CN113555096A - Operating room scheduling method and system considering doctor scheduling condition - Google Patents
Operating room scheduling method and system considering doctor scheduling condition Download PDFInfo
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Abstract
The invention provides an operating room scheduling method and system considering doctor scheduling conditions, and relates to the technical field of operating room scheduling. The invention solves the problem of combining the scheduling of doctors and the scheduling of operating rooms in surgical departments in large hospitals, not only reasonably allocates the operating dates and the operating rooms for patients, but also reasonably allocates the working contents of the doctors to the operating rooms or outpatients by considering the condition that the surgeons need to execute various tasks, simultaneously meets the requirements of the operations of the patients and the requirements of the outpatients department for seeing the doctor, improves the utilization rate of the doctors and the operating rooms, and also improves the satisfaction degree of the patients. According to the method, patients needing operations every day are distributed to an operating room to be regarded as 0-1 packing problems, solutions of the problems are quickly obtained through dynamic programming, then the solutions are further optimized through heuristic rules, approximate optimal solutions of the operation distribution problems are obtained, and finally a variable neighborhood search algorithm obtains a global better solution through maximizing iteration times and searching different neighborhood structures.
Description
Technical Field
The invention relates to the technical field of operating room scheduling, in particular to an operating room scheduling method and system considering doctor scheduling conditions.
Background
High operating costs are one of the main problems that plague hospital administration. Operating room scheduling is a major concern for hospitals because 40% of hospital expenses and incomes originate from the operating room. Therefore, it is necessary for hospital administrators to schedule multiple resources within a department room to reduce the cost of medical resources, such as doctors, operating rooms, etc.
In the conventional operating room scheduling model, the procedure of determining the operation date for the patient and deciding the operating room and the operation start time at a specific operation date is mainly used. In the past, operating room scheduling has primarily considered factors of the patient and operating room, such as patient characteristics, whether scheduled or unscheduled, whether the operating room is multi-functional or single-functional, and so forth. In recent years, however, there has been much literature on considering the impact of surgeon factors, such as surgeon preference, time available, and weekend holidays, on operating room scheduling.
However, in the real hospital situation, for the surgeons, they need to perform the operation for the patient to meet the operation requirement of the patient, and also need to sit at the outpatient department to meet the requirement of the sitting department, and through the survey of the literature, the problem that the researchers consider the scheduling of the doctor outpatient office while considering the scheduling of the operating room in the surgical department is not found.
Disclosure of Invention
Technical problem to be solved
Aiming at the defects of the prior art, the invention provides an operating room scheduling method and system considering doctor scheduling conditions, and solves the problem that the existing scheme does not perform operating room scheduling while doctor outpatient scheduling is considered.
(II) technical scheme
In order to achieve the purpose, the invention is realized by the following technical scheme:
in a first aspect, an operating room scheduling method considering doctor scheduling conditions is provided, the method comprising:
s1, acquiring the number I of patients, the operation duration of each patient, the number P of doctors, the number R of operating rooms and the fixed opening of the operating roomsDischarge time TregMaximum allowable overtime time ToverAnd a planning period D;
setting algorithm parameters including maximum iteration number itermaxThe initial iteration number iter is 1;
s2, randomly generating an initial solution, wherein the initial solution comprises two parts, namely the operation date of the patient and the number of doctors required by each shift of the clinic department;
s3, acquiring the number of patients needing operations each day in the current solution; performing operating room allocation based on the number of the patients needing operation every day, the longest working time of the operating room and the operation duration of each patient to obtain an operating room allocation result every day;
s4, generating a daily outpatient shift scheduling result based on the daily operating room distribution result;
s5, calculating the fitness value based on the daily doctor outpatient shift scheduling result and the daily operating room distribution result to obtain the fitness values of the current solution x and x;
the fitness value is the sum of the overtime cost of an operating room, the fixed open cost of the operating room, the hospitalization cost of a patient, the operation cost of a doctor and the sitting and examining cost of the doctor;
s6, judging whether the maximum iteration number is reached, and if the iteration number does not reach the maximum iteration number, executing S7-S10; otherwise, go to S11;
s7, obtaining a solution x' through shaking;
s8, executing S3-S4;
s9, updating the solution x 'through the VND to obtain a solution x ", and calculating the fitness value of x';
s10, comparing the fitness values of x and x', updating the current solution and the iteration times, and returning to S6;
and S11, taking the current solution as an operating room scheduling scheme, and outputting the current solution together with the daily scheduling result.
Further, S3, acquiring the number of patients needing surgery per day in the current solution; and performing operating room allocation based on the number of patients needing operation each day, the longest working time of the operating room and the operation duration of each patient to obtain the daily operating room allocation result, wherein the daily operating room allocation result comprises the following steps:
operating room allocation is carried out by utilizing a dynamic planning algorithm to obtain daily operating room allocation results;
the number of patients corresponds to the number of articles of the dynamic planning algorithm, the maximum working time of the operating room corresponds to the maximum capacity of the box of the dynamic planning algorithm, and the aim is to minimize the idle time of the operating room.
