CN112598284A - Limited resource dynamic allocation method for endowment system - Google Patents

Limited resource dynamic allocation method for endowment system Download PDF

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CN112598284A
CN112598284A CN202011554805.2A CN202011554805A CN112598284A CN 112598284 A CN112598284 A CN 112598284A CN 202011554805 A CN202011554805 A CN 202011554805A CN 112598284 A CN112598284 A CN 112598284A
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沈晓蓓
熊才源
余玉刚
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University of Science and Technology of China USTC
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Abstract

The invention relates to a limited resource dynamic allocation method for an endowment system, which considers the problems of how to dynamically allocate endowment homes with different service qualities and old people with different health conditions. The invention firstly divides the rest homes providing different service qualities in the rest home system into office rest homes and community rest homes, divides the old people with different health levels into the old people with high priority and the old people with low priority, and then mathematically samples related concepts, thereby providing a dynamic allocation method for the rest home service system from the mathematical point of view. The method not only overcomes the defects of prior-to-first-to-take distribution strategies and complete distribution strategies commonly used in the existing endowment system, but also greatly reduces the service cost and improves the social welfare.

Description

Limited resource dynamic allocation method for endowment system
Technical Field
The invention relates to the field of service of an endowment system, in particular to the problem of dynamic allocation of multiple types of limited resources and multiple types of random requirements.
Background
In recent years, due to the increasing aging trend of the population, nursing care is more and more important in social welfare, wherein a nursing home becomes a key resource in nursing care. However, in reality, the limited resources of the nursing home are far from meeting the increasing demand of the elderly. In Beijing, the office nursing homes released in the whole market for one year can only meet the requirements of the old in one week. In a certain place, each old person needs to queue for 25.5 months on average to enter an office nursing home. Unfortunately, a large number of elderly people die each year because they do not have timely access to services.
Aiming at the problem of scarcity of endowment resources, in reality, a government actively encourages slightly-defective old people to select community endowment homes for endowment, meanwhile, the office endowment homes divide the old people into different priority service levels according to the health conditions of the old people, the old people with high priority enjoy the priority of being served, and the old people with low priority can appropriately wait in the endowment system. In practice, the elderly care system often uses two service strategies, one is a first-come first-serve strategy, and the method arranges the elderly to enter the nursing home according to the time sequence before and after the elderly apply for the nursing home. However, this service method brings a serious problem of mismatching of the bed and the demand of the old people in reality: when an office nursing home is occupied by too many low-priority elderly people, a large number of high-priority elderly people must line up or go to the community nursing home. It is obvious that such a low-quality community retirement home cannot completely meet the requirements of high-priority old people. The other is a complete allocation strategy, and the service mode reserves beds of all office nursing homes for the old with high priority and arranges all the old with low priority to the community nursing homes. Unfortunately, when the number of high-priority elderly people is small, a large number of office nursing homes are left idle.
In order to make up for the deficiency of the service strategy in the actual endowment system and reasonably match the limited bed of the endowment hospital and the old people with different health states, the invention designs a brand-new allotment service strategy.
Disclosure of Invention
The technical problem of the invention is solved: the method overcomes the defects of the service technology in the existing endowment system, provides a dynamic allocation optimization strategy, improves the service level in the endowment system, and greatly reduces the service cost.
The technical solution of the invention is as follows: a method for dynamically allocating limited resources for an endowment system is implemented by the following steps as shown in FIG. 1:
step S1, dividing the office nursing home subsidized by the government and the community nursing home created by the private in the nursing system into different service levels according to the professional degree and cost of the service; meanwhile, dividing the old applying for the nursing home into high-priority old and low-priority old according to income, health condition and presence or absence of children, and establishing a limited resource dynamic allocation model;
