CN116307054B - Intelligent office configuration method based on greedy algorithm - Google Patents
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Abstract
The invention provides an intelligent office configuration method based on a greedy algorithm, and belongs to the technical field of resource configuration; the configuration method comprises the following steps: data preprocessing, room allocation and adjustment after allocation; in the data preprocessing stage, the number and area requirements of various rooms are calculated; in the room allocation stage, the requirements of hard constraint are met, and meanwhile, the requirements of soft constraint are met as much as possible, so that a primary configuration scheme of the office room is generated; the adjustment stage after distribution, optimally adjusting the distribution of the service rooms and other rooms, generating an optimal configuration scheme of the office rooms, and giving scheme scores; aiming at the business scene of using the office in the application of the lower level unit, the invention forms a corresponding room allocation plan according to the related requirements of the unit and the idle office information in the system; compared with the manual flow, the method is faster, more reasonable and more accurate, has lower cost and unified standard, and is more suitable for standard management.
Description
Technical Field
The invention belongs to the technical field of resource allocation, and particularly relates to an intelligent office allocation method based on a greedy algorithm.
Background
Among the many directions of digital construction, there is still a fresh interest of researchers for digital construction of unit property distribution. Traditional office allocation is mainly performed manually, and a series of problems exist: firstly, aiming at large concentrated courtyards, lack of accurate analysis on conditions such as requirements of using units, personnel establishment, positions and the like; based on the manually recorded list and drawings, the method is neither intuitive nor convenient, and technical errors are easy to occur. Secondly, the overall arrangement of units to be distributed needs to be performed in advance by one to two years, and then multiparty negotiation, modification and optimization are performed according to the formulated initial scheme to determine the final allocation scheme, and the complete period may be as long as two to three years. Thirdly, the unified template standard for data compilation is lacking, and the upper level is difficult to monitor and manage the service execution process in time. In general, the limitations of the traditional manual distribution approach are: the real estate allocation is unreasonable, the resource utilization rate is low, more waste exists, the data collection period is long, the data is not visual, the standards are not uniform, and the like, and more importantly, a long-acting office management mechanism cannot be established.
To solve this problem, a real estate management system has been developed. It is desirable to conduct closed-loop management of the full life cycle of a property resource by establishing a full business, full flow property management system. Each business and each flow are all incorporated into a digital and intelligent information platform, so that the transparency of the house property information can be realized, and the management is convenient and standardized; the method is beneficial to graded utilization, classified utilization and intelligent distribution; unified maintenance, unified approval and unified supervision are realized; the purpose of reasonable allocation and utilization of the house property resources is achieved. The key and difficult points are how to realize intelligent distribution. A system for comprehensively planning the resources of a plurality of units of houses, when distributing the resources to a plurality of units of personnel, the priority of the same building, the same floor and continuous rooms of the same unit is considered; the personnel distribution area approaches the room area as much as possible; the area allocated for various kinds of rooms approaches the required area, etc.
Based on the technical problems, the invention provides a method and a system for intelligent office configuration based on a greedy algorithm in combination with requirements and characteristics of intelligent office configuration.
Disclosure of Invention
The invention aims to at least solve one of the technical problems in the prior art and provides an intelligent office configuration method based on a greedy algorithm.
