A robust surgery scheduling method and system based on dual resource constraints

Abstract

The application relates to a kind of robust surgery scheduling method and system based on double resource constraints, method includes the following steps: obtaining surgery demand information;According to surgery demand information, define double resource constraint condition, get scheduling result by constructing double vector coding;Based on scheduling result, the key surgery sequence sequence that determines the total completion time of surgery is identified as the critical path, the order or surgery scheme of key surgery sequence sequence is replaced using search operator, generate new scheduling scheme, and evaluate the fitness of new scheduling scheme, fitness is set based on the total completion time of surgery, if the fitness of new scheduling scheme is less than the fitness of current scheduling result, then update scheduling result and critical path, repeat this step until termination condition is reached, obtain final scheduling result;Output the surgery scheduling scheme corresponding to final scheduling result.Compared with prior art, the application has the advantages of high resource utilization, high flexibility and the like.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of resource scheduling, in particular to a robust surgery scheduling method and system based on double resource constraints. BACKGROUND

[0002] In the modern medical system, with the continuous expansion of the hospital scale and the increasing demand for surgery, surgery scheduling has become a crucial link in hospital management.

[0003] Traditional surgery scheduling methods often rely on manual judgment and paper records, which have the following defects: (1) Traditional surgery scheduling methods are difficult to estimate surgery duration, reasonably allocate operating room resources, and coordinate complex factors such as doctor scheduling, resulting in low operating room utilization, uneven doctor workload, and long patient waiting time. (2) In large hospitals, surgeons need to perform multiple tasks, including surgery, outpatient service, training, etc. Traditional scheduling methods are even more difficult to meet such diverse needs.

[0004] Therefore, there is an urgent need for a more intelligent and efficient surgery scheduling system to solve the above problems, to achieve reasonable allocation of operating rooms and reasonable scheduling of doctors, to improve the utilization rate of operating rooms, and to shorten the waiting time of patients. SUMMARY

[0005] The purpose of the present application is to overcome the defects of the prior art and provide a robust surgery scheduling method and system based on double resource constraints.

[0006] The purpose of the present application can be achieved by the following technical solutions:

[0007] A robust surgery scheduling method based on double resource constraints, comprising the following steps:

[0008] S1: Obtain surgery demand information;

[0009] S2: According to the surgery demand information, define the double resource constraint condition, and obtain the scheduling result by constructing double vector coding;

[0010] S3: Based on the scheduling result, identify the key surgery sequence sequence that determines the total completion time of the surgery as the critical path, replace the order or surgery scheme of the key surgery sequence sequence using a search operator, generate a new scheduling scheme, and evaluate the fitness of the new scheduling scheme. The fitness is set based on the total completion time of the surgery. If the fitness of the new scheduling scheme is less than the fitness of the current scheduling result, update the scheduling result and the critical path, repeat the step until the termination condition is reached, and obtain the final scheduling result;

[0011] S4: Output the surgery scheduling scheme corresponding to the final scheduling result.

[0012] Further, the surgery demand information includes a surgery to be scheduled, a surgeon to be scheduled, an operating room to be scheduled, and a time required for the surgery.

[0013] Further, the double vector encoding includes a surgery vector sequence and a medical resource allocation sequence, the medical resource allocation sequence including medical staff allocation and operating room allocation information, the surgery vector sequence being generated by random combination, and the medical resource allocation sequence with the shortest surgery duration being generated.

[0014] Further, an expression of the double vector encoding is as follows:

[0015]

[0016] wherein b(i v j x r y ) represents a start time of surgery I i under resource (R j , Sur r ); f(i v j x r y ) represents a completion time of surgery I i under resource (R j , Sur r ); represents a duration of surgery I i under resource (R j , Sur r ) constraint; f(j x -1 ) is a completion time of a previous surgery in operating room R j ; f(r y- ) is a completion time of a previous surgery of surgeon Sur r ; v represents that a current surgery numbered I i is the vth surgery performed among all surgeries, x is the xth surgery of current surgery I i in operating room R j , and y means that surgery I i is the yth surgery of surgeon Sur r .

