Method, system, computer equipment and storage medium for automatic scheduling of hospital logistics

Abstract

The present invention discloses a method, system, computer equipment and storage medium for automatic scheduling of hospital logistics, and relates to the technical field of hospital logistics management. The present invention divides the scheduling tasks within a certain time period according to regions and working hours, combines the repair and alarm data of equipment in a certain area in a certain time period in previous years, quantifies the scheduling influencing factors, calculates the proportion of manpower, and thus calculates the optimal manpower in the working period of the area; according to the scheduling rules, a series of scheduling tables are randomly generated as the initial group, and a genetic algorithm is used for iteration. After a set number of iterations, the scheduling table with the highest fitness is obtained as the optimal scheduling table. The present invention introduces the repair and alarm data of the equipment as the scheduling influencing factors to calculate the proportion of manpower, optimizes the scheduling manpower from the perspective of the equipment, improves the work efficiency of the operation and maintenance personnel, enhances the ability to handle the high pressure of logistics operation and maintenance, and reduces the workload of the operation and maintenance personnel.

Description

Technical Field

[0001] The present invention relates to the technical field of hospital logistics management, in particular to the technical field of hospital logistics scheduling, and more specifically to a method, system, computer equipment and storage medium for automatic hospital logistics scheduling. Background Art

[0002] The operation and maintenance of mechanical and electrical equipment in hospital logistics is generally done through scheduling. The advantage of scheduling is that it can allocate manpower according to manpower needs and professional skills of personnel, which not only ensures the progress of operation and maintenance work, but also saves manpower costs. At present, the scheduling of the logistics department of the hospital is done manually by management personnel or scheduling specialists, which will bring the following problems:

[0003] 1. The scheduling results are greatly affected by human factors, especially the experience of the scheduler. A scheduler with little experience and who does not understand the skills and levels of each operation and maintenance personnel will cause a waste of human resources.

[0004] 2. As the number, professions, and types of work of operation and maintenance personnel increase, the difficulty and duration of scheduling will continue to increase.

[0005] 3. It is difficult to ensure fairness in artificially formulated schedules. Summary of the invention

[0006] In order to overcome the defects and shortcomings in the above-mentioned prior art, the present invention provides a method, system, computer equipment and storage medium for automatic scheduling of hospital logistics. The purpose of the present invention is to solve the problems in the above-mentioned prior art that the scheduling results are greatly affected by human factors, the scheduling is difficult and time-consuming, and it is difficult to ensure scheduling fairness. The automatic scheduling method for hospital logistics of the present invention divides the scheduling tasks within a certain time period according to regions and working hours to obtain a data matrix, in which each element of the data matrix represents the manpower of a certain area during a certain working hour; combined with the repair and alarm data of equipment in a certain area in a certain time period in previous years, the scheduling influencing factors are quantified, and the proportion of manpower in the working hour in the area is obtained in combination with the scheduling influencing factors, so as to calculate the optimal manpower in the working hour in the area; for any scheduling table, the actual manpower of the scheduling table in the working hour in the area is solved, and the actual manpower is compared with the optimal manpower to obtain the fitness of the scheduling table; according to the scheduling rules, a series of scheduling tables are randomly generated as the initial group, and a genetic algorithm is used for iteration, and each iteration is uniformly mutated; when the number of iterations reaches a threshold, the scheduling table with the highest fitness is obtained from the current group as the optimal scheduling table. The present invention introduces equipment repair and alarm data as scheduling influencing factors to calculate the proportion of manpower, and optimizes the scheduling manpower arrangement from the perspective of equipment. On the one hand, it can solve the problems that the scheduling results are greatly affected by human factors, the scheduling is difficult and time-consuming, and the scheduling is unfair. On the other hand, it can optimize the allocation of manpower, improve the work efficiency of operation and maintenance personnel, enhance the ability to handle the high pressure of logistics operation and maintenance, and reduce the workload of operation and maintenance personnel.

[0007] In order to solve the problems existing in the above-mentioned prior art, the present invention provides a method for automatic scheduling of hospital logistics, which comprises the following steps:

[0008] S1. Divide the shift tasks within the set time period according to regions and working hours;

[0009] S2. Obtain the historical repair and alarm data of the hospital logistics equipment, and analyze the equipment repair frequency, equipment maintenance difficulty and equipment alarm frequency in each working period in each area during the historical time period corresponding to the set time period, as well as the equipment aging degree and equipment use frequency in each area;

[0010] S3, using the equipment repair frequency, equipment maintenance difficulty, and equipment alarm frequency of each working period in each area in the historical time period corresponding to the set time period obtained in step S2, as well as the equipment aging degree and equipment use frequency of each area; as influencing factors, calculate the proportion of manpower required for each working period in each area in the set time period;

[0011] S4. According to the set scheduling rules and the number of people on duty, the total manpower ratio within the set time period is obtained. According to the total manpower ratio and the manpower proportion of each area and each working period calculated in step S3, the optimal manpower ratio of each area and each working period within the set time period is calculated;

[0012] S5. For any shift schedule, the degree of fit between its actual manpower ratio and the optimal manpower ratio is used as its fitness function; a series of shift schedules are randomly generated as the initial group according to the scheduling rules and the number of people on duty; a genetic algorithm is used for iteration; when the number of iterations reaches the set threshold, the schedule with the highest fitness is obtained from the current group, and the optimal schedule is generated from this schedule.

[0013] Furthermore, in step S1, the shift tasks within the set time period are divided according to regions and working periods, and a human resource allocation data matrix M*N is obtained, where M represents the number of regions and N represents the number of working periods; each element Z in the data matrix mn It represents the manpower ratio of area m in working period n.