Further, after the operation room allocation is performed by using the dynamic planning algorithm to obtain the daily operation room allocation result, the method further includes:
optimizing the number of open operating rooms based on heuristic rules;
the heuristic rules include:
k1, obtaining the number of the operating rooms opened and the number of the unopened operating rooms on the basis of the daily operating room distribution result b _ 1;
k2, judging whether an unopened operating room exists or not and whether an operating room is overtime or not;
if all the operating rooms are opened or no operating room is overtime, outputting a daily operating room distribution result b _ 1;
if an operating room is not opened and the operating room has overtime, acquiring the operating room cost c _1 of the current operating room distribution result, then opening a new operating room, starting from the first operating room in the operating room in which the patients are arranged, judging whether the overtime exists, if so, randomly selecting the patients from the operating rooms to be placed into the newly opened operating room, stopping selecting the patients from the operating room to be placed into the newly opened operating room until the overtime does not exist in the operating room, then judging whether the next operating room has overtime exists, and repeating the steps until the newly opened operating room does not contain any next patient;
k3, updating to obtain a daily operating room distribution result b _2, and calculating the corresponding operating room cost c _ 2;
k4, comparing the sizes of c _1 and c _2, if c _2 is smaller, continuing to open a new operating room, repeating the step K2, otherwise outputting the shift table b _ 1.
Further, the generating daily outpatient shift results based on the daily operating room assignment results includes:
obtaining a patient performing a daily operation based on the daily operating room assignment;
acquiring a daily operating doctor based on the daily operating patient;
according to the number of doctors required by each shift of the clinic department, doctors who do not perform operations every day are distributed to obtain the daily outpatient shift scheduling result;
and the generation method of the daily outpatient shift scheduling result comprises the following steps:
t1, assume that doctor who can sit on d day generates a set pdLet d be 1;
t2 calculation set pdThe rest sitting diagnosis times and continuous working days of each doctor;
t3, starting from the k shifts on d days, arranging the doctors with the most residual sitting times and continuous work which does not exceed S days in the k shifts on d days, and making k equal to 1;
t4, update set pdRepeating the step 3, and continuing to the step T5 until the doctor requirement of the kth shift is met;
t5, k equals k +1, and the process returns to step T3;
t6, d ═ d +1, return to step T1.
In a second aspect, there is provided an operating room scheduling system considering doctor's scheduling, the system comprising:
a data acquisition module for acquiring the number of patients I, the operation duration of each patient, the number of doctors P, the number of operating rooms R and the fixed open time T of the operating roomsregMaximum allowable overtime time ToverAnd a planning period D; setting algorithm parameters including maximum iteration number itermaxThe initial iteration number iter is 1;
the initial solution generation module is used for randomly generating an initial solution, and the initial solution comprises two parts which respectively represent the operation date of the patient and the number of doctors required by each shift of the clinic;
the daily operating room distribution result generation module is used for acquiring the number of patients needing operations daily in the current solution; performing operating room allocation based on the number of the patients needing operation every day, the longest working time of the operating room and the operation duration of each patient to obtain an operating room allocation result every day;
the daily outpatient shift result generation module is used for generating a daily outpatient shift result based on the daily operating room distribution result;
an optimal solution iteration module for executing the methods from S5 to S11:
s5, calculating the fitness value based on the daily doctor outpatient shift scheduling result and the daily operating room distribution result to obtain the fitness values of the current solution x and x;
the fitness value is the sum of the overtime cost of an operating room, the fixed open cost of the operating room, the hospitalization cost of a patient, the operation cost of a doctor and the sitting and examining cost of the doctor;
s6, judging whether the maximum iteration number is reached, and if the iteration number does not reach the maximum iteration number, executing S7-S10; otherwise, go to S11;
s7, obtaining a solution x' through shaking;
s8, acquiring a daily operating room distribution result and a daily outpatient shift scheduling result of the solution x';
s9, updating the solution x 'through the VND to obtain a solution x ", and calculating the fitness value of x';
s10, comparing the fitness values of x and x', updating the current solution and the iteration times, and returning to S6;
and S11, taking the current solution as an operating room scheduling scheme, and outputting the current solution together with the daily scheduling result.
Further, acquiring the number of patients needing operation each day in the current solution; and performing operating room allocation based on the number of patients needing operation each day, the longest working time of the operating room and the operation duration of each patient to obtain the daily operating room allocation result, wherein the daily operating room allocation result comprises the following steps:
operating room allocation is carried out by utilizing a dynamic planning algorithm to obtain daily operating room allocation results;
the number of patients corresponds to the number of articles of the dynamic planning algorithm, the maximum working time of the operating room corresponds to the maximum capacity of the box of the dynamic planning algorithm, and the aim is to minimize the idle time of the operating room.