The invention comprises three stages: a data preprocessing stage, a room allocation stage and a post-allocation adjustment stage;
the data preprocessing stage is used for calculating the quantity and the area requirement of various rooms;
in the room allocation stage, the requirements of hard constraint are met, and meanwhile, the requirements of soft constraint are met as much as possible, so that a preliminary allocation scheme of the office room is generated;
the post-allocation adjustment stage optimizes and adjusts the distribution of the service rooms and other rooms, generates an optimal configuration scheme of the office rooms, and gives scheme scores;
optionally, in the data preprocessing stage, calculating the number and the area requirements of various rooms, including:
parameters input during calculation include: the compiling information of each unit to be distributed and the personnel thereof, and the office building available for distribution and all room information not distributed;
the input parameters must meet various requirements in office room management system;
optionally, the room allocation stage includes:
sequencing the unit data according to the number of codes and the number of the unit data, transmitting the unit data and office building information and room information into a greedy algorithm interface at the same time, and then generating a preliminary configuration scheme of the office according to greedy algorithm operation;
the greedy algorithm comprises:
A. calculating the area of each floor of each building, only considering cross-floor and single-layer distribution, and preferentially considering single-layer distribution, and not considering cross-building distribution of the same unit; setting a demand meeting coefficient of 0.8, and directly ending the flow when the data is not met;
B. matching the distribution requirement of the first unit with the area data of each layer calculated in the step A, and starting to enter the distribution step C when a single layer accords with the area and the area is closest to the single layer; if the single-layer data do not meet the requirement of multiplying the demand by the coefficient, combining adjacent floors, and extracting all unassigned rooms in the nearest combined result to enter an allocation step C;
C. marking the single room characteristics according to the single unit number requirements and the area upper limit of the office, and if the single room characteristics are not met, reducing the minimum single unit area requirements to recursively search until the single unit number is met; then directly entering a distribution step, firstly distributing the single rooms, then distributing the single rooms according to the requirements of the areas of the remaining various rooms in a one-to-one ordering mode according to the room numbers until the distribution is completed, wherein the upper limit of the required area is not exceeded but more than 75% of the required area is required, and the purposes of the rooms are simultaneously set during the distribution, such as: office, service rooms, etc.;
D. after one-time distribution, recalculating the area information which can be distributed in the step A, transmitting the area information and the next unit demand data into the step B, and circulating the steps until the room division of all units is completed;
optionally, the hard constraint requirement includes:
A. office: the standard of the using area needs to be met, and personnel in the room verify that the sum of the using areas is larger than or equal to the using area of the room;
B. service house: the area standard of each unit needs to be met, wherein the area standard is determined according to the verification level of a three-level scheme in the unit and the number of people;
C. equipment house and accessory house: the method comprises the steps that pre-screening is carried out according to whether equipment rooms and auxiliary rooms exist on a building and floors, the floors which do not exist are filtered, meanwhile, the standard of unit building area is required to be met, and the method is determined according to the check-up level and the number of people of a triple scheme in a unit;
D. high-order big workshops: defining a single room according to an area standard with the largest fixed area of the unit kernel;
optionally, the soft constraint requirement includes:
A. dining: whether a canteen exists or not is used as an advanced screening option;
B. traffic: the distance is as close as possible to the distance of the main pipe unit or the designated longitude and latitude;
C. parking requirements: whether the parking space is saturated;
D. the room floors are relatively concentrated;
E. the room numbers are connected as much as possible;
F. aiming at a certain building, the rooms are fully arranged as much as possible;
G. floor division point: the stair or the elevator is used as a boundary, a floor is divided into two or more relatively complete space units, when a basic office room is allocated, if a small number of rooms need to be allocated across the space units, the matching degree of factors such as office rooms/service rooms/single rooms/room orientations can be properly reduced, and the same unit is allocated in the same space unit as much as possible;
H. layer height: the method comprises the steps of limiting the layer height aiming at some service halls, and meeting the requirements of window halls;
optionally, the post-allocation adjustment stage includes:
the service rooms are required to be relatively uniformly distributed in the rooms allocated by the units, the rooms are divided into intervals according to the ratio of the service rooms to the total room number, the room area and the service room area are searched, and if the difference is closest to or lower than 20%, the two uses are exchanged;
after adjustment, generating an optimal configuration scheme of the office;
optionally, the solution score includes:
firstly, calculating the matching rate of various house types, and then taking an average value as the final total score of the scheme; the specific calculation formula is as follows:
total score = (office match + service room match + equipment room match + meal match + single inter-optimizing allocation + parking space match + main unit approach + house orientation match)/8
The invention provides a greedy algorithm-based intelligent office configuration method and system. Aiming at the business scene of using the office in the application of the lower level unit, the invention forms a corresponding room allocation plan according to the related requirements of the unit and the idle office information in the system; compared with the manual house selection, comparison and distribution processes, the configuration method is faster, more reasonable and more accurate, and has lower cost.
Drawings
FIG. 1 is a basic flow diagram of a greedy algorithm-based intelligent office configuration method according to an embodiment of the present invention;
FIG. 2 is a detailed flow chart of a greedy algorithm-based intelligent office configuration method according to an embodiment of the invention;
Detailed Description
The present invention will be described in further detail below with reference to the drawings and detailed description for the purpose of better understanding of the technical solution of the present invention to those skilled in the art. It will be apparent that the described embodiments are some, but not all, embodiments of the invention. All other embodiments, which can be made by a person skilled in the art without creative efforts, based on the described embodiments of the present invention belong to the protection scope of the present invention.