step S2, calculating the optimal allocation level of the end bed of each period (day, month, year and the like according to the actual situation) of the office nursing home in the nursing system and the number level of the old people served by the community nursing home in each period based on the limited resource dynamic allocation model;
step S3, designing an optimal service strategy for each period in the endowment system according to the optimal distribution level of the end bed of each period of the office endowment hospital and the quantity level of the old people served by the community endowment hospital in each period in the step S2;
and S4, designing a dynamic implementation algorithm to quickly calculate the reservation level of the bed of the office endowment home at each period, the optimal service old man quantity level of the community endowment home at each period and the optimal service cost in the whole endowment system based on the optimal service strategy in the step S3.
In step S1, a dynamic allocation model of the limited resources is established as follows:
for the case of 1, …, period T,
Figure BDA0002858069600000021
wherein,
Figure BDA0002858069600000022
for the period of time T +1,
Figure BDA0002858069600000023
in the above dynamic allocation model for limited resources, the relationship between the number of remaining beds in the nursing home in the t +1 th period and the t th period and the number of the old people queued in the system is a dynamic transfer equation as follows:
Figure BDA0002858069600000024
wherein,
Figure BDA0002858069600000025
is the total service cost of the aging system in the t-th period;
Figure BDA0002858069600000026
expected service cost of the endowment system from the T +1 th period to the T period;
Figure BDA0002858069600000027
is the expected minimum service cost for the aging system from the T-th period to the T-th period; y istIs a decision variable which represents the number of the remaining beds of the office nursing home at the end of the t-th period; v. oftIs a decision variable representing the "net remaining bed volume" of the office at the end of the t-th period, where vt＝yt"total number of unserviced elderly in end-of-term care system at t;
Figure BDA0002858069600000031
is a state vector in the endowment system, where zi,tRepresenting the number of beds left after the complete service of the office nursing home at the end of the t-th period is taken as the aged people from the 1 st to the i th classes of the high-priority aged people; z is a radical of0The number of beds of the initial office nursing home in each period is represented, the low-priority old people are divided into n types according to the waiting time in the queuing system, and the ith type refers to one of the n types;
Figure BDA0002858069600000032
the number of the old people with high priority and low priority who apply for the endowment service at the beginning of the t-th period is represented;
Figure BDA0002858069600000033
is the beginning of period tThe i, i-1, …, n +1 old people apply for the queuing number of the old people in the office nursing home in the nursing system; u. ofiIs the waiting cost of the i-th old man in each period; u shapeiIs the service cost of the i-th class of elderly assigned to the community retirement home; m is the number of office nursing homes; m +1 refers to the community rest home; cjJ is 1, …, m represents the number of beds in the jth office at the beginning of the planning period; h isjRepresents the unit bed holding cost of the jth office rest house; u represents a high priority elderly; g represents a low priority elderly; deltai＝ui-ui+1，i＝1,…,n；△i＝Ui-Ui+1,i＝1,…,n；
Figure BDA0002858069600000034
Is a constant representing the total number of beds from j to m of the office nursing home.
The step S2 is to calculate the number of remaining beds at the end of each period of the office retirement hospital and the number of elderly services per period of the community retirement hospital as follows:
for the office rest home, the rest number of the bed in the rest home at the end of each period is
Figure BDA0002858069600000035
Wherein,
Figure BDA0002858069600000036
is the optimal distribution level of beds of the office nursing home in the t-th period; based on the optimal allocation level, any bed surplus and old people queuing conditions are given to the endowment system at the beginning of each period, and the office endowment house can give a uniquely determined optimal decision scheme;
for the community rest homes, the optimal number of the old people serving the community rest homes at each period is as follows:
Figure BDA0002858069600000037
wherein,
Figure BDA0002858069600000038
is the t-th community cultureOptimal allocation level for the number of elderly in the old home; based on the optimal allotment level, the community rest home can give a uniquely determined optimal decision scheme given any number of queued old people in the end-of-term rest system.
Step S3, designing an optimal service strategy in the endowment system;