Further, after the operation room allocation is performed by using the dynamic planning algorithm to obtain the daily operation room allocation result, the method further includes:
optimizing the number of open operating rooms based on heuristic rules;
the heuristic rules include:
k1, obtaining the number of the operating rooms opened and the number of the unopened operating rooms on the basis of the daily operating room distribution result b _ 1;
k2, judging whether an unopened operating room exists or not and whether an operating room is overtime or not;
if all the operating rooms are opened or no operating room is overtime, outputting a daily operating room distribution result b _ 1;
if an operating room is not opened and the operating room has overtime, acquiring the operating room cost c _1 of the current operating room distribution result, then opening a new operating room, starting from the first operating room in the operating room in which the patients are arranged, judging whether the overtime exists, if so, randomly selecting the patients from the operating rooms to be placed into the newly opened operating room, stopping selecting the patients from the operating room to be placed into the newly opened operating room until the overtime does not exist in the operating room, then judging whether the next operating room has overtime exists, and repeating the steps until the newly opened operating room does not contain any next patient;
k3, updating to obtain a daily operating room distribution result b _2, and calculating the corresponding operating room cost c _ 2;
k4, comparing the sizes of c _1 and c _2, if c _2 is smaller, continuing to open a new operating room, repeating the step K2, otherwise outputting the shift table b _ 1.
Further, the generating daily outpatient shift results based on the daily operating room assignment results includes:
obtaining a patient performing a daily operation based on the daily operating room assignment;
acquiring a daily operating doctor based on the daily operating patient;
according to the number of doctors required by each shift of the clinic department, doctors who do not perform operations every day are distributed to obtain the daily outpatient shift scheduling result;
and the generation method of the daily outpatient shift scheduling result comprises the following steps:
t1, assume that doctor who can sit on d day generates a set pdLet d be 1;
t2 calculation set pdThe rest sitting diagnosis times and continuous working days of each doctor;
t3, starting from the k shifts on d days, arranging the doctors with the most residual sitting times and continuous work which does not exceed S days in the k shifts on d days, and making k equal to 1;
t4, update set pdRepeating the step 3, and continuing to the step T5 until the doctor requirement of the kth shift is met;
t5, k equals k +1, and the process returns to step T3;
t6, d ═ d +1, return to step T1.
(III) advantageous effects
The invention provides an operating room scheduling method and system considering doctor scheduling conditions.
Compared with the prior art, the method has the following beneficial effects:
1. the invention solves the problem of combining the scheduling of doctors and the scheduling of operating rooms in surgical departments in large hospitals, not only reasonably allocates the operating dates and the operating rooms for patients, but also reasonably allocates the working contents of the doctors to the operating rooms or outpatients by considering the condition that the surgeons need to execute various tasks, simultaneously meets the requirements of the operations of the patients and the requirements of the outpatients department for seeing the doctor, improves the utilization rate of the doctors and the operating rooms, and also improves the satisfaction degree of the patients.
2. The invention simultaneously considers three factors of a doctor, a patient and an operating room, and considers the hospitalization time of the patient, the maximum overtime time and the fixed open time of the operating room, the continuous working time of the doctor, the doctor sitting at most several times in the outpatient clinic each day, the maximum working time of the doctor each day, the maximum working time of the planning period and the like. The invention integrates various constraints and factors which need to be considered in the actual hospital, aims to reduce the cost of the hospital and the waiting cost of the patient, balances the relationship among a doctor, an operating room and the patient and provides a more effective method for hospital management.
3. According to the method, patients needing operations every day are distributed to an operating room to be regarded as 0-1 packing problems, solutions of the problems are quickly obtained through dynamic programming, then the solutions are further optimized through heuristic rules, approximate optimal solutions of the operation distribution problems are obtained, and finally a variable neighborhood search algorithm obtains a global better solution through maximizing iteration times and searching different neighborhood structures.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a flow chart of an embodiment of the present invention;
FIG. 2 is a diagram illustrating the results of a control experiment according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention are clearly and completely described, and it is obvious that the described embodiments are a part of the embodiments of the present invention, but not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The embodiment of the application provides the operating room scheduling method and system considering the scheduling condition of doctors, and solves the problem that the existing scheme does not perform operating room scheduling while considering doctor outpatient scheduling.
In order to solve the technical problems, the general idea of the embodiment of the application is as follows:
the problem of doctor's scheduling and the scheduling of operating room combine together is solved, this problem mainly divide into three parts, the distribution of operating room plan, doctor's scheduling and operation. Operating room planning mainly determines the number of operating room openings per day and the operating date of the patient; the doctor scheduling mainly determines the daily work content of the doctor, and the doctor is distributed to an operating room or a morning or afternoon shift of an outpatient service; the assignment of the operation is primarily to determine to which operating room the patient is assigned.