[0014] Furthermore, in step S2, historical repair and alarm data of the hospital logistics equipment over the years are obtained, and the historical repair and alarm data of the hospital logistics equipment obtained each year are divided according to the set time period in step S1, and the historical repair and alarm data in the historical time period corresponding to the set time period in step S1 are divided according to region and working period; the equipment repair frequency, equipment maintenance difficulty and equipment alarm frequency in each working period in each region within the corresponding historical time period are obtained, as well as the equipment aging degree and equipment usage frequency in each region.

[0015] Furthermore, the equipment repair frequency a mn Indicates the ratio of the number of repair reports of equipment in area m during working period n to the total number of repair reports of equipment in the historical time period corresponding to the time period set in step S1;

[0016] The equipment maintenance difficulty b mn Indicates the ratio of the maintenance time of the equipment in area m in working period n to the total maintenance time of the equipment in the historical time period corresponding to the time period set in step S1;

[0017] The device alarm frequency c mn It indicates the ratio of the number of alarms of the equipment in area m in working period n to the total number of equipment alarms in the historical time period corresponding to the time period set in step S1.

[0018] Furthermore, the device aging degree d mIt represents the ratio of the service time of the equipment in area m to the life cycle time of the equipment in area m;

[0019] The device uses a frequency e m Indicates the ratio of the usage time of the devices in area m to the usage time of all devices.

[0020] Furthermore, in step S3, the manpower ratio of each area and each working period is

[0021] , where represents the proportion of manpower in area m during working period n; a mn b represents the frequency of equipment repair reports in working period n within area m; mn represents the difficulty of equipment maintenance in area m during working period n; c mn Indicates the frequency of equipment alarms in working period n within area m; d m Indicates the aging degree of the equipment in area m; e m Indicates the device usage frequency of devices in region m.

[0022] Furthermore, in step S4, the calculation formula for the optimal manpower ratio is as follows:

[0023] In the formula, It represents the optimal manpower ratio in area m during working period n; It represents the proportion of manpower in area m during working period n; Z represents the total manpower ratio.

[0024] Furthermore, in step S5, the fitness of each schedule in the initial group is obtained according to the fitness function, the schedules in the initial group are arranged from large to small according to the fitness, the first half of the arranged schedules are copied to the next generation group, and mutated at the same time with a set mutation probability to obtain the next generation group. After the number of iterations reaches the set threshold, the schedule with the highest fitness is obtained from the current group, and the optimal schedule is generated from this schedule.

[0025] The fitness function is

[0026] , It represents the optimal manpower ratio in area m during working period n; It represents the actual manpower ratio in area m during working period n calculated according to the current shift schedule; represents fitness, The higher the value of, the closer the current schedule is to the optimal solution.

[0027] The mutation probability is set to 0.05, and each iteration mutates uniformly.

[0028] The second aspect of the present invention provides a system for automatic scheduling of hospital logistics, the system comprising: a data extraction module, a data analysis module, an attendance management module, a scheduling management module and an automatic scheduling module;

[0029] The data extraction module is used to extract hospital space information, equipment information, historical equipment repair data and historical equipment alarm data from the database on an annual basis, and send the extracted data to the data analysis module for data analysis;

[0030] The data analysis module analyzes the hospital space information, equipment information, historical equipment repair data and historical equipment alarm data transmitted by the data extraction module, and obtains the equipment repair frequency, equipment maintenance difficulty and equipment alarm frequency of each working period in each area in the historical time period corresponding to the set time period, as well as the equipment aging degree and equipment use frequency of each area, and uses them as influencing factors to calculate the proportion of manpower required for each working period in each area in the set time period;

[0031] The attendance management module includes personnel management and personnel attendance performance management. The personnel management includes the management of attendance data and the approval process management of business trips and leave. The personnel attendance performance management performs performance statistics based on the personnel attendance data.

[0032] The shift management module is used to set shift rules and shift management;

[0033] The automatic scheduling module is used to divide the scheduling tasks within the set time period according to regions and working hours; the total manpower ratio within the set time period is calculated based on the number of on-duty personnel counted in the attendance management module and the scheduling rules in the scheduling management module, and the optimal manpower ratio for each area and each working time period within the set time period is calculated based on the total manpower ratio and the proportion of manpower required for each area and each working time period obtained by the data analysis module;

[0034] It is also used to use the degree of fit between the actual manpower ratio and the optimal manpower ratio as the fitness function of any shift schedule; randomly generate a series of shift schedules as the initial group according to the scheduling rules and the number of people on duty; use the genetic algorithm to iterate; when the number of iterations reaches the set threshold, obtain the schedule with the highest fitness from the current group, and output this schedule as the optimal schedule.

[0035] The data analysis module divides the historical repair and alarm data of hospital logistics equipment obtained each year according to set time periods, and divides the historical repair and alarm data in the historical time period corresponding to the set time period according to regions and working hours; obtains the equipment repair frequency, equipment maintenance difficulty and equipment alarm frequency in each working hour in each region within the corresponding historical time period, as well as the equipment aging degree and equipment usage frequency in each region.

[0036] Furthermore, the equipment repair frequency a mn Indicates the ratio of the number of repair reports of equipment in area m during working period n to the total number of repair reports of equipment in the historical time period corresponding to the time period set in step S1;

[0037] The equipment maintenance difficulty b mn Indicates the ratio of the maintenance time of the equipment in area m in working period n to the total maintenance time of the equipment in the historical time period corresponding to the time period set in step S1;

[0038] The device alarm frequency c mn It indicates the ratio of the number of alarms of the equipment in area m in working period n to the total number of equipment alarms in the historical time period corresponding to the time period set in step S1.

[0039] Furthermore, the device aging degree d m It represents the ratio of the service time of the equipment in area m to the life cycle time of the equipment in area m;

[0040] The device uses a frequency e m Indicates the ratio of the usage time of the devices in area m to the usage time of all devices.

