JP4959752B2 - Method and apparatus for adjusting weighting coefficient of waiting time evaluation function - Google Patents

Description

  The present invention relates to a method and apparatus for adjusting a weighting factor of a latency evaluation function used for determining a service order.

In order to reduce the waiting time of users that occur in service providing facilities such as hospitals, beauty salons, restaurants, etc., a method for optimizing the order of users who receive services has been proposed.
For example, the “service time allocation method and weighting coefficient adjustment device” disclosed in Patent Document 1 is such that when creating a service order and assigning a non-reserved day-to-day customer to a reserved free time, The total waiting time of each customer when forcibly assigned to each free time is calculated, and the customer on the day is assigned to the free time that minimizes the total waiting time.

Japanese Patent No. 4143110

  The method and apparatus of Patent Literature 1 change the order so that the entire waiting time by the evaluation function is minimized. At this time, the waiting time is increased / decreased using an evaluation function having a predetermined weighting coefficient to adjust the priority of order determination. For example, when the waiting time of a reservation customer who has been given the highest priority in the initial order or a customer in the early order of reception increases, the increase is weighted so that the service of the customer is prioritized. An evaluation function having a weighting coefficient greatly affects the determination of the optimal order, but the evaluation function and its weighting coefficient are determined by trial and error. For this reason, the method and apparatus of Patent Document 1 are not practical, and in order to configure the system as an actually usable system, it is necessary to adjust the weighting coefficient as needed in consideration of the contents of the service.

  The present invention has been made in view of the above problems, and a main object thereof is to appropriately adjust a weighting coefficient of a waiting time evaluation function for determining a service order.

In order to solve the above-mentioned problem, the present invention is based on the performance data including the waiting time of the service user in a predetermined period stored in advance and weighting coefficient data including two or more weighting coefficients. A weighting coefficient adjustment method for adjusting a weighting coefficient of a waiting time evaluation function according to the computer,
(1) extracting initial order data of a predetermined date from the result data;
(2) selecting a weighting factor from the weighting factor data;
(3) setting an order of users of the service;
(4) calculating the weighted waiting time by the weighting coefficient when the service is performed in the order, calculating a weighted waiting time total value obtained by summing the weighted waiting times, and storing the weighted waiting time;
(5) If (4) has been performed for the order of users of all the services, the process proceeds to (6); otherwise, the process proceeds to (3);
(6) identifying and storing a minimum weighted waiting time total value and its order among the weighted waiting time total values stored in (4);
(7) If (3) to (6) have been performed for all weighting coefficients, proceed to (8); otherwise, proceed to (2);
(8) Among the total weighted waiting time values stored in (6), the one having the smallest actual waiting time total value obtained by summing up the corresponding actual waiting times is identified and corresponds to the actual waiting time total value. Storing the weighting factor;
(9) If (1) to (8) have been performed for all days within the predetermined period, proceed to (10); otherwise, proceed to (1);
(10) A step of identifying and storing a weighting coefficient having the highest frequency among the weighting coefficients stored in (8) is performed.

  According to this method, the weighting coefficient that minimizes the total value of the waiting time after weighting when the order is changed from the beginning is specified, so that the optimum weighting coefficient for the user can be obtained.

  Further, the present invention is a weighting coefficient adjustment method, wherein in (4), a value obtained by adding the initial waiting time by applying the weighting coefficient to the increment after the change of order from the beginning of the waiting time of each user. The waiting time after weighting is used.

  According to this method, when the order is changed from the beginning, the weighting coefficient that minimizes the total value of the waiting time after weighting weighted to the increase in waiting time is specified, so that the user's intention for the increase is reflected. can do.

  Further, the present invention is a weighting coefficient adjustment method, wherein when the increase is smaller than a predetermined value, a weighted increase obtained by applying a weighting coefficient to the increase is smaller than the increase. When is greater than a predetermined value, the weighting coefficient is selected such that the increment after weighting is greater than the increment.

According to this method, an increase in waiting time is underestimated to a predetermined value, and is overestimated when it exceeds a predetermined value, so even if the waiting time increases, the increase is within the allowable limit for the user. It can be suppressed below a certain predetermined value. That is, it is possible to reflect the patient's intention that the increase in the waiting time is permissible up to a predetermined value, but it is difficult to endure the increase in the predetermined value or more. For example, a quadratic function .DELTA.Tw = a * [Delta] T ² increment [Delta] T of the waiting time and weighting function to adjust the predetermined value which is the boundary of the evaluation by a factor a.