Unless specifically stated otherwise, technical or scientific terms used herein should be defined in the general sense as understood by one of ordinary skill in the art to which this invention belongs. The use of "including" or "comprising" and the like in the present invention is not intended to limit the shape, number, step, action, operation, component, original and/or group thereof referred to, nor exclude the presence or addition of one or more other different shapes, numbers, steps, actions, operations, components, original and/or group thereof. Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or order of the indicated features.
As shown in fig. 1 and 2, the invention provides a greedy algorithm-based intelligent office configuration method S200, which specifically includes steps S210 to S230:
s210, a data preprocessing stage.
Specifically, the number and area requirements of various types of rooms are calculated.
In the actual application process, the parameters input during calculation include: the organization information of each unit to be allocated and its personnel, and the office building available for allocation and all room information not allocated.
Furthermore, the input parameters must meet the requirements of the office management system.
S220, room allocation stage.
Specifically, while the requirement of hard constraint is met, the requirement of soft constraint is met as much as possible, and a preliminary configuration scheme of the office is generated.
In the practical application process, the unit data is required to be sequenced according to the number of the codes and the quantity of the unit data is priority, and the unit data and office building information and room information are simultaneously transmitted into a greedy algorithm interface, and then a preliminary configuration scheme of the office is generated according to greedy algorithm operation.
It should be noted that, in the practical application process, the greedy algorithm of the present invention includes:
A. calculating the area of each floor of each building, only considering cross-floor and single-layer distribution, and preferentially considering single-layer distribution, and not considering cross-building distribution of the same unit; setting a demand meeting coefficient of 0.8, and directly ending the flow when the data is not met;
B. matching the distribution requirement of the first unit with the area data of each layer calculated in the step A, and starting to enter the distribution step C when a single layer accords with the area and the area is closest to the single layer; if the single-layer data do not meet the requirement of multiplying the demand by the coefficient, combining adjacent floors, and extracting all unassigned rooms in the nearest combined result to enter an allocation step C;
C. marking the single room characteristics according to the single unit number requirements and the area upper limit of the office, and if the single room characteristics are not met, reducing the minimum single unit area requirements to recursively search until the single unit number is met; then directly entering a distribution step, firstly distributing the single rooms, then distributing the single rooms according to the requirements of the areas of the remaining various rooms in a one-to-one ordering mode according to the room numbers until the distribution is completed, wherein the upper limit of the required area is not exceeded but more than 75% of the required area is required, and the purposes of the rooms are simultaneously set during the distribution, such as: office, service rooms, etc.;
D. after one-time distribution, recalculating the area information which can be distributed in the step A, transmitting the area information and the next unit demand data into the step B, and circulating the steps until the room division of all units is completed;
it should be noted that, in the practical application process, the hard constraint requirements of the present invention include:
A. office: the standard of the using area needs to be met, and personnel in the room verify that the sum of the using areas is larger than or equal to the using area of the room;
B. service house: the area standard of each unit needs to be met, wherein the area standard is determined according to the verification level of a three-level scheme in the unit and the number of people;
C. equipment house and accessory house: the method comprises the steps that pre-screening is carried out according to whether equipment rooms and auxiliary rooms exist on a building and floors, the floors which do not exist are filtered, meanwhile, the standard of unit building area is required to be met, and the method is determined according to the check-up level and the number of people of a triple scheme in a unit;
D. high-order big workshops: the unit cell is defined according to the area standard of the unit core with the largest fixed area.
It should be noted that, in the practical application process, the soft constraint requirements of the present invention include:
A. dining: whether a canteen exists or not is used as an advanced screening option;
B. traffic: the distance is as close as possible to the distance of the main pipe unit or the designated longitude and latitude;
C. parking requirements: whether the parking space is saturated;
D. the room floors are relatively concentrated;
E. the room numbers are connected as much as possible;
F. aiming at a certain building, the rooms are fully arranged as much as possible;
G. floor division point: the stair or the elevator is used as a boundary, a floor is divided into two or more relatively complete space units, when a basic office room is allocated, if a small number of rooms need to be allocated across the space units, the matching degree of factors such as office rooms/service rooms/single rooms/room orientations can be properly reduced, and the same unit is allocated in the same space unit as much as possible;
H. layer height: the method comprises the steps of limiting the layer height aiming at some service halls, and meeting the requirements of window halls;
s230, an adjustment stage after distribution.
