sorting method suitable for automated dispensing systems includes:

[0008] An automated dispensing system with two entry / exit configurations is constructed, the automated dispensing system including a robotic arm for storing and retrieving medicine boxes.

[0009] Based on a dual-command cycle retrieval mode, the travel time of mechanically retrieving medicine boxes is characterized.

[0010] To address the randomness of pharmacist service hours, a dual-command retrieval and sorting model in a human-machine collaborative environment is constructed to optimize the retrieval order of drugs in adjacent prescription orders. In this model, prescription orders arrive consecutively and are processed according to a first-come, first-served rule.

[0011] The construction of the automated dispensing system under two entry / exit station configurations includes:

[0012] The automated dispensing system consists of double-sided medicine racks with |L| positions. Each position holds a medicine box of equal volume, and each medicine box contains only one type of medicine.

[0013] The automated dispensing system also includes a crane. A track runs through the middle of the double-sided medicine rack, allowing the crane to move parallel to the ground at a speed v. A robotic arm is mounted on the crane and moves vertically along it at a speed v. Two inlet / outlet stations are located slightly below the center of the first (front) side of the medicine rack (their height from the ground is ergonomically designed).

[0014] The robotic arm operates at time t i,j The medicine box is conveyed to one inlet / outlet station. Simultaneously, a pharmacist sorts medicines from another medicine box at a random sorting time X. The robotic arm and the pharmacist process medicines simultaneously, working together for a time max(X,t). i,j ).

[0015] The dual-command cycle-based retrieval mode characterizes the travel time of the mechanical medicine box, including:

[0016] The dual-command cycle retrieval mode refers to the system simultaneously executing storage and retrieval requests within a single cycle.

[0017] Cycle time is defined as the sum of the time to retrieve the medicine box, the time to travel to the storage location and store the medicine box, the travel time from the storage location to the retrieval location, and the time to retrieve the medicine box and transport it to the inbound / outbound station.

[0018] Clearly, by employing a two-command operation, the total time for the system to execute all storage and retrieval requests will be reduced. The distance the robotic arm travels between any two positions can be measured by the Chebyshev distance. Therefore, in the two-command retrieval mode, the travel time t for the robotic arm to return the medicine box to storage position i and retrieve the medicine box at position j is [not specified]. i,j The calculation is shown in equation (1):

[0019]

[0020] In the formula, x i (x j ), y i (y j Let d be the x and y coordinates of position i(j) in the medicine shelf, and x0 and y0 be the x and y coordinates of the entry / exit station, respectively. The two entry / exit stations are adjacent, and the movement distance of the robotic arm between the two entry / exit stations is negligible. m d n Let v be the length and height of a medicine box, respectively, and v be the speed at which the robotic arm moves in the horizontal and vertical directions.

[0021] To address the randomness of pharmacist service times, a dual-command retrieval and sorting model is constructed in a human-machine collaborative environment to optimize the retrieval order of medications in adjacent prescription orders. In this model, prescription orders arrive consecutively and are processed according to a first-come, first-served rule, including:

[0022] The dual-command retrieval and ranking model is as follows:

[0023] Objective function:

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[0025] Constraints:

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[0039] In the formula, k represents the drug number index, K is the total number of drugs in each prescription order, k∈{1,2,K,K}, p represents the inbound / outbound index, p∈{1,2}, l p The number index representing the entry / exit station location, M k Let Φ represent the set of medicine box locations containing medicine k on the medicine shelf, and let Φ represent the set of all medicine box locations for all medicines in each prescription order, i.e., Φ = M1UM2ULUM. K Let L represent the set of all positions on the medicine shelf, i.e., L = ΦU{l p}, |L| represents the total number of positions, u i u j Then it represents any real number.