  Further, the present invention is a weighting coefficient adjustment method, wherein the computer selects, in (8), the actual waiting time total value smaller than the actual data value, and changes the order from the selected one. The order in which there is no user whose actual waiting time has increased is extracted, and the one having the minimum actual waiting time is identified from among the extracted orders.

  According to this method, since the order in which there is no user whose waiting time has increased is extracted, it is possible to specify an order and a weighting coefficient so that all users have a waiting time not longer than the actual data.

  The present invention is also a weighting coefficient adjustment method, wherein in (8), the computer further extracts, from the selected items, an order in which a user whose actual waiting time has increased due to the order change, The extracted actual waiting time is smaller than the average value of the original waiting times, and the extracted one having the smallest actual waiting time total value is specified.

  According to this method, even in the order in which there are users whose waiting time has increased, those whose actual waiting time is smaller than the average value of the original waiting time are extracted. An order and weighting factor can be specified that results in no latency.

  The present invention is also a weighting coefficient adjustment method, wherein the computer stores, in (4), including the total downtime of the equipment that provides the service to the user, and in (6). The order including the evaluation of the total value of the non-working time is specified, and the weighting coefficient is stored in (8) including the evaluation of the total value of the non-working time.

  According to this method, evaluation is performed including not only the waiting time of the service user but also the downtime of the facility that provides the service, so that a more appropriate weighting factor can be specified. The service providing facilities include not only equipment but also human resources.

  The present invention includes a weighting coefficient adjustment device. In addition, the problems disclosed by the present application and the solutions thereof will be clarified by the description of the mode for carrying out the invention and the drawings.

  According to the present invention, it is possible to appropriately adjust the weighting coefficient of the waiting time evaluation function for determining the service order.

It is a figure which shows the structure of the weighting coefficient adjustment apparatus. It is a figure which shows the structure of the data previously stored in the memory | storage part 15 of the weighting coefficient adjustment apparatus 1, (a) shows the structure of the performance data 15A, (b) shows the structure of the weighting coefficient data 15B, c) shows the relationship between the waiting time increase ΔT and the waiting time weighting time ΔTw. It is a figure which shows the structure of the data produced | generated in the process of the weighting coefficient adjustment apparatus 1, and memorize | stored in the memory | storage part 15, (a) shows the structure of initial order data 15C, (b)-(d) is optimization. The structure of the order data 15D is shown. It is a figure which shows the structure of the data produced | generated in the process of the weighting coefficient adjustment apparatus 1, and memorize | stored in the memory | storage part 15, (a) shows the structure of the total value data 15E, (b) shows optimal weighting coefficient data 15F. The configuration is shown. It is a flowchart which shows the process of the weighting coefficient adjustment apparatus 1. FIG. It is a flowchart which shows the detail of the optimal weighting coefficient specific process.

  Hereinafter, embodiments for carrying out the present invention will be described with reference to the drawings. The weighting coefficient adjustment apparatus for waiting time evaluation function according to the embodiment of the present invention stores service performance data for each day in the past predetermined period in advance, and changes the weighting coefficient and service order as parameters for each day. Is calculated, the optimum weighting coefficient for the day is specified based on the waiting time, and the most frequent weighting coefficient is specified throughout the predetermined period. According to this, the weighting coefficient of the waiting time evaluation function for determining the service order can be adjusted appropriately. In the following, an embodiment in which the weighting coefficient adjusting device is applied to a hospital will be described.

≪Device configuration and overview≫
FIG. 1 is a diagram illustrating a configuration of the weighting coefficient adjusting apparatus 1. The weighting coefficient adjustment apparatus 1 includes a communication unit 11, a display unit 12, an input unit 13, a processing unit 14, and a storage unit 15. The communication unit 11 is a part that performs IP communication with other devices via a network, and is realized by, for example, a NIC (Network Interface Card) or the like. The display unit 12 is a part that displays data according to an instruction from the processing unit 14, and is realized by, for example, a liquid crystal display (LCD). The input unit 13 is a part where an operator inputs data (for example, medical examination result data or weighting coefficient data), and is realized by, for example, a keyboard or a mouse. The processing unit 14 transfers data between the units and controls the weighting coefficient adjusting apparatus 1 as a whole. A CPU (Central Processing Unit) executes a program stored in a predetermined memory. Realized. The storage unit 15 stores data from the processing unit 14 and reads the stored data, and is realized by, for example, a nonvolatile storage device such as a flash memory or a hard disk device. The weighting coefficient adjustment device 1 may be a stand-alone device (PC (Personal Computer) or the like), or may be a device (server or the like) that can communicate with a plurality of terminals via a network. Good.

