A radiotherapy warehouse management system order processing method

Abstract

This invention relates to the technical field of radiotherapy mold storage management, and more specifically, to an order processing method for a radiotherapy storage management system, comprising the steps of: acquiring the treatment rate and shelf status of each machine room; determining the treatment interval based on the treatment rate, and generating a set of tasks to be executed in conjunction with the shelf status; calculating priorities for picking tasks and storage tasks respectively in response to the set of tasks to be executed; determining a subset of executable tasks based on the priorities and the available quantity of warehouse shelves; for tasks in the subset of executable tasks, selecting and allocating the automated guided vehicle (AGV) that satisfies anti-congestion constraints and has the shortest total execution time; and executing the highest priority task according to the priorities and allocation results. This invention can dynamically adapt to the differentiated treatment interval requirements of different machine rooms, effectively utilize handling and storage resources, and avoid AGV congestion.

Description

Technical Field

[0001] This invention relates to the technical field of radiotherapy mold storage management, and more specifically, to an order processing method for a radiotherapy storage management system. Background Technology

[0002] Radiation therapy differs from other treatments because each person's body shape and lesions are different. Therefore, each patient has one or more sets of special molds that match their individual body shape and lesions to facilitate the implementation of the treatment plan. However, in reality, due to a combination of factors such as hospital facilities, level of informatization, and management model, chaotic mold management often occurs, hindering patients' normal radiotherapy, affecting doctors' treatment efficiency, and even interrupting the treatment process.

[0003] Due to the special nature of radiotherapy, in order to make the entire radiotherapy process information-controlled, intelligent and efficient, a radiotherapy storage management system has been designed, including a warehouse, multiple computer rooms and at least one unmanned transport vehicle, which transports radiotherapy molds between storage shelves in the warehouse and computer rooms.

[0004] Existing technology discloses an order processing method, apparatus, equipment, and storage medium. By acquiring the expected outbound time of orders to be processed and the handling task information of orders in progress, the "critical processing time" of each order is calculated, and a priority order is determined accordingly. This allows for order processing according to priority, thereby improving material handling efficiency while meeting the timeliness requirements of orders to be processed. However, in radiotherapy warehouse management systems, the use of radiotherapy molds is related to the frequency of patient treatment in each machine room. This solution cannot dynamically adapt to the differentiated treatment interval requirements of different machine rooms. Furthermore, radiotherapy warehouse management systems not only have path and task constraints for automated guided vehicles (AGVs), but also dual physical space constraints such as the upper limit of machine room shelf capacity and the upper limit of warehouse shelf capacity. This solution does not consider the potential congestion of AGVs caused by multiple tasks in the same machine room, nor does it consider the limitation on the number of shelves that can be processed simultaneously on the warehouse side. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of the prior art and provide an order processing method for a radiotherapy warehouse management system that can dynamically adapt to the different treatment interval requirements of different computer rooms, effectively utilize transportation and storage resources, and avoid congestion of unmanned transport vehicles.

[0006] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is: to provide an order processing method for a radiotherapy warehouse management system, comprising the following steps: S1: Obtain the treatment rate and rack status of each server room; S2: Determine the treatment interval based on the treatment rate, and generate a set of tasks to be executed in combination with the status of the server room rack; S3: In response to the set of tasks to be executed, calculate priorities for the picking task and the inventory task respectively; S4: Based on the aforementioned priority and the available quantity of warehouse shelves, determine a subset of executable tasks; S5: For tasks in the executable task subset, select the unmanned transport vehicle that satisfies the congestion prevention constraint and has the shortest total execution time for the task and assign it to the task. S6: Execute the highest priority task according to the priority and allocation results.

[0007] The radiotherapy warehousing management system order processing method of the present invention establishes a closed-loop scheduling logic from task generation to completion, introduces treatment interval calculation, combines the status of computer room shelves and warehouse shelves, and takes unmanned transport vehicle congestion and total task execution time as active constraints for task scheduling. It can dynamically adapt to the differentiated treatment interval requirements of different computer rooms, effectively utilize handling and storage resources and avoid unmanned transport vehicle congestion.

[0008] Preferably, in step S1, the expression for determining the treatment interval is: ; In the formula, Indicates the computer room number; Indicates computer room The treatment rate; Indicates computer room Treatment intervals.