[0040] The objective function (2) represents minimizing the average picking time of prescription orders in a human-machine collaborative environment. It is assumed that the pharmacist's random picking time X follows a normal distribution, i.e., X:N(μ,σ). 2 ), where μ is the mean and σ is the standard deviation, then

[0041]

[0042] Constraint (3) ensures that the remaining inventory at position j meets the dosage required by the prescription order for the medicine.

[0043] Constraint (4) is the start of the retrieval sequence, indicating that the robotic arm needs to first send the medicine box back from the in / out station to the storage location before retrieving the medicine box location j of the new medicine.

[0044] Constraints (5) and (6) restrict each order and each drug location to be retrieved at most once.

[0045] Constraint (7) restricts the number of input arcs at each point to be equal to the number of output arcs.

[0046] Constraint (8) Avoid duplicate searches for drugs.

[0047] Constraint (9) ensures that the robotic arm retrieves one drug location and then retrieves another drug.

[0048] Constraint (10) ensures that the difference in the number of double command cycle operations executed by the robot arm starting from the two entry / exit stations does not exceed 1, because the robot arm operates alternately from the two entry / exit stations.

[0049] Constraint (11) states that a new prescription order may have at most two types of medications that are the same as those in the previous prescription order (affected by the number of inbound / outbound items). If the new prescription order includes the last two medication requests in the previous prescription order, the pharmacist will sort them directly at the inbound / outbound item.

[0050] Constraint (12) ensures that Two-command cycle operation.

[0051] Constraint (13) is to eliminate constraints on the sub-loop.

[0052] In constraint (14) For 0-1 variables, This indicates that the robotic arm will access position j immediately after accessing position i, otherwise...

[0053] In constraint (15) For 0-1 variables, This indicates two medicine boxes containing medications from newly arrived prescription orders, which pharmacists can directly sort without requiring a robotic arm to retrieve them again; otherwise...

[0054] The dual-command retrieval and sorting model can be solved by calling the CPLEX optimization solver in the MATLAB software programming environment.

[0055] The beneficial effects of this invention are: it can be widely applied in medical institutions such as pharmacies to improve the performance of automated dispensing systems and the efficiency of drug dispensing. By optimizing the retrieval and sorting process, this method can reduce the travel time of the robotic arm and improve the efficiency of drug picking, thereby shortening patient waiting time and improving the overall operational efficiency of the automated dispensing system. Attached Figure Description

[0056] Figure 1 This is a flowchart of the present invention;

[0057] Figure 2 This is a simplified diagram of the automatic dispensing system under two entry / exit station configurations in an embodiment of the present invention;

[0058] Figure 3 This is a simplified diagram of an automated dispensing system under an inbound / outbound configuration in an embodiment of the present invention;

[0059] Figure 4 This is a schematic diagram of the robotic arm retrieving the sequence of the drug in the method of the present invention;

[0060] Figure 5 This is a schematic diagram of how a robotic arm retrieves the sequence of a drug using traditional methods. Detailed Implementation

[0061] The present invention will be further described below with reference to the accompanying drawings and specific embodiments.

[0062] Example 1: As Figure 1 As shown, a dual-command retrieval and sorting method suitable for automated dispensing systems includes:

[0063] An automated dispensing system with two entry / exit configurations is constructed, the automated dispensing system including a robotic arm for storing and retrieving medicine boxes.

[0064] Based on a dual-command cycle retrieval mode, the travel time of mechanically retrieving medicine boxes is characterized.

[0065] To address the randomness of pharmacist service hours, a dual-command retrieval and sorting model in a human-machine collaborative environment is constructed to optimize the retrieval order of drugs in adjacent prescription orders. In this model, prescription orders arrive consecutively and are processed according to a first-come, first-served rule.

[0066] The construction of the automated dispensing system under two entry / exit station configurations includes:

[0067] The automated dispensing system consists of double-sided medicine racks with |L| positions. Each position holds a medicine box of equal volume, and each medicine box contains only one type of medicine.