[0017] Further, the search operator includes an exchange operator and a re-allocation operator, the exchange operator being an exchange of the order of two surgeries on a critical path, and the re-allocation operator being a replacement of a certain surgery on the critical path with another available combination of operating room and surgeon.

[0018] Further, an expression for calculating the total surgery completion time is as follows:

[0019]

[0020] wherein, denotes the xth surgery I i in the operating room R j under the scheduling scheme s, performed by the doctor Sur r yth surgery performed by the doctor Sur denotes the xth surgery I i in the operating room R j under the scheduling scheme s, performed by the doctor Sur r yth surgery performed by the doctor Sur denotes the xth surgery I i performed by the doctor Sur j in the operating room R r s ijr denotes whether the xth surgery I i is performed by the doctor Sur j in the operating room R r s ijr = 1, otherwise s ijr = 0.

[0021] In a second aspect of the present application, a robust surgery scheduling system based on double resource constraints is provided. When the system is running, any one of the robust surgery scheduling methods based on double resource constraints is executed. The system comprises a data input module and a data processing module, a big data storage database, and a scheduling system management terminal.

[0022] The data input module is a front-end interface of the surgery scheduling system, used for inputting data required for surgery scheduling, including patient basic information, doctor scheduling information, operating room resource information, and surgery demand information.

[0023] The data processing module is connected with the data input module, used for analyzing and processing data required for surgery scheduling, integrating any one of the robust surgery scheduling methods based on double resource constraints, generating a surgery scheduling scheme, and further comprising a performance monitoring module, a parameter tuning module, and an error handling module.

[0024] The big data storage database is connected with the data input module and the data processing module, used for storing and managing all data generated by the surgery scheduling system, having data retrieval, complex query, and secure storage functions.

[0025] The management terminal is connected with the data processing module and the big data storage database, comprising a user interface for viewing surgery arrangements, resource usage, statistical reports, and performing manual adjustments and management operations.

[0026] Further, the data input module supports multiple methods for inputting data, including keyboard input method, code scanning input method, voice input method and electronic medical record system calling method.

[0027] Further, the big data storage processing database comprises a data collection and preprocessing module, a data storage module, a data updating and maintenance module, a data analysis module and a data encryption module.

[0028] Further, the management terminal comprises a core function module and an auxiliary function module, the core function module comprises a visual interface, a surgery data input, a surgery progress tracking, a resource information input, a resource allocation, an interactive operation, a permission management, a scheduling scheme calculation, a dynamic adjustment function, a scheduling notification, a scheduling report generation, a data analysis function, a decision support function, a system configuration function and an update and maintenance function, and the auxiliary function module comprises a user management function, a message notification function, a historical notification record, a data backup function, a fault troubleshooting function, a real-time resource monitoring and a resource demand prediction function.

[0029] Compared with the prior art, the present application has the following beneficial effects:

[0030] 1) The present application establishes a double resource constraint resource scheduling method, which allocates surgery order, surgery doctor and surgery room, identifies the key surgery order sequence that determines the total completion time of surgery, uses search operator to find the neighborhood solution of the critical path, obtains the scheduling scheme, evaluates the fitness of the scheduling scheme, solves the optimal surgery scheme combination, reasonably allocates surgery order, surgery time, doctor allocation and surgery room allocation, avoids resource conflict, and more efficiently utilizes medical resources.

[0031] 2) The system of the present application effectively supports the application of the method of the present application, simplifies the difficulty of data collection and management through the management terminal, facilitates real-time tracking of surgery progress, and can update the surgery arrangement in time when the surgery is completed in advance or delayed, improving the flexibility of surgery arrangement. BRIEF DESCRIPTION OF DRAWINGS

[0032] Figure 1 is a method flowchart of the present application;

[0033] Figure 2 is a system workflow diagram of the present application;

[0034] Figure 3 is a system implementation block diagram of the present application. DETAILED DESCRIPTION

[0035] The present application will be described in detail below in conjunction with the drawings and specific embodiments. The present embodiment is implemented on the basis of the technical scheme of the present application, and gives a detailed implementation manner and specific operation process, but the protection scope of the present application is not limited to the following embodiments.