[0041] Furthermore, the proportion of manpower in each area and each working period is

[0042] , where represents the proportion of manpower in area m during working period n; a mn b represents the frequency of equipment repair reports in working period n within area m; mn represents the difficulty of equipment maintenance in area m during working period n; c mn Indicates the frequency of equipment alarms in working period n within area m; d m Indicates the aging degree of the equipment in area m; e m Indicates the device usage frequency of devices in region m.

[0043] The formula for calculating the optimal manpower ratio is as follows:

[0044] In the formula, It represents the optimal manpower ratio in area m during working period n; It represents the proportion of manpower in area m during working period n; Z represents the total manpower ratio.

[0045] In the automatic scheduling module, the scheduling tasks within the set time period are divided according to regions and working hours to obtain a human resource allocation data matrix M*N, where M represents the number of regions and N represents the number of working hours; each element Z in the data matrix mn It represents the manpower ratio of area m in working period n.

[0046] Furthermore, the automatic scheduling module obtains the fitness of each schedule in the initial group according to the fitness function, arranges the schedules in the initial group from large to small according to the fitness, copies the first half of the arranged schedules to the next generation group, and mutates them with a set mutation probability to obtain the next generation group. After the number of iterations reaches the set threshold, the schedule with the highest fitness is obtained from the current group, and the optimal schedule is generated from this schedule.

[0047] The fitness function is

[0048] , It represents the optimal manpower ratio in area m during working period n; It represents the actual manpower ratio in area m during working period n calculated according to the current shift schedule; represents fitness, The higher the value of, the closer the current schedule is to the optimal solution.

[0049] The mutation probability is set to 0.05, and each iteration mutates uniformly.

[0050] The third aspect of the present invention provides a computer device, comprising a processor, an input device, an output device and a memory, wherein the processor, the input device, the output device and the memory are interconnected, wherein the memory is used to store a computer program, the computer program comprises program instructions, and the processor is configured to call the program instructions to execute some or all of the steps described in the first aspect of the present invention.

[0051] The fourth aspect of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program for electronic data exchange, wherein the computer program enables a computer to execute some or all of the steps described in the first aspect of the present invention.

[0052] Compared with the prior art, the beneficial technical effects brought by the present invention are as follows:

[0053] 1. The present invention introduces equipment repair and alarm data as scheduling influencing factors to calculate the proportion of manpower, and optimizes the scheduling manpower from the perspective of equipment. On the one hand, it can solve the problems that the scheduling results are greatly affected by human factors, the scheduling is difficult and time-consuming, and the scheduling is unfair. On the other hand, it can optimize the allocation of manpower, improve the work efficiency of operation and maintenance personnel, enhance the ability to handle the high pressure of logistics operation and maintenance, and reduce the workload of operation and maintenance personnel.

[0054] 2. The present invention automatically generates a shift schedule based on unified rules, thereby ensuring the fairness of the shift schedule, reducing the requirements for the experience of the schedulers, and alleviating the work pressure of the schedulers.

[0055] 3. The present invention predicts the manpower needs in different areas at different times based on previous equipment repair and alarm situations, and can reasonably arrange manpower to maximize the utilization of human resources, improve the work efficiency of operation and maintenance personnel, and enhance the ability to handle high pressure of logistics operation and maintenance. The present invention obtains the optimal solution through genetic algorithm, improves the work efficiency of operation and maintenance personnel, and effectively enhances the ability to handle high pressure of logistics operation and maintenance through non-uniform dynamically adjusted shift schedules, reducing the workload of operation and maintenance personnel.

[0056] 4. The hospital logistics automatic scheduling system proposed in the present invention extracts historical data from the database of the hospital logistics management system on an annual basis through a data extraction module, which is convenient for analyzing historical data on an annual basis. At the same time, the historical data of previous years are divided according to the set time period, so that the scheduling tasks of each set time period are all referenced by the corresponding historical time period data. The present invention does not use all historical data as a reference, but refers to the historical data of the corresponding time period. For example, if the time period is set to a month, the reference for automatic scheduling in December 2021 is the historical data of December last year (December 2020), or the historical repair data and alarm data of December each year from the beginning of the historical query record to the end of 2020; in this way, the accuracy of predicting manpower based on historical data can be ensured, and factors such as seasonality and time are taken into consideration. For example, in summer, there are more repair and alarm data for air conditioners, while in winter, there are fewer repair and alarm data for air conditioners, and more repair and alarm data for heating. Only by querying and predicting according to the corresponding historical time period can the accuracy and fairness of scheduling be effectively ensured.

[0057] 5. The scheduling management module of the present invention can adjust the scheduling rules according to actual conditions. The shift management can also manually modify the schedule generated by the automatic scheduling module. The manually modified schedule will be updated and optimized by the automatic scheduling module, and the schedule in the subsequent time period will be modified. It will be automatically modified in real time according to the adjusted personnel, which is convenient for the operation and maintenance personnel to adjust the shifts and vacations, and also convenient for the operation and maintenance personnel to adjust themselves.