[0009] Preferably, in step S2, the process of generating the set of tasks to be executed includes: Each time goods are picked up, the number of occupied shelves in the server room increases by 1; each time goods are stored, the number of occupied shelves in the server room decreases by 1. Based on the server room's shelf limit and the number of shelves already occupied, determine whether the server room meets the shelf constraints for generating new tasks: ; In the formula, Indicates the current time; Indicates computer room Last pickup time; Indicates the current time engine room The number of shelves already occupied; Indicates computer room The maximum shelf space limit; This represents the shelf constraint for generating new tasks. A value of 1 indicates that there are free shelves in the computer room, in which case a new task will be generated. A value of 0 indicates that all shelves in the computer room are occupied, in which case no new task will be generated.

[0010] Preferably, in step S3, calculating the priority for the pickup task includes: ; ; In the formula, Indicates computer room The theoretical time required for the new radiotherapy mold This indicates an adjustable urgency weight; Indicates computer room Basic priority; Indicates the relationship between 0 and Take the maximum value between them; Indicates task At the current time The pickup priority score.

[0011] By introducing the calculation of treatment intervals and the priority calculation of pickup tasks, the priority score is closely linked to the remaining time when the machine room actually needs new radiotherapy molds. This allows for dynamic response to the treatment frequency of different machine rooms, ensuring that machine rooms with short treatment intervals can obtain molds first, thus avoiding treatment interruptions caused by a shortage of radiotherapy molds.

[0012] Preferably, in step S3, calculating the priority for inventory tasks includes: ; In the formula, Indicates the weight of shelf occupancy rate; Indicates task At the current time Inventory priority score.

[0013] A priority formula based on the occupancy rate of the data center racks was designed for inventory tasks, which allows inventory tasks to be sent to data centers with more empty racks. This utilizes the idle rack space, balances the system load, and avoids a chain of scheduling problems caused by radiotherapy molds not being returned due to rack overflow.

[0014] Preferably, in step S4, the expression for the executable task subset is: ; In the formula, Indicates a subset of executable tasks; Indicates a set of tasks to be executed; Indicates task Ranking based on priority scores; Indicates the current time The number of warehouse shelves already occupied; This indicates the number of available shelves in the warehouse.

[0015] Preferably, in step S5, the calculation process for the total time taken by the unmanned transport vehicle to perform the task includes: ; ; ; In the formula, Indicates the number of the automated guided vehicle; Indicates unmanned transport vehicle Execute the task Total time spent; Indicates unmanned transport vehicle The remaining time to complete the current task; Indicates unmanned transport vehicle From the current task endpoint to the task The time taken to move from the starting point; Indicates computer room Time consumed during a single access to a radiotherapy mold; This indicates that automated guided vehicles (AGVs) are located between warehouse shelves and the server room. The length of the movement path of the shelf; Indicates the time required for a single warehouse transfer; Indicates the duration of a single connection to the data center; Indicates the moving speed of the automated guided vehicle; Indicates the number is Unmanned transport vehicles; Indicates unmanned transport vehicle At the current time From the endpoint of the currently executing task to the task The distance traveled between the destinations.

[0016] Preferably, in step S5, the expression for the unmanned transport vehicle that satisfies the congestion prevention constraint is: ; In the formula, Indicates the task At the current time Filter and sort the available automated guided vehicles; Indicates the current time engine room The number of unmanned transport vehicles performing tasks within the facility; Indicates the number is Unmanned transport vehicles; This indicates the preset congestion prevention threshold; A function representing the sorting criteria; The process of selecting the automated guided vehicle with the shortest total time is as follows: ; In the formula, Indicates the current time Execute the task The unmanned transport vehicle with the shortest total time.

[0017] Preferably, in step S6, the task to be performed and the assigned unmanned vehicle are: ; In the formula, Indicates the highest priority task; Indicates the current time Execute the task The automated guided vehicle with the shortest total time; This represents the scheduling decision function.

[0018] Preferably, the expression for the actual end time of the task is: ; In the formula, Indicates the actual end time of the task.