[0036] Embodiment 1

[0037] As Figure 1 shown, the present application is a robust surgical scheduling method based on double resource constraints, comprising the following steps:

[0038] S1: obtaining surgical demand information;

[0039] Obtain surgical demand information from the hospital information system (HIS), including patient basic information, surgical type, expected surgical time, relevant surgical time in big data storage database, take the mean of expected surgical time and all relevant surgical time as the surgical time of the surgery. Collect operating room resource information, including open surgical type of operating room, equipment configuration, daily available time period, etc. Statistics of medical staff's scheduling, skill expertise and other resource information.

[0040] S2: defining double resource constraint conditions according to the surgical demand information, and obtaining scheduling results by constructing double vector coding;

[0041] Define double resource constraint conditions, including operating room resource constraints (such as the number of operating rooms, the limitation of different doctors available operating rooms, and the limitation of open time) and medical staff resource constraints (such as the scheduling conflict of doctors, the limitation of doctors' working time).

[0042] Construct an optimization model with the goal of minimizing total surgical waiting time, maximizing operating room utilization and medical staff working efficiency.

[0043] Double vector coding includes surgical vector sequence and medical resource allocation sequence, and medical resource allocation sequence includes medical staff allocation and operating room allocation information. The surgical vector sequence is generated by random combination, and the medical resource allocation sequence with the shortest surgical duration is generated.

[0044] Specifically, fruit fly optimization algorithm (FOA) is used for optimization scheduling. Two vectors are used to represent each fruit fly, namely surgical sequence vector (SSV) and medical resource allocation vector (MAV). Here, medical resources are double resources, which contain two parts: surgeons and operating rooms. For fruit fly algorithm, the coding consists of SSV and MAV. When initialized, the initial SSV is generated by randomly sorting from the candidate set of surgeries, and the MAV is generated by the resource with the shortest surgical duration from all resources.

[0045] Select the surgery one by one from left to right in SSV; then arrange the start time of the surgery in the specified operating room by the specified surgeon at the earliest available time

[0046] For the non-first surgery of the doctor, the start time b(i v j xr y ) and end time f(i v j x r y ) can be calculated according to the following steps: the start time of the surgery depends on two factors: the completion time f(j j ) of the previous surgery in the operating room R x-1 ; the maximum completion time f(r y- ) of the previous surgery of the same surgeon (in the same operating room or different operating rooms). The expression of the double vector coding is:

[0047]

[0048] where b(i v j x r y ) represents the start time of surgery I i in resources (R j , Sur r ); f(i v j x r y ) represents the completion time of surgery I i in resources (R j , Sur r ); represents the duration of surgery I i under the constraints of resources (R j , Sur r ); f(j x -1 ) is the completion time of the previous surgery in the operating room R j ; f(r y- ) is the completion time of the previous surgery of the surgeon Sur r ; v represents the current surgery numbered I i is the vth surgery performed among all surgeries, x is the xth surgery of the current surgery I i in the operating room R j , and y means that the surgery I i is the yth surgery of the surgeon Sur r .

[0049] S3: Based on the scheduling result, identify the critical surgery sequence sequence that determines the total completion time of the surgery as the critical path, replace the order or surgery scheme of the critical surgery sequence sequence using the search operator, generate a new scheduling scheme, and evaluate the fitness of the new scheduling scheme. The fitness is based on the total completion time of the surgery. If the fitness of the new scheduling scheme is less than the fitness of the current scheduling result, update the scheduling result and the critical path, and repeat this step until the termination condition is reached to obtain the final scheduling result.

[0050] Specifically: two operators are used to generate the neighborhood solution in the critical path, one is the exchange operator (SO), the other is the reassignment operator (RO). For the index of solving the maximum completion time C(s), the critical path is the path with the longest completion time of the current solution. Changing the operation order or reassigning the operation resources on the critical path has a great possibility to change the maximum completion time. SO is achieved by exchanging two operations in the critical path. RO is achieved by reassigning a combination of another feasible resource to the operation in the critical path, here, using the alternative resource (other surgeons) available in the same operating room to replace the original resource in the critical path. The calculation expression of the total operation completion time is:

[0051]

[0052]

[0053] wherein, denotes the completion time of the yth operation of the xth operation in the operating room R i under the scheduling scheme s, performed by the surgeon Sur j . r denotes the start time of the yth operation of the xth operation in the operating room R i under the scheduling scheme s, performed by the surgeon Sur j . r denotes the duration of the operation I i performed by the surgeon Sur j in the operating room R r , s ijr denotes whether the operation I i is performed by the surgeon Sur j in the operating room R r , if yes, s ijr =1, otherwise s ijr =0.