[0058] 6. The automatic scheduling module of the present invention introduces the equipment repair and alarm data as scheduling influencing factors to calculate the proportion of manpower, and optimizes the scheduling manpower from the perspective of equipment. On the one hand, it can solve the problems that the scheduling results are greatly affected by human factors, the scheduling is difficult, the time is long, and the scheduling is unfair. On the other hand, it can optimize the allocation of manpower, improve the work efficiency of operation and maintenance personnel, enhance the ability to handle the high pressure of logistics operation and maintenance, and reduce the workload of operation and maintenance personnel. Based on unified rules, the scheduling table is automatically generated to ensure the fairness of the scheduling, reduce the requirements for the experience of the scheduling personnel, and reduce the work pressure of the scheduling personnel. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 A flow chart of the method for automatic scheduling of hospital logistics of the present invention;

[0060] Figure 2 This is a system framework diagram of the system for automatic scheduling of hospital logistics of the present invention. DETAILED DESCRIPTION

[0061] The technical solution of the present invention is further described in detail below in conjunction with specific embodiments. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0062] Example 1

[0063] As a preferred embodiment of the present invention, refer to the attached specification Figure 1 As shown, this embodiment discloses a method for automatic scheduling of hospital logistics, which includes the following steps:

[0064] S1. Divide the shift tasks within the set time period according to regions and working hours;

[0065] S2. Obtain the historical repair and alarm data of the hospital logistics equipment, and analyze the equipment repair frequency, equipment maintenance difficulty and equipment alarm frequency in each working period in each area during the historical time period corresponding to the set time period, as well as the equipment aging degree and equipment use frequency in each area;

[0066] S3, using the equipment repair frequency, equipment maintenance difficulty, and equipment alarm frequency of each working period in each area in the historical time period corresponding to the set time period obtained in step S2, as well as the equipment aging degree and equipment use frequency of each area; as influencing factors, calculate the proportion of manpower required for each working period in each area in the set time period;

[0067] S4. According to the set scheduling rules and the number of people on duty, the total manpower ratio within the set time period is obtained. According to the total manpower ratio and the manpower proportion of each area and each working period calculated in step S3, the optimal manpower ratio of each area and each working period within the set time period is calculated;

[0068] S5. For any shift schedule, the degree of fit between its actual manpower ratio and the optimal manpower ratio is used as its fitness function; a series of shift schedules are randomly generated as the initial group according to the scheduling rules and the number of people on duty; a genetic algorithm is used for iteration; when the number of iterations reaches the set threshold, the schedule with the highest fitness is obtained from the current group, and the optimal schedule is generated from this schedule.

[0069] As an implementation mode of this embodiment, the set time period refers to the scheduling time period required for a scheduling. For example, if a scheduling needs to schedule personnel within a month, the set time period is one month after the start of the current scheduling task; and the historical time period corresponding to the set time period refers to the division by year. The historical time period represents the time period in the previous year or the previous N years corresponding to the time period currently expected to be scheduled. For example, the set time period is one month, and the scheduling task for December needs to be processed, then the historical time period is December of each year.

[0070] As another implementation of this embodiment, the working period can be defined according to needs. It can be defined as one hour, or it can be set according to shift rules, such as three shifts, 23:00-7:00 the next day, 7:00-15:00, and 15:00-23:00; each working period is 8 hours.

[0071] As another implementation of this embodiment, the set scheduling rules refer to the hospital's customized scheduling rules, for example, the working hours per person per shift fluctuate between 7-10 hours, the total working hours per week are 40 hours, and the rest time between two shifts must not be less than 6 hours.

[0072] Example 2

[0073] As another preferred embodiment of the present invention, refer to the attached specification Figure 1 The present invention discloses a method for automatic scheduling of hospital logistics, which comprises the following steps:

[0074] S1. Divide the scheduled tasks within the set time period according to regions and working hours to obtain a human resource allocation data matrix M*N, where M represents the number of regions and N represents the number of working hours. Each element Z in the data matrix mn It represents the manpower ratio of area m in working period n;

[0075] S2. Obtain the historical repair and alarm data of the hospital logistics equipment over the years, divide the historical repair and alarm data of the hospital logistics equipment obtained each year according to the set time period in step S1, and divide the historical repair and alarm data in the historical time period corresponding to the set time period in step S1 according to regions and working hours; obtain the equipment repair frequency, equipment maintenance difficulty and equipment alarm frequency in each working hour in each region in the corresponding historical time period, as well as the equipment aging degree and equipment use frequency in each region;

[0076] S3, using the equipment repair frequency, equipment maintenance difficulty, and equipment alarm frequency of each working period in each area in the historical time period corresponding to the set time period obtained in step S2, as well as the equipment aging degree and equipment use frequency of each area; as influencing factors, calculate the proportion of manpower required for each working period in each area in the set time period;

[0077] S4. According to the set scheduling rules and the number of people on duty, the total manpower ratio within the set time period is obtained. According to the total manpower ratio and the manpower proportion of each area and each working period calculated in step S3, the optimal manpower ratio of each area and each working period within the set time period is calculated;

[0078] S5. For any shift schedule, the degree of fit between its actual manpower ratio and the optimal manpower ratio is used as its fitness function; a series of shift schedules are randomly generated as the initial group according to the shift scheduling rules and the number of people on duty; it is iterated using a genetic algorithm; the fitness of each shift schedule in the initial group is obtained according to the fitness function, and the shift schedules in the initial group are arranged from large to small according to fitness, and the first half of the shift schedules after arrangement are copied to the next generation group, and mutated at the same time with a set mutation probability, so as to obtain the next generation group. After the number of iterations reaches the set threshold, the shift schedule with the highest fitness is obtained from the current group, and the optimal shift schedule is generated from this shift schedule. The set mutation probability is 0.05, and each iteration mutates uniformly.

[0079] Example 3

[0080] As another preferred embodiment of the present invention, refer to the attached specification Figure 1 The present invention discloses a method for automatic scheduling of hospital logistics, which comprises the following steps:

[0081] S1. Divide the scheduled tasks within the set time period according to regions and working hours to obtain a human resource allocation data matrix M*N, where M represents the number of regions and N represents the number of working hours. Each element Z in the data matrix mn It represents the manpower ratio of area m in working period n.

[0082] As an implementation mode of this embodiment, the set time period refers to the scheduling time period required for a scheduling. For example, if a scheduling needs to schedule personnel within a month, the set time period is one month after the start of the current scheduling task; and the historical time period corresponding to the set time period refers to the division by year. The historical time period represents the time period in the previous year or the previous N years corresponding to the time period currently expected to be scheduled. For example, the set time period is one month, and the scheduling task for December needs to be processed, then the historical time period is December of each year.