Specifically, the distribution of the service rooms and other rooms is optimized and adjusted, an optimal configuration scheme of the office rooms is generated, and scheme scores are given.
In the practical application process, the service rooms are required to be relatively uniformly distributed in the rooms allocated by the units, the rooms are divided into intervals according to the ratio of the service rooms to the total room number, the room area and the service room area are searched, and if the difference is closest to or lower than 20%, the two purposes are exchanged.
After adjustment, generating an optimal configuration scheme of the office;
furthermore, when calculating the output scheme score, the invention firstly calculates the matching rate of various house types, and then takes the average value as the final total score of the scheme; the specific calculation formula is as follows:
total score = (office match + service room match + equipment room match + meal match + single inter-optimizing allocation + parking space match + main unit approach + house orientation match)/8
The intelligent configuration method of the office based on the greedy algorithm is further described below with reference to the specific embodiment:
example 1
The example illustrates a greedy algorithm-based intelligent office configuration method, which comprises the following steps:
s1, calculating the number and area requirements of various rooms;
s2, calculating the area of each floor of each building, setting a demand meeting coefficient of 0.8, and directly ending the flow when the data are not met;
s3, matching the distribution requirement of the first unit with the area data of each layer calculated in the step S2;
s4, if the single layers are consistent and the areas are closest, starting to enter a distribution step S5; if the single-layer data do not meet the requirement of multiplying the demand by the coefficient, combining adjacent floors, and extracting all unassigned rooms in the nearest combined result to enter an allocation step S5;
s5, setting the upper limit of the area of the office according to the unit single-room number requirement and the programming, marking the single-room characteristics of the room, and if the single-room characteristics are not met, reducing the minimum single-room area requirement to recursively search until the single-room number is met;
s6, distributing the single rooms well, and then distributing the single rooms in a one-to-one sequence according to the area requirements of the remaining various rooms until the distribution is completed;
s7, recalculating the distributable area information in the step S1 after one-time distribution, transmitting the distributable area information and the next unit demand data to the step S2, and circulating the steps until all units are separated to generate a primary configuration scheme of the office;
s8, optimizing and adjusting the distribution of the service rooms and other rooms, generating an optimal configuration scheme of the office rooms, and giving scheme scores.
The invention provides a greedy algorithm-based intelligent office configuration method and system, which have the following beneficial effects:
under the condition of combining all constraint conditions, the method provided by the invention not only can meet the hard constraint of offices, service rooms, equipment rooms, high-level large units and the like, but also has higher matching degree in the aspect of soft constraint.
Secondly, compared with the manual room selection, comparison and distribution processes, the room distribution method provided by the invention can realize a room distribution scheme which is faster, more reasonable, more accurate and lower in cost.
It is to be understood that the above embodiments are merely illustrative of the application of the principles of the present invention, but not in limitation thereof. Various modifications and improvements may be made by those skilled in the art without departing from the spirit and substance of the invention, and are also considered to be within the scope of the invention.