[0054] S4: output the final scheduling result corresponding to the operation scheduling scheme.

[0055] Embodiment 2

[0056] The second embodiment of the present application proposes a robust operation scheduling system based on the method of embodiment 1: including a data input module and a data processing module, a big data storage database and a scheduling system management terminal;

[0057] ​​The data input module is a front-end interface of the surgery scheduling system, used for collecting and inputting various data required for surgery scheduling, including but not limited to patient basic information, doctor scheduling information, operating room resource information, and surgery demand information.

[0058] The data processing module is connected with the data input module, used for intelligent analysis and processing of the received data to generate a surgery scheduling scheme, which includes surgery type, surgery time, surgery priority sorting, resource utilization rate, resource allocation optimization, and conflict detection and resolution.

[0059] The big data storage database is connected with the data input module and the data processing module, used for storing and managing all data generated by the system, supporting fast retrieval, complex query, and safe storage of data.

[0060] The management terminal is connected with the data processing module and the big data storage database, providing a user interface for management personnel to view surgery arrangement, resource usage, statistical reports, and other information, and to perform necessary manual adjustment and management operations.

[0061] As shown in Figure 2 , the workflow of the system of the present application is as follows: data is collected through the data acquisition module, combined with the big data module using the fruit fly optimization algorithm, a surgery plan is generated in the data processing module, and the final surgery scheduling result is displayed through dynamic adjustment by the management terminal according to the actual situation.

[0062] As shown in Figure 3 , it is a scheduling implementation block diagram of each part of the system of the present application.

[0063] The data input module supports multiple methods of inputting data, and the specific method is as follows:

[0064] A1: A graphical user interface (GUI) is designed to facilitate quick data entry by medical staff. The data includes:

[0065] patient basic information (name, age, gender, contact information, medical record number, etc.);

[0066] doctor information (name, professional field, available surgery time period, surgery preference, etc.);

[0067] operating room resource information (number of operating rooms, equipment configuration, cleaning and disinfection status, special purpose restrictions, etc.);

[0068] surgery demand (surgery type, estimated duration, urgency, required medical staff and equipment, etc.);

[0069] A2: Multiple input methods such as scanning codes and voice input are supported to improve the convenience and accuracy of data entry;

[0070] A3: Integrated electronic medical record system interface, automatically obtain patient basic information and medical history.

[0071] The data processing module is connected with the data input module, and is used for intelligent analysis and processing of the received data to generate a surgery scheduling scheme. The processing includes surgery priority sorting, resource allocation optimization, and conflict detection and resolution. A fruit fly optimization algorithm based on double resource constraints is integrated to process the data, and the specific steps are as follows:

[0072] B1: Module initialization, load configuration file, set initial parameters of fruit fly optimization algorithm (such as population size, iteration number, initial position, etc.), and parameters of surgery scheduling model (such as resource type, surgery type, doctor and nurse scheduling rules, etc.).

[0073] B2: Data loading: load the data required for surgery scheduling from the database or file system, including basic information of surgery (such as surgery type, etc.), resource information (such as doctors, nurses, equipment required for surgery, etc.), and current resource status (such as idle operating room, available doctor and nurse schedule, etc.).

[0074] B3: According to the loaded data, construct a double resource constrained surgery scheduling model. The model involves solving objectives, solving constraints, and decision variables.

[0075] B4: Execution of fruit fly optimization algorithm under double resource constraints

[0076] Initialize fruit fly population: randomly generate initial surgery scheduling scheme as the initial position of fruit fly according to the set population size;

[0077] Start iteration, olfactory search: for each fruit fly, perform neighborhood search near its current position to generate a new surgery scheduling scheme. The search process considers resource constraints and dependencies between surgeries;

[0078] Fitness evaluation: calculate the fitness of the newly generated scheduling scheme, such as the weighted sum of surgery waiting time and total completion time. The fitness can be set according to the management requirements;

[0079] Visual positioning: compare the fitness of all fruit flies to find the current optimal solution;

[0080] Position update: update the position of fruit fly (i.e. surgery scheduling scheme) according to the result of visual positioning, move towards a better solution.