for the office rest home, if the total number of the beds available for distribution in the initial office rest home at each period exceeds the distribution level
Figure BDA0002858069600000039
Then the high-priority old people are arranged to enter the home of the office firstly, and then the low-priority old people are arranged to enter the home of the office according to the first-come first-serve rule, so that the number of beds which can be distributed by the home of the office is reduced to be equal to the optimal distribution level
Figure BDA0002858069600000041
For community rest homes, at the end of each period, if the number of the old people queued in the office rest home exceeds the number of the old people queued in the office rest home
Figure BDA0002858069600000042
Then, the old people with low priority are distributed to the resident community nursing home according to the first-come-first-serve rule, and then the old people with high priority are distributed to the resident community nursing home, so that the total number of the old people queued in the nursing system is equal to that of the old people
Figure BDA0002858069600000043
The step S4 is to calculate the optimal service cost per term in the endowment system and to design an implementation algorithm as follows: for the entire planning period T ═ T +1, T-1, …,1,
first, calculate the minimum service cost in the T +1 age-care system
Figure BDA0002858069600000044
As the initial input of the algorithm;
second, calculating the result based on the T +1 periodCalculating the optimal allocation level of the number of the old people in the T-period community nursing home
Figure BDA0002858069600000045
Thirdly, based on the optimal distribution level of the number of the old in the community nursing home
Figure BDA0002858069600000046
Calculating the optimal distribution level of the number of beds in the T-period office nursing home
Figure BDA0002858069600000047
Fourthly, according to the optimal allocation level of the office rest home and the community rest home in each period
Figure BDA0002858069600000048
Calculating the minimum service cost in the aging system in the T period
Figure BDA0002858069600000049
Fifthly, the minimum service cost in the aging system in the T stage
Figure BDA00028580696000000410
As the initial input of the algorithm, the second, third and fourth steps are repeated until the minimum service cost in the 1 st-stage old-age care system is calculated
Figure BDA00028580696000000411
Output the distribution level of the beds of the office nursing home at each period
Figure BDA00028580696000000412
Allocation level of the aged in community nursing home
Figure BDA00028580696000000413
And optimal cost of service per session
Figure BDA00028580696000000414
Compared with the prior art, the invention has the advantages that: the invention solves the problem that the number of beds in the endowment system is not matched with the number of the old people by introducing a dynamic planning model based on the actual condition of the actual endowment system. The optimal reservation level of beds of office nursing homes in the endowment system and the number level of the old people served by the community nursing homes in each period are obtained, the optimal service scheme in the endowment system is provided, finally, the optimal service scheme implementation algorithm is designed, and the optimal service cost in each period in the endowment system is rapidly calculated. Therefore, the service level in the endowment system is improved, the service cost of the endowment system is reduced, and the social welfare is improved.
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FIG. 1 is a flowchart of a method for optimizing dynamic allocation of limited resources in an aging system according to the present invention.
Detailed Description
The present invention will be described in detail below with reference to the accompanying drawings and examples.
The endowment system generally consists of a government-funded office endowment hospital and a private community endowment hospital. For the old, the government-funded office retirement home is better than the privately-created community retirement home in terms of service specialty and economy. Therefore, the present invention first classifies the nursing home into different grades according to the quality of service of the nursing home. Meanwhile, the old people are classified into high priority and low priority according to the conditions of applying for the health status, income, presence or absence of children and the like of the old people, the old people with the high priority have priority service right, and the old people with the low priority can queue in the system.
And then, based on a real service scene, establishing a limited resource dynamic allocation model and calculating the bed level which should be reserved at the end of each period of the office rest home and the number level of the old people which should be served by the community rest home at each period.
Finally, an optimal service strategy for each period in the endowment system is provided, and a dynamic allocation optimization algorithm is designed to quickly calculate the optimal service cost in the endowment system for each period.