Claims (6)
1. The intelligent office configuration method based on the greedy algorithm is characterized by comprising three stages: a data preprocessing stage, a room allocation stage and a post-allocation adjustment stage;
the data preprocessing stage is used for calculating the quantity and the area requirement of various rooms;
in the room allocation stage, the requirements of hard constraint are met, and meanwhile, the requirements of soft constraint are met as much as possible, so that a preliminary allocation scheme of the office room is generated;
the post-allocation adjustment stage optimizes and adjusts the distribution of the service rooms and other rooms, generates an optimal configuration scheme of the office rooms, and gives scheme scores;
wherein the room allocation phase comprises: sequencing the unit data according to the number of codes and the number of the unit data, transmitting the unit data and office building information and room information into a greedy algorithm interface at the same time, and then generating a preliminary configuration scheme of the office according to greedy algorithm operation; the greedy algorithm comprises:
A. calculating the area of each floor of each building, only considering cross-floor and single-layer distribution, and preferentially considering single-layer distribution, and not considering cross-building distribution of the same unit; setting a demand meeting coefficient of 0.8, and directly ending the flow when the data is not met;
B. matching the distribution requirement of the first unit with the area data of each layer calculated in the step A, and starting to enter the distribution step C when a single layer accords with the area and the area is closest to the single layer; if the single-layer data do not meet the requirement of multiplying the demand by the coefficient, combining adjacent floors, and extracting all unassigned rooms in the nearest combined result to enter an allocation step C;
C. marking the single room characteristics according to the single unit number requirements and the area upper limit of the office, and if the single room characteristics are not met, reducing the minimum single unit area requirements to recursively search until the single unit number is met; then directly entering a distribution step, firstly distributing the single rooms, then distributing the single rooms according to the requirements of the areas of the rest various rooms in a one-to-one sequence according to the room numbers until the distribution is completed, wherein the upper limit of the required area is not exceeded but more than 75% of the required area is required, and the purposes of the rooms, including offices and service rooms, are set during the distribution;
D. after one-time distribution, recalculating the area information which can be distributed in the step A, transmitting the area information and the next unit demand data into the step B, and circulating the steps until the room division of all units is completed;
the demand meeting coefficient is an interval coefficient of room area distribution, and the room area which can be distributed by meeting the demand meeting coefficient of 0.8 is 0.8 to 1.0 times of a standard value.
2. The intelligent configuration method of office rooms based on greedy algorithm according to claim 1, wherein the data preprocessing stage calculates the number and area requirements of various kinds of rooms, and the method comprises the following steps:
parameters input during calculation include: the organization information of each unit to be allocated and its personnel, and the office building available for allocation and all room information not allocated.
3. The greedy algorithm-based intelligent office configuration method according to claim 1, wherein the hard constraint requirements include:
A. office: the standard of the using area needs to be met, and personnel in the room verify that the sum of the using areas is larger than or equal to the using area of the room;
B. service house: the area standard of each unit needs to be met, wherein the area standard is determined according to the verification level of a three-level scheme in the unit and the number of people;
C. equipment house and accessory house: the method comprises the steps that pre-screening is carried out according to whether equipment rooms and auxiliary rooms exist on a building and floors, the floors which do not exist are filtered, meanwhile, the standard of unit building area is required to be met, and the method is determined according to the check-up level and the number of people of a triple scheme in a unit;
D. high-order big workshops: the unit cell is defined according to the area standard of the unit core with the largest fixed area.
4. The greedy algorithm-based intelligent office configuration method according to claim 1, wherein the soft constraint requirements include:
A. dining: whether a canteen exists or not is used as an advanced screening option;
B. traffic: the distance is as close as possible to the distance of the main pipe unit or the designated longitude and latitude;
C. parking requirements: whether the parking space is saturated;
D. the room floors are relatively concentrated;
E. the room numbers are connected as much as possible;
F. aiming at a certain building, the rooms are fully arranged as much as possible;
G. floor division point: dividing a floor into two or more relatively complete space units by taking stairs or elevators as boundaries, and if a small number of rooms need to be distributed across the space units when basic office rooms are distributed, properly reducing the matching degree of office/service rooms/single rooms/room orientation factors and distributing the same units in the same space units as much as possible;
H. layer height: and the floor height limitation is carried out on some service halls, so that the requirements of the window halls are met.
5. The greedy algorithm-based intelligent office configuration method according to claim 1, wherein the post-allocation adjustment phase comprises:
the service rooms are required to be relatively uniformly distributed in the rooms allocated by the units, the rooms are divided into intervals according to the ratio of the service rooms to the total room number, the room area and the service room area are searched, and if the difference is closest to or lower than 20%, the two uses are exchanged;
after adjustment, an optimal configuration scheme for the office is generated.
6. The greedy algorithm-based intelligent office configuration method according to claim 1, wherein the solution score comprises:
firstly, calculating the matching rate of various house types, and then taking an average value as the final total score of the scheme; the specific calculation formula is as follows:
total score = (office match + service room match + equipment room match + meal match + single inter-optimizing allocation + parking space match + main unit proximity + house orientation match)/8.
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