[0083] As another implementation of this embodiment, the working period can be defined according to needs. It can be defined as one hour, or it can be set according to shift rules, such as three shifts, 23:00-7:00 the next day, 7:00-15:00, and 15:00-23:00; each working period is 8 hours.

[0084] S2. Obtain the historical repair and alarm data of the hospital logistics equipment over the years, divide the historical repair and alarm data of the hospital logistics equipment each year according to the set time period in step S1, and divide the historical repair and alarm data in the historical time period corresponding to the set time period in step S1 according to region and working period; obtain the equipment repair frequency, equipment maintenance difficulty and equipment alarm frequency in each region and each working period in the corresponding historical time period, as well as the equipment aging degree and equipment usage frequency in each region.

[0085] The equipment repair frequency a mn It indicates the ratio of the number of repair reports of the equipment in area m during working period n to the total number of repair reports of the equipment in the historical time period corresponding to the time period set in step S1.

[0086] The equipment maintenance difficulty b mn It represents the ratio of the maintenance time of the equipment in area m in working period n to the total maintenance time of the equipment in the historical time period corresponding to the time period set in step S1.

[0087] The device alarm frequency c mn It indicates the ratio of the number of alarms of the equipment in area m in working period n to the total number of equipment alarms in the historical time period corresponding to the time period set in step S1.

[0088] The equipment aging degree d m Indicates the ratio of the service time of the equipment in region m to the life cycle time of the equipment in region m.

[0089] The device uses a frequency e m Indicates the ratio of the usage time of the devices in area m to the usage time of all devices.

[0090] S3. Use the equipment repair frequency, equipment maintenance difficulty, and equipment alarm frequency in each working period in each area in the historical time period corresponding to the set time period obtained in step S2, as well as the equipment aging degree and equipment use frequency in each area; as influencing factors to calculate the proportion of manpower required in each working period in each area in the set time period.

[0091] The proportion of manpower in each area and each working period is

[0092] In the formula, represents the proportion of manpower in area m during working period n; a mn b represents the frequency of equipment repair reports in working period n within area m; mn represents the difficulty of equipment maintenance in area m during working period n; c mn Indicates the frequency of equipment alarms in working period n within area m; d m Indicates the aging degree of the equipment in area m; e m Indicates the device usage frequency of devices in region m.

[0093] S4. According to the set scheduling rules and the number of on-duty personnel, the total manpower ratio within the set time period is obtained. According to the total manpower ratio and the manpower proportion of each area and each working period calculated in step S3, the optimal manpower ratio of each area and each working period within the set time period is calculated.

[0094] As another implementation of this embodiment, the set scheduling rules refer to the hospital's customized scheduling rules, for example, the working hours per person per shift fluctuate between 7-10 hours, the total working hours per week are 40 hours, and the rest time between two shifts must not be less than 6 hours.

[0095] The formula for calculating the optimal manpower ratio is as follows:

[0096] , where It represents the optimal manpower ratio in area m during working period n; It represents the proportion of manpower in area m during working period n; Z represents the total manpower ratio.

[0097] S5. For any shift schedule, the degree of fit between its actual manpower ratio and the optimal manpower ratio is used as its fitness function; a series of shift schedules are randomly generated as the initial group according to the shift scheduling rules and the number of people on duty; it is iterated using a genetic algorithm; the fitness of each shift schedule in the initial group is obtained according to the fitness function, and the shift schedules in the initial group are arranged from large to small according to fitness, and the first half of the shift schedules after arrangement are copied to the next generation group, and mutated at the same time with a set mutation probability, so as to obtain the next generation group. After the number of iterations reaches the set threshold, the shift schedule with the highest fitness is obtained from the current group, and the optimal shift schedule is generated from this shift schedule. The set mutation probability is 0.05, and each iteration mutates uniformly.

[0098] The fitness function is

[0099] , where It represents the optimal manpower ratio in area m during working period n; It represents the actual manpower ratio in area m during working period n calculated according to the current shift schedule; represents fitness, The higher the value of, the closer the current schedule is to the optimal solution.

[0100] As another implementation method of this embodiment, according to the scheduling rules and the number of people on duty, 1000 schedules that meet the scheduling rules are randomly generated, and for each schedule, its fitness X can be obtained. In each iteration, the first 500 schedules are sorted from high to low according to the fitness, and the different schedules are cross-inherited and mutated to generate new schedules, from which the schedules that meet the scheduling rules are selected as the subset P(t+1). A threshold T is set, and when t=T, the iteration ends. The schedule with the highest X value in the current subset P(T+1) is used as the optimal solution for the scheduling of the month.

[0101] Example 4

[0102] As another preferred embodiment of the present invention, refer to the attached specification Figure 2 As shown, this embodiment discloses a system for automatic scheduling of hospital logistics, which includes: a data extraction module, a data analysis module, an attendance management module, a scheduling management module and an automatic scheduling module;

[0103] The data extraction module is used to extract hospital space information, equipment information, historical equipment repair data and historical equipment alarm data from the database on an annual basis, and send the extracted data to the data analysis module for data analysis;

[0104] The data analysis module analyzes the hospital space information, equipment information, historical equipment repair data and historical equipment alarm data transmitted by the data extraction module, and obtains the equipment repair frequency, equipment maintenance difficulty and equipment alarm frequency of each working period in each area in the historical time period corresponding to the set time period, as well as the equipment aging degree and equipment use frequency of each area, and uses them as influencing factors to calculate the proportion of manpower required for each working period in each area in the set time period;

[0105] The attendance management module includes personnel management and personnel attendance performance management. The personnel management includes the management of attendance data and the approval process management of business trips and leave. The personnel attendance performance management performs performance statistics based on the personnel attendance data.