In order that the invention may be more readily understood, the invention will now be further described with reference to an example, which is not intended to be limiting.
Suppose the average number of high-priority old people applying for the endowment system at each stage is DU5, average number of low priority aged people DG15 (one day per session). Assuming that 10 office nursing homes are provided, each office nursing home has 20 beds, the low-priority old people have to be served after waiting for 6 times at most in the service system, and the whole planning period is T-12. Other cost parameters are set as follows: cost h for each officej3-0.2(j-1), j-1, … 10; the waiting cost per unit of the old people without service is as follows: u. ofi4-0.3i, i-0, …, n + 1; the unit service cost allocated to the community retirement home is: u shapei0.2(i + n) (n-i +1) +4-0.3 n. The reserved level of the bed of the office nursing home per period obtained in the step S2
Figure BDA0002858069600000051
And the number level of the old people served by the community nursing home at each period
Figure BDA0002858069600000052
And the optimal service plan of the endowment system per term obtained in the step S3, by executing the optimal allocation algorithm in the endowment system designed in the step S4, the following results can be obtained:
table 1: dynamic allocation optimization strategy for limited resources
Figure BDA0002858069600000053
Figure BDA0002858069600000061
QU represents the number of elderly people not served after the service of the office nursing home; the QW indicates the number of old people not served after the service of the office and community nursing homes.
As can be seen from Table 1All the old people arriving at the system can be completely served in the office nursing home in the first 8 th period
Figure BDA0002858069600000062
No elderly people are assigned to the community nursing home. However, since the 9 th day, the bed of the office nursing home cannot satisfy all the old people who newly arrive at the service system. For example, in the ninth phase, 27 beds are left in the office nursing home, 14 of the beds must be reserved for the elderly who may reach high priority in the service system in the future, and 13 elderly who are left after the service in the office nursing home must be allocated to the community nursing home. Therefore, the number of elderly people served in the community nursing home at the 9 th stage is 9.
Finally, in order to more intuitively reveal the reduced service costs and the increased social benefits of the present invention in the endowment system, in the present embodiment, the instances are selected from a certain endowment system. The service conditions adopted by the system for old people in a certain place are as follows:
the system for nursing the aged in a certain place firstly classifies the applied aged into three priority service levels of severe defect, moderate defect and mild defect (severe defect is similar to the high priority and moderate defect and mild defect is similar to the low priority) according to the health condition, income, presence or absence of children and the like of the aged, and each type of aged is distributed to a specific nursing home according to the service rule of first-come first-served. If the beds of a certain type of nursing home are allocated, the elderly must queue up in the corresponding service queue. The data shows that there are serious service consequences for both the prior-to-first-serve and full provisioning policies. Therefore, the invention adopts the actual data of the aging system in a certain place to prove the value of the invention. In a certain place, each home of nursing home has 90 beds on average, the number of old people with severe defect in the nursing system is 15 people on average every day, and the number of old people with mild defect is 30 people. The embodiment of the invention selects the relative average service cost in the whole planning period as a measurement index:
Figure BDA0002858069600000063
where P is ∈ { N, F }. C (N), C (F) respectively represent first come first serve strategy and completeAverage service cost of provisioning policies; c (T) represents the average service cost of the dynamic provisioning service policy. By performing the results described in claim 1, the following table is obtained:
TABLE 2 relative average service cost
Figure BDA0002858069600000064
Figure BDA0002858069600000071
Note:
Figure BDA0002858069600000072
the proportion of the severely defected old people to the slightly defected old people in the nursing home applied at each period is shown.
As can be seen from table 2, the dynamic provisioning optimization strategy proposed by the present invention performs better than the first-come-first-served strategy and the full provisioning strategy in real-world applications. Greatly reducing the service cost and improving the social welfare.
While the foregoing is directed to embodiments of the present invention, other and further embodiments of the invention may be devised without departing from the basic scope thereof, and the scope thereof is determined by the claims that follow.