The purpose of this problem is to minimize various costs, such as operating room opening costs, doctor costs, and patient waiting costs. Based on the characteristics of the problem, a hybrid algorithm combining dynamic planning and variable neighborhood searching is designed to solve the combination optimization problem. Provides more effective operating room management methods for hospital managers.
In order to better understand the technical solution, the technical solution will be described in detail with reference to the drawings and the specific embodiments.
Example 1:
the invention provides an operating room scheduling method considering doctor scheduling conditions, which is executed by a computer and comprises the following steps:
s1, acquiring the number I of patients, the operation duration of each patient, the number P of doctors, the number R of operating rooms and the fixed open time T of the operating roomsregMaximum allowable overtime time ToverAnd a planning period D;
setting algorithm parameters including maximum iteration number itermaxThe initial iteration number iter is 1;
s2, randomly generating an initial solution, wherein the initial solution comprises two parts, namely the operation date of the patient and the number of doctors required by each shift of the clinic department;
s3, acquiring the number of patients needing operations each day in the current solution; performing operating room allocation based on the number of the patients needing operation every day, the longest working time of the operating room and the operation duration of each patient to obtain an operating room allocation result every day;
s4, generating a daily outpatient shift scheduling result based on the daily operating room distribution result;
s5, calculating the fitness value based on the daily doctor outpatient shift scheduling result and the daily operating room distribution result to obtain the fitness values of the current solution x and x;
the fitness value is the sum of the overtime cost of an operating room, the fixed open cost of the operating room, the hospitalization cost of a patient, the operation cost of a doctor and the sitting and examining cost of the doctor;
s6, judging whether the maximum iteration number is reached, and if the iteration number does not reach the maximum iteration number, executing S7-S10; otherwise, go to S11;
s7, obtaining a solution x' through shaking;
s8, executing S3-S4;
s9, updating the solution x 'through the VND to obtain a solution x ", and calculating the fitness value of x';
s10, comparing the fitness values of x and x', updating the current solution and the iteration times, and returning to S6;
and S11, taking the current solution as an operating room scheduling scheme, and outputting the current solution together with the daily scheduling result.
The beneficial effect of this embodiment does:
1) the embodiment of the invention solves the problem of combining the scheduling of doctors and the scheduling of operating rooms in the surgical departments in large hospitals, not only reasonably allocates the operating dates and the operating rooms for patients, but also reasonably allocates the working contents of the doctors to the operating rooms or outpatients, simultaneously meets the requirements of the operations of the patients and the requirements of the outpatients for seeing the doctor, improves the utilization rate of the doctors and the operating rooms, and also improves the satisfaction degree of the patients.
The following describes the implementation process of the embodiment of the present invention in detail, as shown in fig. 1:
s1, acquiring the number I of patients, the operation duration of each patient, the number P of doctors, the number R of operating rooms and the fixed open time T of the operating roomsregMaximum allowable overtime time ToverAnd planning period D, etc.;
setting algorithm parameters which compriseMaximum number of iterations itermaxThe initial iteration number iter is 1.
And S2, randomly generating an initial solution, wherein the initial solution comprises two parts, and the two parts respectively represent the operation date of the patient and the number of doctors required by each shift of the clinic department.
For example, the planning period D is 30 days, and the initial solution includes the operation date of the patient and the number of doctors in the morning and afternoon of the outpatient service each day in the 30 days.
S3, acquiring the number of patients needing operations each day in the current solution; and performing operation room allocation based on the number of the patients needing operation every day, the longest working time of the operation room and the operation time length of each patient to obtain the operation room allocation result every day.
Specifically, the operating room allocation can be performed by using a dynamic planning algorithm to obtain daily operating room allocation results;
since each patient can only be allocated 1 time, and the longest working time of the operating room and the operation duration of each patient are known, in order to minimize the idle time of the operating room, more patients are arranged in each operating room as much as possible, so that the problem is converted into a 0-1 boxing problem with known quantity and capacity.
The number of patients corresponds to the number of items and the maximum operating time of the operating room corresponds to the maximum capacity of the case, with the aim of filling the case as far as possible until any of the remaining items are no longer placed.
An operating room is opened first, and the patients are allocated to the operating room by solving the problem through dynamic planning, the aim is to minimize the idle time of the operating room until any remaining patient is not placed in the operating room, and then the operating room is opened again, and the patients are scheduled in the same way until all the patients are scheduled in the operating room.
The transfer equation for dynamic programming is as follows:
dp[i][j]it means that only the first i patients are considered, and just put into the operation room with the capacity j, when the capacity of the operation room is j, the occupied capacity of the operation room is the largest, namely the residual space of the operation room is the smallest. i cycles from 0 to i, j cycles from 0 to Tmax，TmaxIs an operationThe length of time the chamber is fixed open plus the maximum overtime length.