[0019] Compared with the prior art, the beneficial effects of this invention are as follows: (1) By introducing the calculation of treatment interval and the priority calculation for picking up tasks, the priority score is closely linked to the remaining time when the machine room actually needs new radiotherapy molds. It can dynamically adapt to the different treatment interval requirements of different machine rooms, ensuring that machine rooms with short treatment intervals can obtain molds first, and avoiding treatment interruption caused by radiotherapy mold shortage. (2) The inventory task and the picking task were distinguished, and a priority formula based on the rack occupancy rate of the computer room was designed for the inventory task, so that the inventory task can be sent to the computer room with more rack space, thereby utilizing the idle rack space, balancing the system load, and avoiding the chain scheduling problem caused by the radiotherapy mold not being able to be returned due to the rack overflow. (3) The dual constraints of the computer room rack capacity and the warehouse rack capacity are considered in the warehouse scheduling. The generation of tasks is controlled by the rack constraints of the computer room, the release of tasks is controlled by calculating the subset of executable tasks, and the computer room is avoided by screening through unmanned transport vehicles. The global collaborative optimization of transportation resources and storage resources is realized, which ensures that radiotherapy molds are available in the computer room and maximizes the transportation efficiency of unmanned transport vehicles for radiotherapy molds. Attached Figure Description

[0020] Figure 1 This is a flowchart of the order processing method of the radiotherapy warehouse management system in an embodiment of the present invention. Detailed Implementation

[0021] The present invention will be further described below with reference to specific embodiments.

[0022] Example 1 A radiotherapy warehouse management system order processing method includes the following steps: S1: Obtain the treatment rate and rack status of each server room; S2: Determine the treatment interval based on the treatment rate and generate a set of tasks to be executed in combination with the status of the server room shelves; S3: In response to the set of tasks to be executed, calculate priorities for picking tasks and inventory tasks respectively; S4: Determine a subset of executable tasks based on priority and the number of available warehouse shelves; S5: For tasks in the executable task subset, select the unmanned transport vehicle that satisfies the congestion prevention constraint and has the shortest total execution time for the task; S6: Execute the highest priority task based on priority and allocation results.

[0023] The above-mentioned radiotherapy warehouse management system order processing method introduces treatment interval calculation, combines the status of computer room shelves and warehouse shelves, and uses unmanned transport vehicle congestion and total task execution time as active constraints for task scheduling. It establishes a closed-loop scheduling logic for the entire link from task generation to completion, which can dynamically adapt to the differentiated treatment interval requirements of different computer rooms, effectively utilize handling and storage resources, and avoid unmanned transport vehicle congestion.

[0024] In step S1, the expression for determining the treatment interval is: ; In the formula, Indicates the computer room number; Indicates computer room The treatment rate; Indicates computer room Treatment intervals.

[0025] Step S2, the process of generating the set of tasks to be executed includes: Each time goods are picked up, the number of occupied shelves in the server room increases by 1; each time goods are stored, the number of occupied shelves in the server room decreases by 1. Based on the server room's shelf limit and the number of shelves already occupied, determine whether the server room meets the shelf constraints for generating new tasks: ; In the formula, Indicates the current time; Indicates computer room Last pickup time; Indicates the current time engine room The number of shelves already occupied; Indicates computer room The maximum shelf space limit; This represents the shelf constraint for generating new tasks; a value of 1 generates a new task, while a value of 0 does not generate a new task.

[0026] A new task will only be generated when the number of shelves currently occupied in the computer room is less than the upper limit and the time since the last supply to the computer room exceeds the treatment interval. This can automatically prevent the delivery of new radiotherapy molds to computer rooms with full shelves and avoid duplicate delivery to computer rooms that have just received radiotherapy molds. This achieves on-demand and timely task generation and saves transportation resources.

[0027] In step S3, calculating the priority for the pickup task includes: ; ; In the formula, Indicates computer room The theoretical time required for the new radiotherapy mold This indicates an adjustable urgency weight; Indicates computer room Basic priority; Indicates the relationship between 0 and Take the maximum value between the two to avoid the final result of the priority being negative; Indicates task At the current time The pickup priority score.

[0028] The lower the score, the more urgent the situation. The lowest score is given the highest priority. By adopting proactive prediction based on treatment needs, the machine room that is about to run out of materials can be prioritized.

[0029] In this embodiment, by introducing the calculation of treatment interval and the priority calculation for picking tasks, the priority score is closely linked to the remaining time when the machine room actually needs new radiotherapy molds. Compared with the traditional method that only relies on the static expected outbound time, this embodiment can dynamically respond to the treatment frequency of different machine rooms, ensuring that machine rooms with short treatment intervals can obtain molds first, thus avoiding treatment interruption caused by radiotherapy mold shortage.

[0030] Example 2 This embodiment is similar to Embodiment 1, except that in step S3, calculating the priority for the inventory task includes: ; In the formula, Indicates the weight of shelf occupancy rate; Indicates task At the current time Inventory priority score.