[0068] The automated dispensing system also includes a crane. A track runs through the middle of the double-sided medicine rack, allowing the crane to move parallel to the ground at a speed v. A robotic arm is mounted on the crane and moves vertically along it at a speed v. Two inlet / outlet stations are located slightly below the center of the first (front) side of the medicine rack.

[0069] The robotic arm operates at time t i,j The medicine box is conveyed to one inlet / outlet station. Simultaneously, a pharmacist sorts medicines from another medicine box at a random sorting time X. The robotic arm and the pharmacist process medicines simultaneously, working together for a time max(X,t). i,j ).

[0070] The dual-command cycle-based retrieval mode characterizes the travel time of the mechanical medicine box, including:

[0071] The dual-command cycle retrieval mode refers to the system simultaneously executing storage and retrieval requests within a single cycle.

[0072] Cycle time is defined as the sum of the time to retrieve the medicine box, the time to travel to the storage location and store the medicine box, the travel time from the storage location to the retrieval location, and the time to retrieve the medicine box and transport it to the inbound / outbound station.

[0073] Clearly, by employing a two-command operation, the total time for the system to execute all storage and retrieval requests will be reduced. The distance the robotic arm travels between any two positions can be measured by the Chebyshev distance. Therefore, in the two-command retrieval mode, the travel time t for the robotic arm to return the medicine box to storage position i and retrieve the medicine box at position j is [not specified]. i,j The calculation is shown in equation (1):

[0074]

[0075] In the formula, x i (x j ), y i (y j Let d be the x and y coordinates of position i(j) in the medicine shelf, and x0 and y0 be the x and y coordinates of the entry / exit station, respectively. The two entry / exit stations are adjacent, and the movement distance of the robotic arm between the two entry / exit stations is negligible. m d n Let v be the length and height of a medicine box, respectively, and v be the speed at which the robotic arm moves in the horizontal and vertical directions.

[0076] To address the randomness of pharmacist service times, a dual-command retrieval and sorting model is constructed in a human-machine collaborative environment to optimize the retrieval order of medications in adjacent prescription orders. In this model, prescription orders arrive consecutively and are processed according to a first-come, first-served rule, including:

[0077] The dual-command retrieval and ranking model is as follows:

[0078] Objective function:

[0079]

[0080] Constraints:

[0081]

[0082]

[0083]

[0084]

[0085]

[0086]

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[0094] In the formula, k represents the drug number index, K is the total number of drugs in each prescription order, k∈{1,2,K,K}, p represents the inbound / outbound index, p∈{1,2}, l p The number index representing the entry / exit station location, M k Let Φ represent the set of medicine box locations containing medicine k on the medicine shelf, and let Φ represent the set of all medicine box locations for all medicines in each prescription order, i.e., Φ = M1UM2UL…UM K Let L represent the set of all positions on the medicine shelf, i.e., L = ΦU{l p}, |L| represents the total number of positions, u i u j Then it represents any real number.

[0095] The objective function (2) represents minimizing the average picking time of prescription orders in a human-machine collaborative environment. It is assumed that the pharmacist's random picking time X follows a normal distribution, i.e., X:N(μ,σ). 2 ), where μ is the mean and σ is the standard deviation, then

[0096]

[0097] Constraint (3) ensures that the remaining inventory at position j meets the dosage required by the prescription order for the medicine.

[0098] Constraint (4) is the start of the retrieval sequence, indicating that the robotic arm needs to first send the medicine box back from the in / out station to the storage location before retrieving the medicine box location j of the new medicine.

[0099] Constraints (5) and (6) restrict each order and each drug location to be retrieved at most once.

[0100] Constraint (7) restricts the number of input arcs at each point to be equal to the number of output arcs.

[0101] Constraint (8) Avoid duplicate searches for drugs.

[0102] Constraint (9) ensures that the robotic arm retrieves one drug location and then retrieves another drug.