Claims (5)

1. A method for dynamically allocating limited resources for an aging system, comprising the steps of:
step S1, dividing the office nursing home subsidized by the government and the community nursing home created by the private in the nursing system into different service levels according to the professional degree and cost of the service; meanwhile, dividing the old applying for the nursing home into high-priority old and low-priority old according to income, health condition and presence or absence of children, and establishing a limited resource dynamic allocation model;
step S2, calculating the optimal distribution level of the end bed of each period of the office nursing home in the nursing system and the quantity level of the old people served by the community nursing home in each period based on the limited resource dynamic distribution model;
step S3, designing an optimal service strategy for each period in the endowment system according to the optimal distribution level of the end bed of each period of the office endowment hospital and the quantity level of the old people served by the community endowment hospital in each period in the step S2;
and S4, designing a dynamic implementation algorithm to quickly calculate the reservation level of the bed of the office endowment home at each period, the optimal service old man quantity level of the community endowment home at each period and the optimal service cost in the whole endowment system based on the optimal service strategy in the step S3.
2. The method of claim 1, wherein the method comprises: in step S1, a dynamic allocation model of the limited resources is established as follows:
for the case of 1, …, period T,
Figure FDA0002858069590000011
wherein,
Figure FDA0002858069590000012
for the period of time T +1,
Figure FDA0002858069590000013
in the above dynamic allocation model for limited resources, the relationship between the number of remaining beds in the nursing home in the t +1 th period and the t th period and the number of the old people queued in the system is a dynamic transfer equation as follows:
Figure FDA0002858069590000014
wherein,
Figure FDA0002858069590000015
is the total service cost of the aging system in the t-th period;
Figure FDA0002858069590000016
expected service cost of the endowment system from the T +1 th period to the T period;
Figure FDA0002858069590000017
is the expected minimum service cost for the aging system from the T-th period to the T-th period; y istIs a decision variable which represents the number of the remaining beds of the office nursing home at the end of the t-th period; v. oftIs a decision variable representing the "net remaining bed volume" of the office at the end of the t-th period, where vt＝yt"total number of unserviced elderly in end-of-term care system at t;
Figure FDA0002858069590000021
is a state vector in the endowment system, where zi,tRepresenting the number of beds left after the complete service of the office nursing home at the end of the t-th period is taken as the aged people from the 1 st to the i th classes of the high-priority aged people; z is a radical of0The number of beds of the initial office nursing home in each period is represented, the low-priority old people are divided into n types according to the waiting time in the queuing system, and the ith type refers to one of the n types;
Figure FDA0002858069590000022
the number of the old people with high priority and low priority who apply for the endowment service at the beginning of the t-th period is represented;
Figure FDA0002858069590000023
the number of queuing of the aged people in the office nursing home is applied by the i-th, i-1, …, n +1 aged people in the beginning of the period t; u. ofiIs the i-th agedWaiting for the cost; u shapeiIs the service cost of the i-th class of elderly assigned to the community retirement home; m is the number of office nursing homes; m +1 refers to the community rest home;
Figure FDA0002858069590000024
representing the number of beds in the jth office nursing home at the beginning of the planning period; h isjRepresents the unit bed holding cost of the jth office rest house; u represents a high priority elderly; g represents a low priority elderly; deltai＝ui-ui+1，i＝1,…,n；△i＝Ui-Ui+1,i＝1,…,n；
Figure FDA0002858069590000025
Is a constant representing the total number of beds from j to m of the office nursing home.
3. The method of claim 1, wherein the method comprises: the step S2 is to calculate the number of remaining beds at the end of each period of the office retirement hospital and the number of elderly services per period of the community retirement hospital as follows:
for the office rest home, the rest number of the bed in the rest home at the end of each period is
Figure FDA0002858069590000026
Wherein,
Figure FDA0002858069590000027
is the optimal distribution level of beds of the office nursing home in the t-th period; based on the optimal allocation level, any bed surplus and old people queuing conditions are given to the endowment system at the beginning of each period, and the office endowment house can give a uniquely determined optimal decision scheme;
for the community rest homes, the optimal number of the old people serving the community rest homes at each period is as follows:
Figure FDA0002858069590000028
wherein,
Figure FDA0002858069590000029
the optimal allocation level of the number of the old people in the t-th community nursing home; based on the optimal allotment level, the community rest home can give a uniquely determined optimal decision scheme given any number of queued old people in the end-of-term rest system.
4. The method of claim 1, wherein the method comprises: step S3, designing an optimal service strategy in the endowment system;
for the office rest home, if the total number of the beds available for distribution in the initial office rest home at each period exceeds the distribution level
Figure FDA0002858069590000031
Then the high-priority old people are arranged to enter the home of the office firstly, and then the low-priority old people are arranged to enter the home of the office according to the first-come first-serve rule, so that the number of beds which can be distributed by the home of the office is reduced to be equal to the optimal distribution level
Figure FDA0002858069590000032
For community rest homes, at the end of each period, if the number of the old people queued in the office rest home exceeds the number of the old people queued in the office rest home
Figure FDA0002858069590000033
Then, the old people with low priority are distributed to the resident community nursing home according to the first-come-first-serve rule, and then the old people with high priority are distributed to the resident community nursing home, so that the total number of the old people queued in the nursing system is equal to that of the old people
Figure FDA0002858069590000034
5. The method of claim 1, wherein the method comprises: the step S4 is to calculate the optimal service cost per term in the endowment system and to design an implementation algorithm as follows:
for the entire planning period T ═ T +1, T-1, …,1,
first, calculate the minimum service cost in the T +1 age-care system
Figure FDA0002858069590000035
As the initial input of the algorithm;
secondly, calculating the optimal allocation level of the number of the old people in the community nursing home in the T period based on the calculation result of the T +1 period
Figure FDA0002858069590000036
Thirdly, based on the optimal distribution level of the number of the old in the community nursing home
Figure FDA0002858069590000037
Calculating the optimal distribution level of the number of beds in the T-period office nursing home
Figure FDA0002858069590000038
Fourthly, according to the optimal allocation level of the office rest home and the community rest home in each period
Figure FDA0002858069590000039
Calculating the minimum service cost in the aging system in the T period
Figure FDA00028580695900000310
Fifthly, the minimum service cost in the aging system in the T stage
Figure FDA00028580695900000311
As the initial input of the algorithm, repeat the second, third, fourth, fifth, sixth, seventh, eighth, ninth, tenth, and ninth,Four steps, until the minimum service cost in the 1 st stage old-age care system is calculated
Figure FDA00028580695900000312
Output the distribution level of the beds of the office nursing home at each period
Figure FDA00028580695900000313
Allocation level of the aged in community nursing home
Figure FDA00028580695900000314
And optimal cost of service per session
Figure FDA00028580695900000315
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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113723877A (en) * 2021-08-18 2021-11-30 中国科学技术大学 Inventory decision method and system based on second-order function decomposition method