When the current operation duration of the input patient is larger than the capacity j of the operation room, i.e. vjIf j, then no patient can continue to be scheduled into the operating room, resulting in the state transition equation:
dp[i][j]＝dp[i-1][j]
when the operation duration currently input into the patient is less than or equal to the capacity j of the operation room, namely vjJ is less than or equal to j, two states of placing and not placing need to be considered, one state with the largest occupied capacity of the operating room is taken, and the state transfer equation is as follows:
dp[i][j]＝max([dp[i-1][j],dp[i-1][j-t]+t),t＝vi
after dynamic planning, the number of operating rooms open and the list of patients scheduled to the operating rooms are available. In order to minimize the cost of the operating room and balance the number of open operating rooms and the overtime time, a heuristic rule is provided, and the problem of the number of open operating rooms is optimized by using the heuristic rule.
And (3) heuristic rule flow:
(1) first, through the solution of the dynamic programming algorithm, the daily operating room allocation result can be obtained, which is assumed to be b _ 1.
(2) From b _1, it can be known how many operating rooms are opened and the number of unopened operating rooms are given as I and J, respectively, and the total number is I and J, respectively.
(3) And judging whether an unopened operating room exists or not and whether an operating room has overtime or not, and outputting a daily operating room distribution result b _1 if all operating rooms are opened or no operating room has overtime.
(4) If the operating rooms are not opened and overtime exists in the operating rooms, acquiring a current operating room shift table as b _1, calculating operating room cost (comprising fixed cost and overtime cost), recording as c _1, then opening a new operating room (without overtime time), in the operating rooms where patients are scheduled, starting from the first operating room, assuming that i is 1, judging whether overtime exists or not, if yes, randomly selecting the patients from i to be placed into the newly opened operating room, stopping selecting the patients from i to be placed into the newly opened operating room until no overtime exists in i, then judging whether overtime exists in the next operating room or not, at the moment, i +1, repeating the steps until no next patient is placed in the newly opened operating room, and stopping.
(5) At this time, the daily operating room allocation result is updated to be b _2, and the corresponding operating room cost is calculated to be c _ 2.
(6) And (5) comparing the sizes of c _1 and c _2, if c _2 is smaller, continuing to open a new operating room, repeating the steps (3) to (4), and otherwise, outputting a shift table b _ 1.
And obtaining a final operating room distribution result through heuristic rules.
S4, generating a daily outpatient shift scheduling result based on the daily operating room distribution result;
acquiring a patient who performs an operation daily according to the operating room allocation result obtained in the step S3;
acquiring a daily operating doctor based on the daily operating patient;
and allocating doctors who do not perform operations every day according to the number of doctors required by each shift of the clinic department to obtain the daily outpatient shift scheduling result.
The doctor scheduling problem is solved by a greedy heuristic algorithm. The greedy algorithm always makes the best choice in the current state. The greedy strategy chosen is a key part of the algorithm and it must not have an ineffective effect. This means that the selection of this state is only relevant for this state and cannot affect the subsequent states. Patient demand for each shift during the planning cycle is generated by a poisson distribution, which indicates the number of physicians required to work for each shift. To meet the patient's needs, a greedy heuristic is applied to assign the doctor to each shift, taking into account the doctor's various constraints. For example, each doctor cannot work continuously for more than S days, nor can it be assigned more than the maximum number of shifts B within the planning horizon.
Since each operation is assigned to one doctor in advance, each doctor is operated after the operation date of each patient is determinedThe date of the room work can also be determined, and doctors cannot perform both operation and sitting diagnosis on the same day. The demand of the k shift doctor on day d is denoted nkd. Due to the limitation of the number of sitting visits and the number of continuous working days of each doctor, we need to calculate the number of sitting visits of the doctor who can participate in the sitting visit every day and the number of continuous working days of each doctor. Second, according to the greedy rule, the physician who has the most number of remaining work shifts on the day and does not violate the continuous work restriction will be assigned to that shift. The remaining physicians are scheduled according to this rule until the needs of all physicians are met. The detailed steps for solving the scheduling problem of doctors through greedy heuristic method are as follows:
t1, assume that doctor who can sit on d day generates a set pdLet d be 1;
t2 calculation set pdThe rest sitting diagnosis times and continuous working days of each doctor;
t3, starting from the k shifts on d days, arranging the doctors with the most residual sitting times and continuous work which does not exceed S days in the k shifts on d days, and making k equal to 1;
t4, update set pdRepeating the step 3, and continuing to the step T5 until the doctor requirement of the kth shift is met;
t5, k equals k +1, and the process returns to step T3;
t6, d ═ d +1, return to step T1.