[0103] Constraint (10) ensures that the difference in the number of double command cycle operations executed by the robot arm starting from the two entry / exit stations does not exceed 1, because the robot arm operates alternately from the two entry / exit stations.

[0104] Constraint (11) states that a new prescription order may have at most two types of medications that are the same as those in the previous prescription order (affected by the number of inbound / outbound items). If the new prescription order includes the last two medication requests in the previous prescription order, the pharmacist will sort them directly at the inbound / outbound item.

[0105] Constraint (12) ensures that Two-command cycle operation.

[0106] Constraint (13) is to eliminate constraints on the sub-loop.

[0107] In constraint (14) For 0-1 variables, This indicates that the robotic arm will access position j immediately after accessing position i, otherwise...

[0108] In constraint (15) For 0-1 variables, This indicates two medicine boxes containing medications from newly arrived prescription orders, which pharmacists can directly sort without requiring a robotic arm to retrieve them again; otherwise...

[0109] The dual-command retrieval and sorting model can be solved by calling the CPLEX optimization solver in the MATLAB software programming environment.

[0110] According to the technical solution proposed by the present invention, the average picking time for prescription orders can be reduced, and pharmacy operational efficiency can be improved. Assuming the basic structure of the automated dispensing system is as follows... Figure 2 As shown, the system's relevant parameters are set as follows: double-sided medicine rack, with each side having a 17×17 layout, i.e., |L| = 17×17×2. The height of each medicine box is d. n =0.168m, length d m =0.275m. The robotic arm moves at a speed of v = 0.1486m / s in both the horizontal and vertical directions. The two entry / exit stations are located at (9,10) and (10,10) on the first side of the medicine shelf, respectively. Based on the actual application time for pharmacists to sort medicines, the mean μ is set to be 5, 10, 15, 20 and 25, and the standard deviation σ is set to be 0, 5, 10 and 15, respectively.

[0111] To verify the effectiveness of the dual-command retrieval and sorting method for an automated dispensing system with two in / out configurations proposed in this invention, it is compared with a dual-command retrieval and sorting method for an automated dispensing system with a traditional in / out configuration. In the traditional method, the automated dispensing system has only one in / out station on the shelf, such as... Figure 3 As shown. The collaboration between the pharmacist and the system is a sequential operation; that is, after the system receives a prescription order request, the robotic arm transports the incoming / outgoing medicine box to its storage location in a dual-command cycle operation mode, and then retrieves a new medicine box and delivers it to the incoming / outgoing station (time: t). i,j In this process, the pharmacist sorts medications from the medication bins at the inlet / outlet (time: X). After sorting, the robotic arm delivers the medication bins to their storage location and then retrieves the next medication request. This process is repeated until all medications in the prescription have been retrieved. Therefore, under this method, the time for human-machine collaborative picking of a certain medication is X+t. i,j .

[0112] One hundred prescription orders were randomly selected from pharmacies, and the average picking time of each order was used as the metric. Prescription orders arrived consecutively, and the order in which medications were retrieved from two adjacent orders was as follows: The drug retrieval sequence for order 1 is assumed to be: The drug search sequence for order 2 is drug and The fact that the last two medications in prescription order 1 might affect the retrieval sequence of prescription order 2, as traditional methods only consider the last medication. This will affect the retrieval sequence of order 2. Based on this, the present invention establishes a dual-command retrieval and sorting model for adjacent prescription orders. The robotic arm adopts a dual-command cycle retrieval mode for prescription orders i1, i2, L, i K-1 i K (Invention method: assuming the last two medications l1 and l2 in the previous prescription order are stored at two different inbound / outbound stations; conventional method: assuming the last medication l1 in the previous prescription order is stored at the inbound / outbound station) Figure 4 and Figure 5 The present invention method and the conventional method are illustrated respectively, and the schematic diagrams of the robotic arm retrieving the drug sequence in the two methods are shown (assuming the retrieval order is i1→i2→L→i). K-1 →i K ).