[0031] When an automated guided vehicle needs to store a disinfected or used radiotherapy mold back to a machine room, it will prioritize machine rooms with lower shelf occupancy rates.

[0032] In this embodiment, inventory tasks and retrieval tasks are distinguished, and a priority formula based on the occupancy rate of the data center shelves is designed for inventory tasks. This allows inventory tasks to be sent to data centers with more empty shelves, thereby utilizing the idle shelf space, balancing the system load, and avoiding the chain scheduling problems caused by the inability to return radiotherapy molds due to overflowing shelves.

[0033] Example 3 This embodiment is similar to Embodiment 2, except that in step S4, the expression for the executable task subset is: ; In the formula, Indicates a subset of executable tasks; Indicates a set of tasks to be executed; Indicates task Ranking based on priority scores; Indicates the current time The number of warehouse shelves already occupied; This indicates the number of available shelves in the warehouse.

[0034] As a shared resource, the warehouse can only handle a limited number of moving tasks simultaneously. All pending tasks are prioritized and scored, and only the highest-ranking tasks are released. By adding a subset of tasks to the executable task set, the problem of task backlog and deadlock at the warehouse entrance is resolved, ensuring that warehouse resources are not heavily occupied by low-priority tasks and guaranteeing the overall throughput of the system.

[0035] In step S5, the calculation process for the total time taken by the unmanned transport vehicle to perform the task includes: ; ; ; In the formula, Indicates the number of the automated guided vehicle; Indicates unmanned transport vehicle Execute the task Total time spent; Indicates unmanned transport vehicle The remaining time to complete the current task; Indicates unmanned transport vehicle From the current task endpoint to the task The time taken to move from the starting point; Indicates computer room Time consumed during a single access to a radiotherapy mold; This indicates that automated guided vehicles (AGVs) are located between warehouse shelves and the server room. The length of the movement path of the shelf; Indicates the time required for a single warehouse transfer; Indicates the duration of a single connection to the data center; Indicates the moving speed of the automated guided vehicle; Indicates the number is Unmanned transport vehicles; Indicates unmanned transport vehicle At the current time From the endpoint of the currently executing task to the task The distance traveled between the destinations.

[0036] This embodiment accurately estimates task time and ensures that connection time is fully included, avoiding scheduling deviations caused by ignoring interface time.

[0037] In step S5, the expression for the unmanned transport vehicle that satisfies the congestion prevention constraint is: ; In the formula, Indicates the task At the current time Filter and sort the available automated guided vehicles; Indicates the current time engine room The number of unmanned transport vehicles performing tasks within the facility; Indicates the number is Unmanned transport vehicles; This indicates the preset congestion prevention threshold; A function representing the sorting criteria; The process of selecting the automated guided vehicle with the shortest total time is as follows: ; In the formula, Indicates the current time Execute the task The unmanned transport vehicle with the shortest total time.

[0038] This embodiment directly solves the practical problem of multiple unmanned transport vehicles queuing, interlocking, or even colliding at the same machine room entrance in radiotherapy scenarios by using anti-blocking constraints, which greatly improves the stability and safety of system operation.

[0039] In step S6, the tasks to be performed and the assigned driverless vehicles are as follows: ; In the formula, Indicates the highest priority task; Indicates the current time Execute the task The automated guided vehicle with the shortest total time; This represents the scheduling decision function.

[0040] In the overall task sorting, picking tasks and inventory tasks are sorted separately, with picking tasks having a higher priority than inventory tasks. The task with the lowest picking priority score is the highest priority task.

[0041] The expression for the actual end time of the task is: ; In the formula, Indicates the actual end time of the task.

[0042] This embodiment considers the dual constraints of data center rack capacity and warehouse rack capacity in warehouse scheduling. It controls task generation by controlling the rack constraints of the data center, controls task release by calculating a subset of executable tasks, and avoids data center congestion by using unmanned transport vehicles. This achieves global collaborative optimization of transportation and storage resources, ensuring that radiotherapy molds are available in the data center and maximizing the transportation efficiency of unmanned transport vehicles for radiotherapy molds.

[0043] In the specific implementation of the above embodiments, the technical features can be combined in any non-contradictory way. For the sake of brevity, not all possible combinations of the above technical features are described. However, as long as the combination of these technical features is not contradictory, it should be considered to be within the scope of this specification.

[0044] Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the implementation of the present invention. Those skilled in the art can make other variations or modifications based on the above description. It is neither necessary nor possible to exhaustively describe all embodiments here. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the claims of the present invention.