[0081] Critical path search: in each iteration, identify the critical path in the current optimal solution, and perform neighborhood search on the critical path to further optimize the scheduling scheme by adjusting the order of surgeries or resource allocation in the critical path.

[0082] Iteration End: Stop the iteration when the set number of iterations is reached or the fitness no longer improves significantly.

[0083] B5: Result Output.

[0084] Output Optimal Scheduling Scheme: Output the optimal surgery scheduling scheme found after iteration, including the specific time arrangement of each surgery, operating room allocation, doctor's schedule, etc.

[0085] Data Storage: Store the optimal scheduling scheme into the big data storage database for subsequent query and use.

[0086] B6: Module Maintenance and Optimization. Performance Monitoring: Monitor the running performance of the module, including calculation time, resource consumption, etc., to ensure the efficient operation of the module.

[0087] Parameter Tuning: According to the running situation of the module and the actual demand, the parameters of the fruit fly optimization algorithm are tuned to improve the solving quality and efficiency.

[0088] Error Handling: Add error handling mechanism in the process of data processing and algorithm execution to ensure the stability and reliability of the module.

[0089] Big Data Storage Database: Connect with the data input module and data processing module, used for storing and managing all data generated by the system, supporting fast retrieval, query and secure storage of data. This module is also used to store and analyze the time spent by various types of surgeries under different resources, which is an important support tool for hospital management and surgery scheduling optimization. The following is the specific work content of this module:

[0090] C1: Data Collection and Preprocessing

[0091] Data Source Identification: Determine the data sources to be collected, including the log system of the operating room, the medical information system (HIS), the electronic medical record system (EMR), etc.

[0092] Data Extraction: Extract surgery-related data from the above data sources regularly or in real time, including but not limited to surgery type, surgery date, surgery duration, surgery team (doctor, nurse, etc.), required resources (operating room, equipment, medicine, etc.) and resource usage duration, etc.

[0093] Data Cleaning: Clean the extracted data to remove duplicate, incorrect or incomplete data records to ensure data accuracy and consistency.

[0094] Data Formatting: Format the cleaned data into a unified format for subsequent storage and analysis.

[0095] C2: Data Storage

[0096] Database Design: Adopt a distributed database architecture based on data storage and analysis needs to improve data storage reliability and scalability.

[0097] Data Storage: Store formatted data in a distributed database system (e.g., HBase, Cassandra). Choose appropriate storage technology based on data volume and access patterns. Encrypt sensitive information such as patient privacy data to ensure data security.

[0098] Data Indexing: Create indexes for key fields (e.g., surgery type, date, resources) to improve data retrieval efficiency.

[0099] C3: Data Update and Maintenance

[0100] Incremental Data Capture: Implement incremental data capture strategies for real-time updated data sources to ensure that newly generated data can be added to the database in a timely manner.

[0101] Data Verification: Regularly verify stored data to ensure data integrity and accuracy.

[0102] Data Backup and Recovery: Develop data backup strategies to ensure quick recovery in case of data loss or damage.

[0103] C4: Data Analysis and Utilization

[0104] Data Query: Provide rich data query interfaces, supporting surgery type, resource usage, surgery duration, and other dimensions of query.

[0105] Statistical Analysis: Perform statistical analysis on stored data, such as calculating the average duration of each type of surgery and resource utilization rate, to provide data support for surgery scheduling and resource allocation.

[0106] Predictive Analysis: Use machine learning or statistical models to learn from historical data and predict future surgery time and resource requirements, further optimizing surgery scheduling and resource allocation.

[0107] Report Generation: Generate reports based on analysis results, including operating room efficiency evaluation and resource utilization rate reports, to provide decision support for hospital management.

[0108] C5: Data Security and Privacy Protection

[0109] Data Encryption: Encrypt sensitive data for storage to ensure data security.

[0110] Access Control: Implement strict access control policies to ensure that only authorized users can access sensitive data.