S5, calculating the fitness value based on the daily doctor outpatient shift scheduling result and the daily operating room distribution result to obtain the fitness values of the current solution x and x;
the fitness value is the sum of the overtime cost of an operating room, the fixed open cost of the operating room, the hospitalization cost of a patient, the operation cost of a doctor and the sitting and examining cost of the doctor;
the doctor operation cost, the doctor sitting diagnosis cost and the fixed operating room opening cost are preset values, the operating room overtime cost is positively correlated with the operating room overtime duration, and the patient hospitalization cost is positively correlated with the interval from hospitalization to the operation date.
S6, judging whether the maximum iteration number is reached, and if the iteration number does not reach the maximum iteration number, executing S7-S10; otherwise, go to S11;
s7, obtaining a solution x' through shaking;
s8, executing S3-S4;
s9, updating the solution x 'through the VND to obtain a solution x ", and calculating the fitness value of x';
s10, comparing the fitness values of x and x', updating the current solution and the iteration times, and returning to S6;
and S11, taking the current solution as an operating room scheduling scheme, and outputting the current solution together with the daily scheduling result.
The results of experimental validation are shown in fig. 2:
under different patient numbers I, doctor numbers P and operating room numbers R, the algorithm of the embodiment of the invention is compared with a genetic algorithm, a simulated annealing algorithm, a difference algorithm and a particle swarm algorithm, and fig. 2 shows the obtained results, wherein each algorithm is operated for 10 times and then an average value and the minimum value of the 10 times are taken.
Example 2:
an operating room scheduling system that takes into account physician scheduling conditions, the system comprising:
a data acquisition module for acquiring the number of patients I, the operation duration of each patient, the number of doctors P, the number of operating rooms R and the fixed open time T of the operating roomsregMaximum allowable overtime time ToverAnd a planning period D; setting algorithm parameters including maximum iteration number itermaxThe initial iteration number iter is 1;
the initial solution generation module is used for randomly generating an initial solution, and the initial solution comprises two parts which respectively represent the operation date of the patient and the number of doctors required by each shift of the clinic;
the daily operating room distribution result generation module is used for acquiring the number of patients needing operations daily in the current solution; performing operating room allocation based on the number of the patients needing operation every day, the longest working time of the operating room and the operation duration of each patient to obtain an operating room allocation result every day;
the daily outpatient shift result generation module is used for generating a daily outpatient shift result based on the daily operating room distribution result;
an optimal solution iteration module for executing the methods from S5 to S11:
s5, calculating the fitness value based on the daily doctor outpatient shift scheduling result and the daily operating room distribution result to obtain the fitness values of the current solution x and x;
the fitness value is the sum of the overtime cost of an operating room, the fixed open cost of the operating room, the hospitalization cost of a patient, the operation cost of a doctor and the sitting and examining cost of the doctor;
s6, judging whether the maximum iteration number is reached, and if the iteration number does not reach the maximum iteration number, executing S7-S10; otherwise, go to S11;
s7, obtaining a solution x' through shaking;
s8, acquiring a daily operating room distribution result and a daily outpatient shift scheduling result of the solution x';
s9, updating the solution x 'through the VND to obtain a solution x ", and calculating the fitness value of x';
s10, comparing the fitness values of x and x', updating the current solution and the iteration times, and returning to S6;
and S11, taking the current solution as an operating room scheduling scheme, and outputting the current solution together with the daily scheduling result.
It can be understood that the operating room scheduling system considering the doctor scheduling condition provided by the embodiment of the present invention corresponds to the operating room scheduling method considering the doctor scheduling condition, and the explanation, examples, and beneficial effects of the relevant contents thereof may refer to the corresponding contents in the operating room scheduling method considering the doctor scheduling condition, and are not described herein again.
In summary, compared with the prior art, the invention has the following beneficial effects:
1. the embodiment of the invention solves the problem of combining the scheduling of doctors and the scheduling of operating rooms in the surgical departments in large hospitals, not only reasonably allocates the operating dates and the operating rooms for patients, but also reasonably allocates the working contents of the doctors to the operating rooms or outpatients, simultaneously meets the requirements of the operations of the patients and the requirements of the outpatients for seeing the doctor, improves the utilization rate of the doctors and the operating rooms, and also improves the satisfaction degree of the patients.
2. The embodiment of the invention simultaneously considers three factors of a doctor, a patient and an operating room, and considers the hospitalization time of the patient, the maximum overtime time and the fixed open time of the operating room, the continuous working time of the doctor, the doctor sitting at most for several times per day at the outpatient service, the maximum working time of the doctor per day, the maximum working time of the doctor in the planning period and the like. Various constraints and factors which need to be considered in the actual hospital are integrated, the hospital cost and the patient waiting cost are reduced, the relationship among a doctor, an operating room and a patient is balanced, and a more effective method is provided for hospital management.
3. According to the embodiment of the invention, the patient needing operation every day is distributed to the operating room as a 0-1 packing problem, the solution of the problem is quickly obtained by dynamic programming, then the solution is further optimized by heuristic rules to obtain an approximate optimal solution of the operation distribution problem, and finally a variable neighborhood search algorithm finally obtains a global better solution by maximizing the iteration times and searching different neighborhood structures.