<< Data structure >>
FIG. 2 is a diagram illustrating a configuration of data stored in advance in the storage unit 15 of the weighting coefficient adjustment apparatus 1. FIG. 2A shows the configuration of the result data 15A. The result data 15A indicates the results of the patient's examination status on a certain past day, and includes patient ID 15A1, reservation time 15A2, reception time 15A3, examination required time 15A4, start time 15A5, waiting time 15A6, and doctor idle time 15A7. Consists of records that contain The patient ID 15A1 is an ID unique to the patient. The appointment time 15A2 is the start time of the examination booked by the patient. The reception time 15A3 is the time when the patient is actually received. The examination required time 15A4 is the time taken for the patient examination. The start time 15A5 is the time when the diagnosis is actually started. The waiting time 15A6 is the time that the patient waits until the start of the examination, and is the time from the reception time or the reservation time to the start time. The doctor idle time 15A7 is a time during which the doctor does not consult between the previous patient and the next patient.

FIG. 2B shows the configuration of the weighting coefficient data 15B. The weighting coefficient data 15B lists combinations of weighting coefficients a and b that are parameters of the waiting time evaluation function. The weighting function of the waiting time by the weighting factors a and b is shown in the following formula 1.
ΔTw = a * ΔT ^ b Equation 1
ΔTw: Weighting time for increment ΔT: Increase time (waiting time increase) for patients whose waiting time has increased due to order change

FIG. 2C shows the relationship between the waiting time increase ΔT and the waiting time weighting time ΔTw. For example, when a = 1 and b = 1, the function is not weighted as ΔTw = ΔT. a = 0.1, the case of b = ^2, ΔTw = 0.1ΔT 2 becomes, [Delta] T is up to 10 minutes falls below .DELTA.Tw = [Delta] T is, [Delta] T is the subsequent 10 minutes over from .DELTA.Tw = [Delta] T. This reflects the patient's intention that the increase in waiting time can be tolerated up to 10 minutes, but it is unbearable to increase it for more than 10 minutes.

  3 and 4 are diagrams illustrating the configuration of data generated by the processing of the weighting coefficient adjusting apparatus 1 and stored in the storage unit 15. FIG. 3A shows the configuration of the initial order data 15C. The initial order data 15C is data extracted every day from the result data 15A and includes a patient ID 15C1, a reservation time 15C2, a reception time 15C3, a consultation required time 15C4, a start time 15C5, a waiting time 15C6, and a doctor idle time 15C7. Consists of records. Each item is the same as each item of the performance data 15A.

  3B to 3D show the configuration of the optimization order data 15D. The optimization order data 15D indicates the optimal order of the patient to be examined for each weighting coefficient. The patient ID 15D1, the appointment time 15D2, the reception time 15D3, the examination time 15D4, the start time 15D5, the waiting time 15D6, and the waiting time increase. It is composed of records including a minute 15D7, an increment weighting 15D8, a waiting time after weighting 15D9, and a doctor idle time 15DA. Each item of patient ID 15D1, reservation time 15D2, reception time 15D3, examination required time 15D4, start time 15D5, waiting time 15D6, and doctor idle time 15DA is the same as each item of performance data 15A. The waiting time increase 15D7 is a value obtained by subtracting the initial waiting time 15C6 from the waiting time 15D6 after the order change for the patient, and indicates an increase in waiting time due to the order change. The increment weight 15D8 is a value obtained by weighting the positive value by the coefficients a and b among the waiting time increment 15D7. The post-weighting waiting time 15D9 is a value obtained by adding the increment weighting 15D8 to the initial waiting time 15C6. FIG. 3B shows the optimization order data I when the coefficients a = 0 and b = 0 (no weighting). FIG. 3C shows the optimization order data II when the coefficients a = 2 and b = 1 (linear function). FIG. 3D shows the optimization order data III when the coefficients a = 0.1 and b = 2 (quadratic function).

  FIG. 4A shows the configuration of the total value data 15E. The total value data 15E indicates the total value of the waiting time and the total value of the idle time for each order of the examined patients regarding the weighting coefficient, and includes a record including the order 15E1, the total waiting time value 15E2, and the idle time total value 15E3. Consists of. The order 15E1 indicates the order of the examined patients. The waiting time total value 15E2 indicates the total value of the waiting time after weighting of the patient predicted in the case of the order. The idle time total value 15E3 indicates the total value of the doctor's idle time predicted in the case of the order.