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6333926B1 (en) * 1998-08-11 2001-12-25 Nortel Networks Limited Multiple user CDMA basestation modem
JP2001357128A (en) * 2000-06-13 2001-12-26 Sanyo Electric Co Ltd Residence fee estimation system for ray nursing home for the aged
CN104508634A (en) * 2012-06-29 2015-04-08 博科通迅系统有限公司 Dynamic resource allocation for virtual machines
CN111080006A (en) * 2019-12-13 2020-04-28 河海大学常州校区 Community home care service scheduling model and solving method
CN111242820A (en) * 2018-11-28 2020-06-05 苏州市铼康护养老护理有限公司 Intelligent home-based care service system

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6333926B1 (en) * 1998-08-11 2001-12-25 Nortel Networks Limited Multiple user CDMA basestation modem
JP2001357128A (en) * 2000-06-13 2001-12-26 Sanyo Electric Co Ltd Residence fee estimation system for ray nursing home for the aged
CN104508634A (en) * 2012-06-29 2015-04-08 博科通迅系统有限公司 Dynamic resource allocation for virtual machines
CN111242820A (en) * 2018-11-28 2020-06-05 苏州市铼康护养老护理有限公司 Intelligent home-based care service system
CN111080006A (en) * 2019-12-13 2020-04-28 河海大学常州校区 Community home care service scheduling model and solving method

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
SHIJIN WANG; SHUAN MA; BIN LI; XUE LI: "A bi-objective model for nursing home location and allocation problem", IEEE *
沈婉婉;鲍勇;: "上海市养老机构"医养结合"优化模式及对策研究", 中华全科医学, no. 06 *
谭成兵;詹林;方晓;: "基于动态性有效资源分配的云计算效益学习模型研究", 计算机测量与控制, no. 04 *

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113723877A (en) * 2021-08-18 2021-11-30 中国科学技术大学 Inventory decision method and system based on second-order function decomposition method
CN113723877B (en) * 2021-08-18 2023-11-17 中国科学技术大学 Inventory decision method and system based on second-order function decomposition method

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