[0111] Privacy Protection: Compliance with relevant laws and regulations to ensure the protection and compliance handling of patient privacy information.

[0112] Through the above working method, the big data storage database module can effectively collect, store, analyze and utilize the operation related data, providing strong data support for hospital operation scheduling and resource allocation.

[0113] The operation scheduling management terminal is an integrated system designed to optimize the allocation of resources in the operating room and improve the efficiency of operation scheduling. The terminal includes a series of functional modules to realize the automation and intelligent management of the operation process. It includes core functional modules and auxiliary functional modules. The following is a detailed description of the specific content of the operation scheduling management terminal:

[0114] D1: Core functional modules

[0115] 1. User interface and interaction design:

[0116] Visual interface: Use intuitive graphical user interface (GUI) to display real-time status of operating room, list of pending operations, doctor and nurse scheduling, equipment resource occupation and idle situation, and other key information. For example, the following information:

[0117] Operation data entry: Enter basic information of operation, such as operation type, patient information, operation doctor, etc.

[0118] Operation progress tracking: Real-time tracking of operation progress, including operation start time, end time, operation stage, etc.

[0119] Resource information entry: Enter basic information and availability status of operating room, surgical equipment, medical staff and other resources.

[0120] Resource allocation: According to the operation demand, automatically or manually allocate operating room, surgical equipment and medical staff and other resources.

[0121] Interactive operation: Support simple operations such as drag and drop, click to make operation appointment, cancel, reschedule, and adjust the scheduling of doctors and nurses.

[0122] Permission management: Set different access permissions according to user roles (such as administrator, doctor, nurse, etc.), ensure data security and operation compliance.

[0123] 2. Operation scheduling optimization algorithm module

[0124] Double resource constraint algorithm: Built-in efficient double resource constraint scheduling algorithm (fruit fly algorithm), considering the double constraint conditions of operating room available time and doctor scheduling, automatically calculating and generating the optimal or near-optimal operation scheduling scheme.

[0125] Dynamic Adjustment Function: Supports automatic or manual adjustment of the scheduling plan based on real-time conditions (such as early completion of surgery, temporary leave of doctors, etc.), ensuring smooth surgical process.

[0126] Dispatch Execution: Convert the scheduling plan into specific surgical arrangements, including surgical order, surgical time, surgical location, etc., and notify relevant personnel to execute.

[0127] 3. Reporting and Notification Function

[0128] Generate Scheduling Report: Generate surgical scheduling reports regularly or on demand, including key indicators such as surgical completion, resource utilization, waiting time, etc., to provide data support for management decisions.

[0129] Notification and Reminders: Send surgical arrangements, resource changes, emergency notifications, etc. to relevant personnel through SMS, email or system internal messages, etc. to ensure timely and accurate information transmission.

[0130] 4. Data Analysis and Decision Support

[0131] Data Analysis Tools: Provide data analysis tools such as trend analysis, comparative analysis, correlation analysis, etc. to help managers better understand surgical scheduling efficiency, resource allocation rationality, etc.

[0132] Decision Support System: Based on data analysis results, provide decision-making suggestions for hospital management to optimize surgical processes and improve resource utilization.

[0133] 5. System Configuration and Maintenance

[0134] System Configuration: Allows administrators to adjust system parameters according to actual hospital conditions, such as the number of operating rooms, resource types, scheduling rules, etc.

[0135] System Update and Maintenance: Supports online software version upgrade, data backup and recovery, system log monitoring, etc. to ensure system stability and data security.

[0136] D2: Auxiliary Function Module

[0137] 1. User Management

[0138] Permission Settings: Set different permissions for different users to ensure data security and normal operation of the system.

[0139] User Information Maintenance: Manage user's basic information and login information, support user registration, login, password reset, etc.

[0140] 2. Message Notification

[0141] Real-time notification: Real-time notification of relevant personnel through system messages, SMS, email, etc. to inform the operation scheduling information, resource allocation, etc.

[0142] Historical record: Save notification records for easy user query and trace back.

[0143] 3. System maintenance

[0144] Data backup: Regular backup of system data to prevent data loss or damage.

[0145] System update: Support for system software updates and upgrades to meet new needs and solve potential problems.