Claims

1. A method for order processing in a radiotherapy warehouse management system, characterized in that, Includes the following steps: S1: Obtain the treatment rate and rack status of each server room; In step S1, the expression for determining the treatment interval is: ； In the formula, Indicates the computer room number; Indicates computer room The treatment rate; Indicates computer room Treatment interval; S2: Determine the treatment interval based on the treatment rate, and generate a set of tasks to be executed in combination with the status of the server room rack; Step S2, the process of generating the set of tasks to be executed includes: Each time goods are picked up, the number of occupied shelves in the server room increases by 1; each time goods are stored, the number of occupied shelves in the server room decreases by 1. Based on the server room's shelf limit and the number of shelves already occupied, determine whether the server room meets the shelf constraints for generating new tasks: ； In the formula, Indicates the current time; Indicates computer room Last pickup time; Indicates the current time engine room The number of shelves already occupied; Indicates computer room The maximum shelf space; This represents the shelf constraint for generating new tasks; a value of 1 indicates that a new task is generated, while a value of 0 indicates that no new task is generated. S3: In response to the set of tasks to be executed, calculate priorities for the picking task and the inventory task respectively; In step S3, calculating the priority for the pickup task includes: ； ； In the formula, Indicates computer room Theoretically, the time required for the new radiotherapy mold is... This indicates an adjustable urgency weight; Indicates computer room Basic priority; Indicates the relationship between 0 and Take the maximum value between them; Indicates task At the current time Pickup priority score; S4: Based on the aforementioned priority and the available quantity of warehouse shelves, determine a subset of executable tasks; S5: For tasks in the executable task subset, select the unmanned transport vehicle that satisfies the congestion prevention constraint and has the shortest total execution time for the task and assign it to the task. S6: Execute the highest priority task according to the priority and allocation results.

2. The order processing method of the radiotherapy warehousing management system according to claim 1, characterized in that, In step S3, calculating the priority for inventory tasks includes: ； In the formula, Indicates the weight of shelf occupancy rate; Indicates task At the current time Inventory priority score.

3. The order processing method of the radiotherapy warehousing management system according to claim 2, characterized in that, In step S4, the expression for the executable task subset is: ； In the formula, Indicates a subset of executable tasks; Indicates a set of tasks to be executed; Indicates task Ranking based on priority scores; Indicates the current time The number of warehouse shelves already occupied; This indicates the number of available shelves in the warehouse.

4. The order processing method of the radiotherapy warehousing management system according to claim 3, characterized in that, In step S5, the calculation process for the total time taken by the unmanned transport vehicle to perform the task includes: ； ； ； In the formula, Indicates the number of the automated guided vehicle; Indicates unmanned transport vehicle Execute the task Total time spent; Indicates unmanned transport vehicle The remaining time to complete the current task; Indicates unmanned transport vehicle From the current task endpoint to the task The time taken to move from the starting point; Indicates computer room Time consumed during a single access to a radiotherapy mold; This indicates that automated guided vehicles (AGVs) are located between warehouse shelves and the server room. The length of the movement path of the shelf; Indicates the time required for a single warehouse transfer; Indicates the duration of a single connection to the data center; Indicates the moving speed of the automated guided vehicle; Indicates the number is Unmanned transport vehicles; Indicates unmanned transport vehicle At the current time From the endpoint of the currently executing task to the task The distance traveled between the destinations.

5. The order processing method of the radiotherapy warehouse management system according to claim 4, characterized in that, In step S5, the expression for the unmanned transport vehicle that satisfies the congestion prevention constraint is: ； In the formula, Indicates the task At the current time Filter and sort the available automated guided vehicles; Indicates the current time engine room The number of unmanned transport vehicles performing tasks within the premises; Indicates the number is Unmanned transport vehicles; This indicates the preset congestion prevention threshold; A function representing the sorting criteria; The process of selecting the automated guided vehicle with the shortest total time is as follows: ； In the formula, Indicates the current time Execute the task The unmanned transport vehicle with the shortest total time.

6. The order processing method of the radiotherapy warehousing management system according to claim 5, characterized in that, In step S6, the tasks to be performed and the assigned driverless vehicles are as follows: ； In the formula, Indicates the highest priority task; Indicates the current time Execute the task The automated guided vehicle with the shortest total time; This represents the scheduling decision function.

7. The order processing method of the radiotherapy warehousing management system according to claim 6, characterized in that, The expression for the actual end time of the task is: ； In the formula, Indicates the actual end time of the task.

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