  FIG. 4B shows the configuration of the optimum weighting coefficient data 15F. The optimum weighting coefficient data 15F indicates an optimum combination of weighting coefficients for each date, and is composed of records including the date 15F1 and coefficients a and b. The date 15F1 indicates a date within a predetermined period. Coefficients a and b indicate the optimum combination of weighting coefficients for the date.

≪Device processing≫
FIG. 5 is a flowchart showing processing of the weighting coefficient adjustment apparatus 1. It is assumed that the storage unit 15 of the weighting coefficient adjustment device 1 stores in advance performance data 15A and weighting coefficient data 15B acquired by the processing unit 14 via the communication unit 11 or the input unit 13. Then, the weighting coefficients a and b of the next day are specified from the weighting coefficient data 15B on the basis of the actual data 15A up to the current day by the batch processing of the weighting coefficient adjustment apparatus 1. Details will be described below.

  First, the weighting coefficient adjusting apparatus 1 extracts the performance data 15A on a predetermined day as the initial order data 15C in a predetermined period (for example, the last one month) (S501). The result data 15A on the predetermined day is extracted in order from the first day to the last day of the predetermined period, for example. Next, the weighting coefficients a and b are selected from the weighting coefficient data 15B (S502). For example, the weighting coefficients a and b are selected in order from the first combination of the weighting coefficient data 15B. Then, the order of the examined patients is set (S503). The order of the examined patients is set according to the permutation of patient IDs, for example.

  Subsequently, the weighting coefficient adjusting apparatus 1 creates the optimization order data 15D from the initial order data 15C, calculates the total value of the waiting time 15D9 after weighting and the total value of the doctor idle time 15DA, and calculates each total value as a total value. The data 15E is stored in the waiting time total value 15E2 and the idle time total value 15E3 (S504). At this time, data indicating the order is set in the order 15E1 of the total value data 15E. Then, it is determined whether or not the total value of the waiting time after weighting and the idle time is calculated for the order of all the examined patients (S505). If all the orders have not been calculated (N in S505), the order setting of the examined patients is performed again (S503). If all the orders are calculated (Y in S505), the total waiting time value 15E2 and the idle time total value 15E3 and the order 15E1 that are minimized are identified with reference to the total value data 15E related to the weighting coefficient. The corresponding optimization order data 15D is stored (S506). At this time, only the total waiting time value 15E2 may be evaluated excluding the idle time total value 15E3.

  Then, the weighting coefficient adjusting apparatus 1 determines whether or not all the weighting coefficients a and b are processed in the weighting coefficient data 15B (S507). If all the weighting factors have not been processed (N in S507), the weighting factors are selected again (S502). If all the weighting factors have been processed (Y in S507), the optimum weighting factors a and b are specified for the predetermined date and stored in the optimum weighting factor data 15F (S508). At this time, the predetermined date is set to the date 15F1. The specification of the optimum weighting coefficient will be described in detail separately.

  Furthermore, the weighting coefficient adjustment apparatus 1 determines whether or not processing has been performed for all days in the predetermined period (S509). If all days have not been processed (N in S509), the result data 15A is extracted again (S501). If all days have been processed (N in S509), the combination of the most frequently occurring weighting factors a and b is identified with reference to the optimum weighting factor data 15F and stored in the storage unit 15 (S510). . This makes it possible to specify a weighting function having optimum weighting coefficients a and b when evaluating the waiting time.

  FIG. 6 is a flowchart showing details of the optimum weighting coefficient specifying process in S508 of FIG. This process is performed with reference to the initial order data 15C and the optimization order data 15D stored in the storage unit 15 of the weighting coefficient adjustment apparatus 1. First, the weighting coefficient adjustment apparatus 1 calculates an average value per patient for the waiting time 15C6 in the initial order data 15C (S601). Taking FIG. 3A as an example, the average value of the waiting time 15C6 is Ta = 25 minutes.

  Next, the total value of the waiting time 15D6 and the total value of the doctor idle time 15DA of the optimization order data 15D are selected to be smaller than the value of the initial order data 15C (S602). In the logical expression, (ΣTm ≦ ΣT0) AND (ΣTdm ≦ ΣTd0). Taking FIG. 3 as an example, optimization order data I, II and III are selected.

  From the selected optimization order data, an order with no patients whose waiting time has increased due to the order change is extracted (S603). In the logical expression, ΔT ≦ 0. Taking FIG. 3 as an example, there is no optimization order data to be extracted.