[0106] The shift management module is used to set shift rules and shift management;

[0107] The automatic scheduling module is used to divide the scheduling tasks within the set time period according to regions and working hours; the total manpower ratio within the set time period is calculated based on the number of on-duty personnel counted in the attendance management module and the scheduling rules in the scheduling management module, and the optimal manpower ratio for each area and each working time period within the set time period is calculated based on the total manpower ratio and the proportion of manpower required for each area and each working time period obtained by the data analysis module;

[0108] It is also used to use the degree of fit between the actual manpower ratio and the optimal manpower ratio as the fitness function of any shift schedule; randomly generate a series of shift schedules as the initial group according to the scheduling rules and the number of people on duty; use the genetic algorithm to iterate; when the number of iterations reaches the set threshold, obtain the schedule with the highest fitness from the current group, and output this schedule as the optimal schedule.

[0109] As an implementation of this embodiment, the set time period refers to the scheduling time period required for one shift scheduling. For example, if one shift scheduling needs to schedule personnel within one month, the set time period is one month after the current scheduling task starts; and the historical time period corresponding to the set time period refers to the division by year. The historical time period indicates the time period in the previous year or the previous N years corresponding to the time period currently expected to be scheduled. For example, if the set time period is one month and the scheduling task for December needs to be processed, the historical time period is December of the previous year.

[0110] As another implementation of this embodiment, the working period can be defined according to the needs, and can be defined as one hour, or can be set according to the shift rules, such as three shifts, 23:00-7:00 the next day, 7:00-15:00, 15:00-23:00; each working period is 8 hours;

[0111] As another implementation of this embodiment, the set scheduling rules refer to the hospital's customized scheduling rules, for example, the working hours per person per shift fluctuate between 7-10 hours, the total working hours per week are 40 hours, and the rest time between two shifts must not be less than 6 hours.

[0112] Example 5

[0113] As another preferred embodiment of the present invention, refer to the attached specification Figure 2 As shown, this embodiment discloses a system for automatic scheduling of hospital logistics, which includes: a data extraction module, a data analysis module, an attendance management module, a scheduling management module and an automatic scheduling module.

[0114] The data extraction module is used to extract hospital space information, equipment information, historical equipment repair data and historical equipment alarm data from the database on an annual basis, and send the extracted data to the data analysis module for data analysis.

[0115] The data analysis module analyzes the hospital space information, equipment information, equipment historical repair data and equipment historical alarm data transmitted by the data extraction module.

[0116] The data analysis module divides the historical repair and alarm data of hospital logistics equipment obtained each year according to the set time period, and divides the historical repair and alarm data in the historical time period corresponding to the set time period according to region and working period; obtains the equipment repair frequency, equipment maintenance difficulty and equipment alarm frequency in each working period in each region within the corresponding historical time period, as well as the equipment aging degree and equipment usage frequency in each region.

[0117] The equipment repair frequency a mn Indicates the ratio of the number of repair reports of equipment in area m during working period n to the total number of repair reports of equipment in the historical time period corresponding to the time period set in step S1;

[0118] The equipment maintenance difficulty b mn Indicates the ratio of the maintenance time of the equipment in area m in working period n to the total maintenance time of the equipment in the historical time period corresponding to the time period set in step S1;

[0119] The device alarm frequency c mn Indicates the ratio of the number of alarms of the equipment in area m in working period n to the total number of equipment alarms in the historical time period corresponding to the time period set in step S1;

[0120] The equipment aging degree d m It represents the ratio of the service time of the equipment in area m to the life cycle time of the equipment in area m;

[0121] The device uses a frequency e m Indicates the ratio of the usage time of the devices in area m to the usage time of all devices.

[0122] The proportion of manpower in each area and each working period is

[0123] In the formula, represents the proportion of manpower in area m during working period n; a mn b represents the frequency of equipment repair reports in working period n within area m; mn represents the difficulty of equipment maintenance in area m during working period n; c mn Indicates the frequency of equipment alarms in working period n within area m; d m Indicates the aging degree of the equipment in area m; e m Indicates the device usage frequency of devices in region m.

[0124] The attendance management module includes personnel management and personnel attendance performance management. The personnel management includes the management of attendance data and the approval process management of business trips and leave. The personnel attendance performance management performs performance statistics based on the personnel attendance data.

[0125] The shift management module is used to set shift rules and shift management.

[0126] The automatic scheduling module divides the scheduling tasks within the set time period according to the regions and working hours to obtain a human resource allocation data matrix M*N, where M represents the number of regions and N represents the number of working hours; each element Z in the data matrix mn It represents the manpower ratio of area m in working period n.

[0127] The automatic scheduling module calculates the total manpower ratio within the set time period based on the number of people on duty counted in the attendance management module and the scheduling rules in the scheduling management module. The optimal manpower ratio for each area and each working period within the set time period is calculated based on the total manpower ratio and the proportion of manpower required for each area and each working period obtained by the data analysis module;

[0128] The formula for calculating the optimal manpower ratio is as follows:

[0129] , where It represents the optimal manpower ratio in area m during working period n; It represents the proportion of manpower in area m during working period n; Z represents the total manpower ratio.

[0130] It is also used to use the degree of fit between the actual manpower ratio and the optimal manpower ratio as the fitness function of any shift schedule; randomly generate a series of shift schedules as the initial group according to the scheduling rules and the number of people on duty; use the genetic algorithm to iterate; when the number of iterations reaches the set threshold, obtain the schedule with the highest fitness from the current group, and output this schedule as the optimal schedule.