[0146] Troubleshooting: Provide troubleshooting tools and methods to help users quickly locate and solve system problems.

[0147] 4. Resource monitoring and prediction

[0148] Real-time resource monitoring: Integrated real-time monitoring system to monitor the current status of hardware resources such as operating rooms, surgical instruments, anesthesia equipment, beds, and human resources such as doctors and nurses.

[0149] Resource demand prediction: Use big data analysis and machine learning algorithms to predict future resource demand trends based on historical surgery data, doctor preferences, patient conditions, etc.

[0150] D3: Technical implementation

[0151] The operation scheduling management terminal is usually based on modern information technology and data processing technology, including but not limited to:

[0152] Database technology: Used to store and manage data related to operation scheduling.

[0153] Optimization algorithm: Such as the fruit fly optimization algorithm mentioned in this article, used to generate the optimal operation scheduling scheme.

[0154] Network communication technology: Realize data exchange and communication between modules within the system and between the system and other systems.

[0155] User interface technology: Provide a friendly user interface for easy user operation and management.

[0156] In summary, the scheduling system management terminal is the core control platform of "a double resource constrained operation scheduling system", which realizes intelligent management and optimal scheduling of operation resources through highly integrated functional modules and advanced algorithm technology.

[0157] The functions are designed as independent software function units and can be saved in any computer accessible storage medium when they are put on the market or used by users as separate products. Based on this perspective, the core technical innovation of the present application or the improved part thereof to the prior art can be presented in the form of a software product stored in a specific storage medium, containing a series of instructions designed to guide a computing device (such as a personal computer, a server, or even a network device) to execute the complete process or part of the process described in the embodiments of the present application.

[0158] The aforementioned storage medium is widely ranged, including but not limited to portable storage devices such as U disk, mobile hard disk, and fixed storage devices such as read-only memory (ROM), random access memory (RAM), magnetic storage medium (such as magnetic disk), and optical storage medium (such as optical disk), etc., all of which can effectively carry and store the program code required to implement the present application.

[0159] The logical flow presented in the flowchart or the sequence of steps described herein can be regarded as a series of ordered executable instructions designed to achieve a specific logical function. These instructions can be specifically embedded in any form of computer readable medium for individual use or as part of the operation of various instruction execution systems, devices or apparatuses (such as computer-based systems, processor-based systems, and any system capable of obtaining and executing instructions from these systems). In the context of the present specification, "computer readable medium" is a broad concept that covers all physical media capable of carrying, storing, exchanging or transmitting programs for direct use by or as an aid to the operation of instruction execution systems, devices or apparatuses.

[0160] The various components of the present application can be realized by hardware, software, firmware or any combination thereof. In the given embodiments, a plurality of steps or method processes can be executed by software or firmware stored in a memory and operated by a suitable instruction execution system. Specifically, if a hardware implementation is adopted, technology widely recognized in the art can be used, including but not limited to: using logic gate circuits to build discrete logic circuits to realize the logical processing function of data signals, designing application specific integrated circuits (ASIC) and integrating appropriate combination logic gate circuits, or using programmable gate arrays (PGA), field programmable gate arrays (FPGA) and other programmable logic devices to achieve the goal, which can be used alone or in combination.

[0161] In summary, the double resource constraint surgery scheduling method and system can effectively improve the efficiency and quality of surgery scheduling, reduce patient waiting time and optimize hospital resource allocation by comprehensively considering the constraint conditions of operating room resources and medical staff resources and using the fruit fly optimization algorithm for solving.

[0162] The preferred embodiments of the present application have been described in detail above. It should be understood that those of ordinary skill in the art can make modifications and variations without departing from the concept of the present application. Therefore, any technical solutions obtained by logical analysis, reasoning or limited experiments based on the concept of the present application and the prior art in the technical field should be within the scope of protection defined by the claims.