  Subsequently, among the orders of patients whose waiting time has increased due to the order change, those whose waiting time is smaller than the average value are extracted (S604). The waiting time here may be the actual waiting time 15D6 or the weighted waiting time 15D9. Therefore, in the logical expression, {(ΔT> 0) AND (Tm <Ta)} OR {(ΔT> 0) AND (Tm ′> Ta)}. Taking FIG. 3 as an example, optimization order data II and III are extracted. According to this, even if there is a patient whose waiting time has increased, since the entire waiting time is selected to be smaller than the average value, the increase is suppressed to a minimum and becomes extremely unfair (disadvantageous). I don't think it will happen.

  Among the orders extracted in the processes of S603 and S604, the one having the smallest total value of the actual waiting time 15D6 and the total value of the doctor idle time 15DA is specified (S605). According to FIG. 3, the optimization order data III is specified. As a result, the optimum weighting coefficients for a given day are a = 0.1 and b = 2, and are stored in the optimum weighting coefficient data 15F of the storage unit 15. Note that only the total value of the actual waiting time 15D6 may be evaluated excluding the total value of the doctor idle time 15DA.

  Although the embodiment of the present invention has been described above, the program executed by the processing unit 14 is recorded on a computer-readable recording medium so that each unit in the weighting coefficient adjusting apparatus 1 shown in FIG. It is assumed that the weighting coefficient adjusting apparatus 1 according to the embodiment of the present invention is realized by causing the computer to read and execute the recorded program. Note that the program may be provided to the computer via a network such as the Internet, or a semiconductor chip or the like in which the program is written may be incorporated in the computer.

  According to the embodiment of the present invention described above, according to the above, when optimizing the examination order of patients, the waiting time is highly effective according to the service type and content, and the doctor idle period is high. The most suitable waiting time weighting coefficient can be calculated so that the time is also shortened. Next, try to eliminate as many people as possible when waiting time increases. In addition, even if there are people who have increased waiting time, in order to evaluate the unfairness of the increase in waiting time, the average value of the waiting time in the past is compared with the waiting time after the order change. The order can be selected so as not to cause unfairness in patients. Since the weighting coefficient is adjusted every day, it is possible to select a weighting coefficient suitable for a situation that changes from day to day, thereby further improving the waiting time reduction effect.

<< Other embodiments >>
As mentioned above, although the form for implementing this invention was demonstrated, the said embodiment is for making an understanding of this invention easy, and is not for limiting and interpreting this invention. The present invention can be changed and improved without departing from the gist thereof, and equivalents thereof are also included in the present invention. For example, in the above-described embodiment, a service called “diagnosis” provided to a patient in a hospital has been described. However, the present invention is not limited thereto, and the present invention is applied to any facility that provides some service to a user. can do. For example, it may be a beauty salon that provides beauty, or a restaurant that provides beverages and dishes.

DESCRIPTION OF SYMBOLS 1 Weighting coefficient adjustment apparatus 14 Processing part 15 Memory | storage part 15A Performance data 15B Weighting coefficient data 15C Initial order data 15D Optimization order data

Claims (12)