[0131] Furthermore, the automatic scheduling module obtains the fitness of each schedule in the initial group according to the fitness function, arranges the schedules in the initial group from large to small according to the fitness, copies the first half of the arranged schedules to the next generation group, and mutates them with a set mutation probability to obtain the next generation group. After the number of iterations reaches the set threshold, the schedule with the highest fitness is obtained from the current group, and the optimal schedule is generated from this schedule.

[0132] The fitness function is

[0133] , where It represents the optimal manpower ratio in area m during working period n; It represents the actual manpower ratio in area m during working period n calculated according to the current shift schedule; represents fitness, The higher the value of, the closer the current schedule is to the optimal solution.

[0134] The mutation probability is set to 0.05, and each iteration mutates uniformly.

[0135] Example 6

[0136] In order to achieve the above-mentioned purpose, according to another aspect of the present application, a computer device is also provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the steps of the above-mentioned method for automatic scheduling of hospital logistics when executing the computer program.

[0137] In this embodiment, the processor may be a central processing unit (CPU). The processor may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or a combination of the above chips.

[0138] The memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs, non-transitory computer executable programs and units, such as the corresponding program units in the above method embodiments of the present invention. The processor executes various functional applications of the processor and works data processing by running the non-transitory software programs, instructions and modules stored in the memory, that is, implementing the method in the above method embodiments.

[0139] The memory may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created by the processor, etc. In addition, the memory may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some embodiments, the memory may optionally include a memory remotely arranged relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0140] The one or more units are stored in the memory, and when executed by the processor, the method in the above-mentioned embodiment 1, embodiment 2 or embodiment 3 is executed.

[0141] Example 7

[0142] As another preferred embodiment of the present invention, this embodiment discloses a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned embodiment 1, embodiment 2 or embodiment 3 are implemented.

Claims

1. A method for automatic scheduling of hospital logistics, characterized in that: The method comprises the following steps: S1. Divide the scheduled tasks within the set time period according to regions and working hours to obtain a human resource allocation data matrix M*N, where M represents the number of regions and N represents the number of working hours. Each element Z in the data matrix mn It represents the manpower ratio of area m in working period n; S2. Obtain the historical repair and alarm data of the hospital logistics equipment, and analyze the equipment repair frequency, equipment maintenance difficulty and equipment alarm frequency in each working period in each area during the historical time period corresponding to the set time period, as well as the equipment aging degree and equipment use frequency in each area; S3. The equipment repair frequency, equipment maintenance difficulty, and equipment alarm frequency of each working period in each area in the historical time period corresponding to the set time period obtained in step S2, as well as the equipment aging degree and equipment use frequency of each area, are used as influencing factors to calculate the proportion of manpower required for each working period in each area in the set time period; the proportion of manpower required for each working period in each area is , where represents the proportion of manpower in area m during working period n; a mn b represents the frequency of equipment repair reports in working period n within area m; mn represents the difficulty of equipment maintenance in area m during working period n; c mn Indicates the frequency of equipment alarms in working period n within area m; d m Indicates the aging degree of the equipment in area m; e m Indicates the device usage frequency of devices in region m; S4. According to the set scheduling rules and the number of people on duty, the total manpower ratio within the set time period is obtained. According to the total manpower ratio and the manpower proportion of each area and each working period calculated in step S3, the optimal manpower ratio of each area and each working period within the set time period is calculated; the calculation formula for the optimal manpower ratio is as follows: , where It represents the optimal manpower ratio in area m during working period n; It represents the proportion of manpower in area m during working period n; Z represents the total manpower ratio; S5. For any shift schedule, the degree of fit between its actual manpower ratio and the optimal manpower ratio is used as its fitness function; a series of shift schedules are randomly generated as the initial group according to the scheduling rules and the number of people on duty; a genetic algorithm is used for iteration; when the number of iterations reaches the set threshold, the schedule with the highest fitness is obtained from the current group, and the optimal schedule is generated from this schedule.

2. The method for automatic scheduling of hospital logistics as claimed in claim 1, characterized in that: In step S2, historical repair and alarm data of the hospital logistics equipment over the years are obtained, and the historical repair and alarm data of the hospital logistics equipment obtained each year are divided according to the set time period in step S1, and the historical repair and alarm data in the historical time period corresponding to the set time period in step S1 are divided according to region and working period; the equipment repair frequency, equipment maintenance difficulty and equipment alarm frequency in each working period in each region within the corresponding historical time period, as well as the equipment aging degree and equipment usage frequency in each region are obtained.

3. The method for automatic scheduling of hospital logistics as claimed in claim 1, characterized in that: The equipment repair frequency a mn Indicates the ratio of the number of repair reports of equipment in area m during working period n to the total number of repair reports of equipment in the historical time period corresponding to the time period set in step S1; The equipment maintenance difficulty b mn Indicates the ratio of the maintenance time of the equipment in area m in working period n to the total maintenance time of the equipment in the historical time period corresponding to the time period set in step S1; The device alarm frequency c mn It indicates the ratio of the number of alarms of the equipment in area m in working period n to the total number of equipment alarms in the historical time period corresponding to the time period set in step S1.

4. The method for automatic scheduling of hospital logistics as claimed in claim 3, characterized in that: The equipment aging degree d m It represents the ratio of the service time of the equipment in area m to the life cycle time of the equipment in area m; The device uses a frequency e m Indicates the ratio of the usage time of the devices in area m to the usage time of all devices.

5. The method for automatic scheduling of hospital logistics as claimed in claim 1 or 4, characterized in that: In step S5, the fitness of each schedule in the initial group is obtained according to the fitness function, and the schedules in the initial group are arranged from large to small according to the fitness. The first half of the arranged schedules are copied to the next generation group, and mutated at the same time with a set mutation probability to obtain the next generation group. After the number of iterations reaches the set threshold, the schedule with the highest fitness is obtained from the current group, and the optimal schedule is generated from this schedule.