[0113] Table 1 compares the average order picking time of the two methods based on different pharmacist sorting time parameters. The formula for calculating the efficiency improvement is as follows:

[0114]

[0115]

[0116] Table 1: Comparison of average order picking time between the two methods

[0117] As shown in Table 1, the results of the method of this invention are significantly better than those of the traditional method, with an efficiency improvement ranging from 10.43% to 71.10%. Specifically, the improvement in order picking time is related to the changes in the parameters μ and σ related to the pharmacist's sorting time. In this method, the cooperation between the pharmacist and the machine is a parallel operation; that is, the robotic arm retrieves the medicine box while the pharmacist sorts simultaneously. Therefore, the average order picking time is affected by both parameters μ and σ. As μ or σ increases, efficiency decreases, mainly because the pharmacist gradually becomes the bottleneck in the human-machine collaborative picking process. In contrast, in the traditional method, the cooperation between the pharmacist and the machine is a sequential operation; that is, the pharmacist can only sort after the robotic arm has finished retrieving the medicine box. Therefore, the average order picking time is only affected by the average pharmacist service time μ, and not by σ. As μ increases, efficiency decreases.

[0118] To verify the effectiveness of the proposed dual-command retrieval and sorting method, it is compared with three common sorting methods used in pharmacies, including dynamic programming, greedy algorithms, and random algorithms. The specific descriptions of the four methods are as follows:

[0119] Dynamic Programming: The drug retrieval order is the original list of drugs in the prescription order, and the location of all medicine boxes for each drug is considered a stage. In each stage, the storage location of all medicine boxes for a drug is considered a state. The decision task in each stage includes selecting the medicine box location to retrieve the drug (each drug has more than one medicine box location). The dynamic programming method aims to determine an optimal strategy based on the stage (i.e., the order of drugs) to reduce the retrieval time of the robotic arm for the prescription order.

[0120] Greedy method: The drug retrieval order is the original list of drugs in the prescription order. At each stage, the position of the medicine box closest to the current state in the next stage is determined. However, the greedy method only focuses on optimizing the shortest picking time within each stage, without considering the optimal picking time for all drugs in the prescription order.

[0121] Randomization Method: The drug retrieval order is the original order list of drugs in the prescription order. After determining the drug position in the current stage, the position of the medicine box in the next stage is randomly selected. The randomization method randomly selects the medicine box position without considering any specific criteria or optimization objectives.

[0122] The method proposed in this invention not only optimizes the order of medicines (stages) but also optimizes the selection of medicine boxes (states).

[0123] In the automated dispensing system with two inbound / outbound station configurations, the average picking time of the above four methods is statistically shown in Table 2 based on different pharmacists' picking time parameters.

[0124]

[0125] Table 2: Comparison of average picking time for four methods under different parameters

[0126] Clearly, the method proposed in this invention significantly reduces the average picking time, thus improving the efficiency of the automated dispensing system in a human-machine collaborative environment.

[0127] The specific embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the present invention is not limited to the above embodiments. Within the scope of knowledge possessed by those skilled in the art, various changes can be made without departing from the spirit of the present invention.