The weighting coefficient of the waiting time evaluation function related to the service is adjusted by the computer based on the performance data including the waiting time of the user of the service in the predetermined period stored in advance and the weighting coefficient data including two or more weighting coefficients. A weighting coefficient adjustment method,
The computer
(1) extracting initial order data of a predetermined date from the result data;
(2) selecting a weighting factor from the weighting factor data;
(3) setting an order of users of the service;
(4) calculating the weighted waiting time by the weighting coefficient when the service is performed in the order, calculating a weighted waiting time total value obtained by summing the weighted waiting times, and storing the weighted waiting time;
(5) If (4) has been performed for the order of users of all the services, the process proceeds to (6); otherwise, the process proceeds to (3);
(6) identifying and storing a minimum weighted waiting time total value and its order among the weighted waiting time total values stored in (4);
(7) If (3) to (6) have been performed for all weighting coefficients, proceed to (8); otherwise, proceed to (2);
(8) Among the total weighted waiting time values stored in (6), the one having the smallest actual waiting time total value obtained by summing up the corresponding actual waiting times is identified and corresponds to the actual waiting time total value. Storing the weighting factor;
(9) If (1) to (8) have been performed for all days within the predetermined period, proceed to (10); otherwise, proceed to (1);
(10) A step of identifying and storing a weighting coefficient having the highest frequency among the weighting coefficients stored in (8);
The weighting coefficient adjustment method characterized by performing. The weighting coefficient adjustment method according to claim 1,
In (4), the weighting coefficient is characterized in that a value obtained by applying the weighting coefficient to the increment after the change in order from the beginning of each user's waiting time and adding the initial waiting time is the weighted waiting time. Adjustment method. The weighting coefficient adjustment method according to claim 2,
When the increase is smaller than a predetermined value, a weighted increase obtained by applying a weighting coefficient to the increase is smaller than the increase. When the increase is larger than a predetermined value, the weighted increase. The weighting factor is selected such that is larger than the increment. A weighting coefficient adjustment method according to claim 2 or claim 3, wherein
The computer
In (8), the actual waiting time total value is selected to be smaller than the value of the actual data, and the order in which there is no user whose actual waiting time has increased due to the order change is extracted from the selected values. A method of adjusting a weighting coefficient, wherein the one having the smallest total actual waiting time is specified from among the extracted values. The weighting coefficient adjustment method according to claim 4,
The computer
In (8), the order in which the users whose actual waiting time has increased due to the order change is further extracted from the selections, and the actual waiting time is smaller than the average of the original waiting times from the extracted one. A method for adjusting a weighting coefficient, comprising: extracting a thing and specifying the one having the smallest total actual waiting time value among the extracted ones. A weighting coefficient adjustment method according to any one of claims 2 to 5,
The computer
In (4), including the total value of the downtime of the equipment that provides the service to the user,
In (6), the order is specified including the evaluation of the total value of the downtime,
In (8), the weighting coefficient is stored including the evaluation of the total value of the downtime.
Weighting coefficient adjustment for adjusting the weighting coefficient of the waiting time evaluation function related to the service based on the actual data including the waiting time of the user of the service in the predetermined period and weighting coefficient data including two or more weighting coefficients A device,
(1) means for extracting initial order data of a predetermined date from the actual data;
(2) means for selecting a weighting coefficient from the weighting coefficient data;
(3) means for setting the order of users of the service;
(4) Means for calculating and storing a weighted waiting time total value obtained by calculating the weighted waiting time by the weighting coefficient when the services are performed in the order, and summing the weighted waiting time;
(5) If (4) has been performed for the order of users of all the services, proceed to (6); otherwise, proceed to (3);
(6) Among the weighted waiting time total values stored in (4), a means for specifying and storing a minimum weighted waiting time total value and its order;
(7) If (3) to (6) have been performed for all weighting coefficients, proceed to (8); otherwise, proceed to (2);
(8) Among the total weighted waiting time values stored in (6), the one having the smallest actual waiting time total value obtained by summing up the corresponding actual waiting times is identified and corresponds to the actual waiting time total value. Means for storing the weighting factor;
(9) If (1) to (8) have been performed for all days within the predetermined period, proceed to (10); otherwise, proceed to (1);
(10) Among the weighting coefficients stored in (8), a means for specifying and storing the most frequently used weighting coefficient;
A weighting coefficient adjusting device comprising: The weighting coefficient adjustment apparatus according to claim 7,
In (4), the weighting coefficient is characterized in that a value obtained by applying the weighting coefficient to the increment after the change in order from the beginning of each user's waiting time and adding the initial waiting time is the weighted waiting time. Adjustment device. The weighting coefficient adjustment device according to claim 8,
When the increase is smaller than a predetermined value, a weighted increase obtained by applying a weighting coefficient to the increase is smaller than the increase. When the increase is larger than a predetermined value, the weighted increase. The weighting factor is selected so that is larger than the increase. The weighting coefficient adjusting device according to claim 8 or 9, wherein
In (8), the actual waiting time total value is selected to be smaller than the value of the actual data, and the order in which there is no user whose actual waiting time has increased due to the order change is extracted from the selected values. A weighting coefficient adjusting apparatus characterized by identifying the one having the smallest actual waiting time total value among the extracted values. The weighting coefficient adjusting device according to claim 10,
In (8), the order in which the users whose actual waiting time has increased due to the order change is further extracted from the selections, and the actual waiting time is smaller than the average of the original waiting times from the extracted one. A weighting coefficient adjustment apparatus characterized by extracting a thing and specifying the one with the smallest actual waiting time total value from among the extracted ones. A weighting coefficient adjustment device according to any one of claims 8 to 11,
In (4), including the total value of the downtime of the equipment that provides the service to the user,
In (6), the order is specified including the evaluation of the total value of the downtime,
In (8), the weighting coefficient is stored including evaluation of the total value of the downtime.

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