6. The method for automatic scheduling of hospital logistics as claimed in claim 5, characterized in that: The fitness function is , where It represents the optimal manpower ratio in area m during working period n; It represents the actual manpower ratio in the area m during the working period n calculated according to the current shift schedule. X represents the fitness. The higher the value of X, the closer the current shift schedule is to the optimal solution.

7. The method for automatic scheduling of hospital logistics as claimed in claim 5, characterized in that: The mutation probability is set to 0.05, and each iteration mutates uniformly.

8. The system for automatic scheduling of hospital logistics is characterized by: The system includes: data extraction module, data analysis module, attendance management module, shift management module and automatic shift scheduling module; The data extraction module is used to extract hospital space information, equipment information, historical equipment repair data and historical equipment alarm data from the database on an annual basis, and send the extracted data to the data analysis module for data analysis; The data analysis module analyzes the hospital space information, equipment information, historical equipment repair data and historical equipment alarm data transmitted by the data extraction module, and obtains the equipment repair frequency, equipment maintenance difficulty and equipment alarm frequency of each working period in each area in the historical time period corresponding to the set time period, as well as the equipment aging degree and equipment use frequency of each area, and uses them as influencing factors to calculate the proportion of manpower required for each working period in each area in the set time period; the proportion of manpower required for each working period in each area is , where represents the proportion of manpower in area m during working period n; a mn b represents the frequency of equipment repair reports in working period n within area m; mn represents the difficulty of equipment maintenance in area m during working period n; c mn Indicates the frequency of equipment alarms in working period n within area m; d m Indicates the aging degree of the equipment in area m; e m Indicates the device usage frequency of devices in region m; The attendance management module includes personnel management and personnel attendance performance management. The personnel management includes the management of attendance data and the approval process management of business trips and leave. The personnel attendance performance management performs performance statistics based on the personnel attendance data. The shift management module is used to set shift rules and shift management; The automatic scheduling module is used to divide the scheduling tasks within the set time period according to regions and working hours, and obtain a human resource allocation data matrix M*N, where M represents the number of regions and N represents the number of working hours; each element Z in the data matrix mn It represents the manpower ratio of area m in working period n; according to the number of people on duty counted in the attendance management module and the scheduling rules in the scheduling management module, the total manpower ratio in the set time period is calculated, and the optimal manpower ratio of each area and each working period in the set time period is calculated according to the total manpower ratio and the proportion of manpower required for each area and each working period obtained by the data analysis module; the calculation formula of the optimal manpower ratio is as follows: , where It represents the optimal manpower ratio in area m during working period n; It represents the proportion of manpower in area m during working period n; Z represents the total manpower ratio; The automatic scheduling module is also used to use the degree of fit between the actual manpower ratio and the optimal manpower ratio as the fitness function for any shift schedule; The automatic scheduling module randomly generates a series of schedules as the initial group according to the scheduling rules and the number of people on duty; iterates using a genetic algorithm; after the number of iterations reaches a set threshold, the schedule with the highest fitness is obtained from the current group, and the output of this schedule is used as the optimal schedule.

9. The system for automatic scheduling of hospital logistics as claimed in claim 8, characterized in that: The data analysis module divides the historical repair and alarm data of hospital logistics equipment obtained each year according to set time periods, and divides the historical repair and alarm data in the historical time period corresponding to the set time period according to regions and working hours; obtains the equipment repair frequency, equipment maintenance difficulty and equipment alarm frequency in each working hour in each region within the corresponding historical time period, as well as the equipment aging degree and equipment usage frequency in each region.

10. The system for automatic scheduling of hospital logistics as claimed in claim 8 or 9, characterized in that: The equipment repair frequency a mn Indicates the ratio of the number of repair reports of equipment in area m during working period n to the total number of repair reports of equipment in the historical time period corresponding to the time period set in step S1; The equipment maintenance difficulty b mn Indicates the ratio of the maintenance time of the equipment in area m in working period n to the total maintenance time of the equipment in the historical time period corresponding to the time period set in step S1; The device alarm frequency c mn It indicates the ratio of the number of alarms of the equipment in area m in working period n to the total number of equipment alarms in the historical time period corresponding to the time period set in step S1.

11. The system for automatic scheduling of hospital logistics as claimed in claim 10, characterized in that: The equipment aging degree d m It represents the ratio of the service time of the equipment in area m to the life cycle time of the equipment in area m; The device uses a frequency e m Indicates the ratio of the usage time of the devices in area m to the usage time of all devices.

12. The system for automatic scheduling of hospital logistics as claimed in claim 8 or 9, characterized in that: The automatic scheduling module obtains the fitness of each schedule in the initial group according to the fitness function, arranges the schedules in the initial group from large to small according to the fitness, copies the first half of the arranged schedules to the next generation group, and mutates them with a set mutation probability to obtain the next generation group. After the number of iterations reaches the set threshold, the schedule with the highest fitness is obtained from the current group, and the optimal schedule is generated from this schedule.

13. The system for automatic scheduling of hospital logistics as claimed in claim 12, characterized in that: The fitness function is , where It represents the optimal manpower ratio in area m during working period n; It represents the actual manpower ratio in the area m during the working period n calculated according to the current shift schedule. X represents the fitness. The higher the value of X, the closer the current shift schedule is to the optimal solution.

14. A computer device, characterized in that: The method comprises a processor, an input device, an output device and a memory, wherein the processor, the input device, the output device and the memory are interconnected, wherein the memory is used to store a computer program, the computer program comprises program instructions, and the processor is configured to call the program instructions to execute the method according to any one of claims 1 to 7.

15. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, wherein the computer program includes program instructions, and when the program instructions are executed by a processor, the processor executes the method according to any one of claims 1 to 7.

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