It should be noted that, through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments. In this document, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (8)
1. An operating room scheduling method considering doctor scheduling conditions, comprising the following steps:
s1, acquiring the number I of patients, the operation duration of each patient, the number P of doctors, the number R of operating rooms and the fixed open time T of the operating roomsregMaximum allowable overtime time ToverAnd a planning period D;
setting algorithm parameters including maximum iteration number itermaxThe initial iteration number iter is 1;
s2, randomly generating an initial solution, wherein the initial solution comprises two parts, namely the operation date of the patient and the number of doctors required by each shift of the clinic department;
s3, acquiring the number of patients needing operations each day in the current solution; performing operating room allocation based on the number of the patients needing operation every day, the longest working time of the operating room and the operation duration of each patient to obtain an operating room allocation result every day;
s4, generating a daily outpatient shift scheduling result based on the daily operating room distribution result;
s5, calculating the fitness value based on the daily doctor outpatient shift scheduling result and the daily operating room distribution result to obtain the fitness values of the current solution x and x;
the fitness value is the sum of the overtime cost of an operating room, the fixed open cost of the operating room, the hospitalization cost of a patient, the operation cost of a doctor and the sitting and examining cost of the doctor;
s6, judging whether the maximum iteration number is reached, and if the iteration number does not reach the maximum iteration number, executing S7-S10; otherwise, go to S11;
s7, obtaining a solution x' through shaking;
s8, executing S3-S4;
s9, updating the solution x 'through the VND to obtain a solution x ", and calculating the fitness value of x';
s10, comparing the fitness values of x and x', updating the current solution and the iteration times, and returning to S6;
and S11, taking the current solution as an operating room scheduling scheme, and outputting the current solution together with the daily scheduling result.
2. The operating room scheduling method considering doctor' S scheduling as claimed in claim 1, wherein said S3, obtaining the number of patients needing operation per day in the current solution; and performing operating room allocation based on the number of patients needing operation each day, the longest working time of the operating room and the operation duration of each patient to obtain the daily operating room allocation result, wherein the daily operating room allocation result comprises the following steps:
operating room allocation is carried out by utilizing a dynamic planning algorithm to obtain daily operating room allocation results;
the number of patients corresponds to the number of articles of the dynamic planning algorithm, the maximum working time of the operating room corresponds to the maximum capacity of the box of the dynamic planning algorithm, and the aim is to minimize the idle time of the operating room.
3. The method as claimed in claim 2, wherein after the operation room assignment is performed by using a dynamic planning algorithm to obtain the daily operation room assignment result, the method further comprises:
optimizing the number of open operating rooms based on heuristic rules;
the heuristic rules include:
k1, obtaining the number of the operating rooms opened and the number of the unopened operating rooms on the basis of the daily operating room distribution result b _ 1;
k2, judging whether an unopened operating room exists or not and whether an operating room is overtime or not;
if all the operating rooms are opened or no operating room is overtime, outputting a daily operating room distribution result b _ 1;
if an operating room is not opened and the operating room has overtime, acquiring the operating room cost c _1 of the current operating room distribution result, then opening a new operating room, starting from the first operating room in the operating room in which the patients are arranged, judging whether the overtime exists, if so, randomly selecting the patients from the operating rooms to be placed into the newly opened operating room, stopping selecting the patients from the operating room to be placed into the newly opened operating room until the overtime does not exist in the operating room, then judging whether the next operating room has overtime exists, and repeating the steps until the newly opened operating room does not contain any next patient;
k3, updating to obtain a daily operating room distribution result b _2, and calculating the corresponding operating room cost c _ 2;
k4, comparing the sizes of c _1 and c _2, if c _2 is smaller, continuing to open a new operating room, repeating the step K2, otherwise outputting the shift table b _ 1.
4. The operating room scheduling method considering doctor scheduling as claimed in claim 3, wherein the generating of the daily outpatient scheduling result based on the daily operating room assignment result comprises:
obtaining a patient performing a daily operation based on the daily operating room assignment;
acquiring a daily operating doctor based on the daily operating patient;
according to the number of doctors required by each shift of the clinic department, doctors who do not perform operations every day are distributed to obtain the daily outpatient shift scheduling result;
and the generation method of the daily outpatient shift scheduling result comprises the following steps:
t1, assume that doctor who can sit on d day generates a set pdLet d be 1;
t2 calculation set pdThe rest sitting diagnosis times and continuous working days of each doctor;
t3, starting from the k shifts on d days, arranging the doctors with the most residual sitting times and continuous work which does not exceed S days in the k shifts on d days, and making k equal to 1;
t4, update set pdRepeating the step 3, and continuing to the step T5 until the doctor requirement of the kth shift is met;
t5, k equals k +1, and the process returns to step T3;
t6, d ═ d +1, return to step T1.