Claims

1. A surgical scheduling method based on dual resource constraints, characterized in that: The following steps are involved: S1: Obtain surgical demand information; S2: Based on the surgical demand information, dual resource constraints are defined and the scheduling result is obtained by constructing dual vector encoding; S3: Based on the scheduling results, identify the key surgical sequence that determines the total completion time of the surgery as the critical path. Use the search operator to replace the order of the key surgical sequence or the surgical plan to generate a new scheduling plan. The fitness of the new scheduling plan is evaluated. The fitness is set based on the total completion time of the surgery. If the fitness of the new scheduling plan is less than the fitness of the current scheduling result, the scheduling result and the critical path are updated. Repeat this step until the termination condition is met to obtain the final scheduling result. S4: Outputting the surgical scheduling plan corresponding to the final scheduling result; The dual-vector encoding includes a surgical vector sequence and a medical resource allocation sequence, wherein the medical resource allocation sequence includes medical staff allocation and operating room allocation information. The surgical vector sequence is generated by random combination to generate a medical resource allocation sequence with the shortest surgical duration. The expression of the dual vector encoding is: Where, Representative surgery In Resources The start time of the next Representative surgery In Resources The completion time of the following; Indicates surgery duration of time under restraint; For operating room The completion time of the previous surgery; For doctors the completion time of the previous surgery; Indicates the number The current surgery is the first among all surgeries The surgery performed, Current surgery In the operating room Middle surgery, It refers to surgery For surgeons No. An operation.

2. A surgical scheduling method based on dual resource constraints according to claim 1, characterized in that: The surgical requirement information includes the surgery to be scheduled, the surgeon to be scheduled, the operating room to be scheduled, and the time required for the surgery.

3. The surgical scheduling method based on dual resource constraints according to claim 1, characterized in that: The search operator includes an exchange operator and a reallocation operator. The exchange operator exchanges the order of two operations on the critical path, and the reallocation operator replaces another available combination of operating room and doctor into a certain operation on the critical path.

4. The method for scheduling surgery based on dual resource constraints according to claim 1, characterized in that: The calculation expression of the total completion time of the operation is: Where, Indicates surgery Under scheduling plan s, it is the operating room The Surgery, performed by a doctor Executed The completion time of the surgery, Indicates surgery Under scheduling plan s, it is the operating room The Surgery, performed by a doctor Executed The start time of the surgery, Indicates surgery In the operating room Dr. Zhong You Duration of execution, Indicates whether surgery In the operating room Dr. Zhong You Surgery, if yes, ,otherwise .

5. A surgical scheduling system based on dual resource constraints, characterized in that: When the system is running, a surgical scheduling method based on dual resource constraints as described in any one of claims 1 to 4 is executed, wherein the system includes a data input module and a data processing module, a big data storage database and a scheduling system management terminal; The data input module is the front-end interface of the surgery scheduling system, which is used to input the data required for surgery scheduling, including basic patient information, doctor scheduling information, operating room resource information and surgery requirement information; The data processing module is connected to the data input module and is used to analyze and process the data required for surgery scheduling, integrate the surgery scheduling method based on dual resource constraints as described in any one of claims 1 to 4, and generate a surgery scheduling plan, and further includes a performance monitoring module, a parameter tuning module, and an error handling module; The big data storage database is connected to the data input module and the data processing module, and is used to store and manage all data generated by the surgery scheduling system, and has data retrieval, complex query and secure storage functions; The management terminal is connected to the data processing module and the big data storage database, and includes a user interface for viewing surgery arrangements, resource usage, statistical reports, and performing manual adjustments and management operations.

6. The surgical scheduling system based on dual resource constraints according to claim 5, characterized in that: The data input module supports multiple methods of inputting data, including keyboard entry method, code scanning input method, voice input method and electronic medical record system call method.

7. The surgical scheduling system based on dual resource constraints according to claim 5, characterized in that: The big data storage and processing database includes a data collection and preprocessing module, a data storage module, a data update and maintenance module, a data analysis module and a data encryption module.

8. The surgical scheduling system based on dual resource constraints according to claim 5, characterized in that: The management terminal includes a core function module and an auxiliary function module. The core function module includes a visual interface, surgical data entry, surgical progress tracking, resource information entry, resource allocation, interactive operation, authority management, scheduling plan calculation, dynamic adjustment function, scheduling notification, scheduling report generation, data analysis function, decision support function, system configuration function and update and maintenance function. The auxiliary function module includes a user management function, message notification function, historical notification record, data backup function, troubleshooting function, real-time resource monitoring and resource demand forecasting function.

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