Claims

1. A dual-command retrieval and sorting method suitable for automated dispensing systems, characterized in that, include: An automated dispensing system with two entry / exit configurations is constructed, the automated dispensing system including a robotic arm for storing and retrieving medicine boxes; Based on the dual-command cycle retrieval mode, the travel time of mechanically retrieving medicine boxes is characterized; To address the randomness of pharmacist service hours, a dual-command retrieval and sorting model in a human-machine collaborative environment is constructed to optimize the retrieval order of drugs in adjacent prescription orders. In the dual-command retrieval and sorting model, prescription orders arrive consecutively and are processed according to the first-come-first-served rule. The dual-command retrieval and ranking model is as follows: Objective function: （2）； Constraints: （3）； （4）； （5）； （6）； （7）； （8）； （9）； （10）； （11）； （12）； （13）； （14）； （15）； In the formula, This indicates a drug number index. The total number of medications in each prescription order. , Indicating inbound / outbound indexes, , The number index indicating the entry / exit position. This indicates that the medicine shelf contains medicines. The location of the medicine box was gathered. This represents the set of all medicine box locations for all medications in each prescription order, i.e. , This represents the set of all positions on the medicine shelf, i.e. , Indicates the total number of positions. , Then it represents any real number; The objective function (2) represents minimizing the average picking time of prescription orders in a human-machine collaborative environment, assuming the pharmacist's random picking time. It follows a normal distribution, that is ,in The mean, If the standard deviation is , then ; Constraint (3) ensures position The remaining inventory meets the dosage required for the prescription drug; Constraint (4) marks the start of the retrieval sequence, meaning the robotic arm needs to first return the medicine box from the in / out station to the storage location before retrieving the location of the new medicine box. ; Constraints (5) and (6) restrict each order and each drug location to be retrieved at most once; Constraint (7) restricts the number of input arcs at each point to be equal to the number of output arcs; Constraint (8) Avoid duplicate searches for drugs; Constraint (9) ensures that the robotic arm retrieves one drug location and then retrieves another drug location; Constraint (10) ensures that the difference in the number of double command cycle operations executed by the robotic arm starting from the two entry / exit stations does not exceed 1; Constraint (11) states that a new prescription order may have at most two types of drugs that are the same as those in the previous prescription order. If the new prescription order includes the last two drug requests in the previous prescription order, the pharmacist will sort them directly at the in / out station. Constraint (12) ensures that One double-command cycle operation; Constraint (13) is to eliminate constraints on the sub-loop; In constraint (14) For 0-1 variables, Indicates the location accessed by the robotic arm. Access location immediately after ,otherwise ; In constraint (15) For 0-1 variables, This indicates two medicine boxes containing medications from newly arrived prescription orders, which pharmacists can directly sort without requiring a robotic arm to retrieve them again; otherwise... .

2. The dual-command retrieval and sorting method for automated dispensing systems according to claim 1, characterized in that, The construction of the automated dispensing system under two entry / exit station configurations includes: The automated dispensing systems all have double-sided medicine racks, totaling [number missing]. There are 10 locations, each containing a medicine box of equal volume, and each medicine box contains only one type of medicine. The automated dispensing system also includes a crane, with a track in the middle of the double-sided medicine rack, allowing the crane to move at a speed... Parallel movement; a robotic arm is mounted on the crane, and the robotic arm moves along the crane at a speed... Vertical movement; two entry / exit stations are set at the lower center of the first side of the medicine shelf; robotic arm in time The medicine box is transported to an in / out station, while pharmacists sort it at random times. The robotic arm and pharmacist simultaneously process medications from another medicine box inside the station, working collaboratively for a period of time. .

3. The dual-command retrieval and sorting method for automated dispensing systems according to claim 1, characterized in that, The dual-command cycle-based retrieval mode characterizes the travel time of the mechanical medicine box, including: The dual-command cycle retrieval mode refers to the system simultaneously executing storage and retrieval requests within one cycle. The cycle time is defined as the sum of the time to retrieve the medicine box, the time to travel to the storage location and store the medicine box, the travel time from the storage location to the retrieval location, and the time to retrieve the medicine box and transport it to the in / out station. In dual-command retrieval mode, the robotic arm returns the medicine box to its storage location. And retrieve location Travel time of the medicine box The calculation is shown in equation (1): （1）； In the formula, ( ), ( (This refers to the location on the medicine shelf) ( The x and y coordinates of ) , These are the x and y coordinates for entering and exiting the station, respectively. Two entering / exiting stations are adjacent. , These are the length and height of a medicine box, respectively. This refers to the movement speed of the robotic arm in the horizontal and vertical directions.

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