5. An operating room scheduling system that takes into account physician scheduling, the system comprising:
a data acquisition module for acquiring the number of patients I, the operation duration of each patient, the number of doctors P, the number of operating rooms R and the fixed open time T of the operating roomsregMaximum allowable overtime time ToverAnd a planning period D; setting algorithm parameters including maximum iteration number itermaxThe initial iteration number iter is 1;
the initial solution generation module is used for randomly generating an initial solution, and the initial solution comprises two parts which respectively represent the operation date of the patient and the number of doctors required by each shift of the clinic;
the daily operating room distribution result generation module is used for acquiring the number of patients needing operations daily in the current solution; performing operating room allocation based on the number of the patients needing operation every day, the longest working time of the operating room and the operation duration of each patient to obtain an operating room allocation result every day;
the daily outpatient shift result generation module is used for generating a daily outpatient shift result based on the daily operating room distribution result;
an optimal solution iteration module for executing the methods from S5 to S11:
s5, calculating the fitness value based on the daily doctor outpatient shift scheduling result and the daily operating room distribution result to obtain the fitness values of the current solution x and x;
the fitness value is the sum of the overtime cost of an operating room, the fixed open cost of the operating room, the hospitalization cost of a patient, the operation cost of a doctor and the sitting and examining cost of the doctor;
s6, judging whether the maximum iteration number is reached, and if the iteration number does not reach the maximum iteration number, executing S7-S10; otherwise, go to S11;
s7, obtaining a solution x' through shaking;
s8, acquiring a daily operating room distribution result and a daily outpatient shift scheduling result of the solution x';
s9, updating the solution x 'through the VND to obtain a solution x ", and calculating the fitness value of x';
s10, comparing the fitness values of x and x', updating the current solution and the iteration times, and returning to S6;
and S11, taking the current solution as an operating room scheduling scheme, and outputting the current solution together with the daily scheduling result.
6. The system as claimed in claim 5, wherein the number of patients requiring operation per day in the current solution is obtained; and performing operating room allocation based on the number of patients needing operation each day, the longest working time of the operating room and the operation duration of each patient to obtain the daily operating room allocation result, wherein the daily operating room allocation result comprises the following steps:
operating room allocation is carried out by utilizing a dynamic planning algorithm to obtain daily operating room allocation results;
the number of patients corresponds to the number of articles of the dynamic planning algorithm, the maximum working time of the operating room corresponds to the maximum capacity of the box of the dynamic planning algorithm, and the aim is to minimize the idle time of the operating room.
7. The system of claim 6, further comprising, after performing the assignment of the operating rooms using the dynamic planning algorithm to obtain the assignment of the operating rooms for each day:
optimizing the number of open operating rooms based on heuristic rules;
the heuristic rules include:
k1, obtaining the number of the operating rooms opened and the number of the unopened operating rooms on the basis of the daily operating room distribution result b _ 1;
k2, judging whether an unopened operating room exists or not and whether an operating room is overtime or not;
if all the operating rooms are opened or no operating room is overtime, outputting a daily operating room distribution result b _ 1;
if an operating room is not opened and the operating room has overtime, acquiring the operating room cost c _1 of the current operating room distribution result, then opening a new operating room, starting from the first operating room in the operating room in which the patients are arranged, judging whether the overtime exists, if so, randomly selecting the patients from the operating rooms to be placed into the newly opened operating room, stopping selecting the patients from the operating room to be placed into the newly opened operating room until the overtime does not exist in the operating room, then judging whether the next operating room has overtime exists, and repeating the steps until the newly opened operating room does not contain any next patient;
k3, updating to obtain a daily operating room distribution result b _2, and calculating the corresponding operating room cost c _ 2;
k4, comparing the sizes of c _1 and c _2, if c _2 is smaller, continuing to open a new operating room, repeating the step K2, otherwise outputting the shift table b _ 1.
8. The operating room scheduling system of claim 5 wherein generating daily outpatient scheduling results based on daily operating room assignment results comprises:
obtaining a patient performing a daily operation based on the daily operating room assignment;
acquiring a daily operating doctor based on the daily operating patient;
according to the number of doctors required by each shift of the clinic department, doctors who do not perform operations every day are distributed to obtain the daily outpatient shift scheduling result;
and the generation method of the daily outpatient shift scheduling result comprises the following steps:
t1, assume that doctor who can sit on d day generates a set pdLet d be 1;
t2 calculation set pdThe rest sitting diagnosis times and continuous working days of each doctor;
t3, starting from the k shifts on d days, arranging the doctors with the most residual sitting times and continuous work which does not exceed S days in the k shifts on d days, and making k equal to 1;
t4, update set pdRepeating the step 3, and continuing to the step T5 until the doctor requirement of the kth shift is met;
t5, k equals k +1, and the process returns to step T3;
t6, d ═ d +1, return to step T1.
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