CN110610319A - Intelligent scheduling system and method based on gas station user classification guidance - Google Patents
Intelligent scheduling system and method based on gas station user classification guidance Download PDFInfo
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06312—Adjustment or analysis of established resource schedule, e.g. resource or task levelling, or dynamic rescheduling
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06316—Sequencing of tasks or work
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/06—Electricity, gas or water supply
Abstract
The invention relates to the technical field of intelligent scheduling, in particular to an intelligent scheduling system and method based on gas station user classification guidance, wherein the system is based on the method and comprises a server, and the server comprises the following modules: the system comprises a traffic flow information acquisition module, a traffic flow estimation module, a people/work hour estimation module and a schedule generation module. The invention solves the problem of poor flexibility of the scheduling mode of the gas station.
Description
Technical Field
The invention relates to the technical field of intelligent scheduling, in particular to an intelligent scheduling system and method based on gas station user classification guidance.
Background
With the rapid development of national economy, continuous improvement of traffic infrastructure and rapid increase of motor vehicle reserves, gas stations have become an indispensable part of people's lives. At present, vehicles in various industries need to be refueled at a gas station, wherein the time for refueling private vehicles on weekdays is relatively concentrated on working hours or working hours, the refueling and gas filling time of taxies is relatively concentrated on noon, the refueling time of other vehicles is relatively discrete, the refueling time of the vehicles has a certain valley rate on the whole, but the refueling time is also discretely changed on the whole in consideration of the interference of various factors.
According to the current scheduling mechanism of the gas station, the staff of the gas station is easy to have insufficient hands and work busy in the vehicle refueling peak. In the filling valley period of the filling station, the number of the personnel is large, the workload is less, and the manpower resource is large and wasted. At present, the gas station generally performs work arrangement in a two-shift mode, and when a person in charge of the gas station performs personnel shift arrangement, vehicle refueling peaks and valleys become a critical problem. In addition, for reasonable scheduling, personnel changes, rest, leave, etc. need to be considered. This is a large workload if the shift is done by all the responsible staff. At present, the scheduling mode of the conventional scheduling system is relatively fixed and single, and in the face of discretely-changed vehicle refueling time, the flexibility of the single scheduling mode is poor, and the working efficiency of staff cannot be guaranteed.
Disclosure of Invention
One of the main purposes of the invention is to provide an intelligent scheduling system based on the classification guidance of a gas station user, which solves the problem of poor flexibility of a scheduling mode of the gas station.
In order to achieve the purpose, the invention provides an intelligent scheduling system based on gas station user classification guidance, which comprises a server, wherein the server comprises the following modules:
the traffic flow information acquisition module is used for acquiring the characteristic information of the vehicles, classifying the vehicles according to the characteristic information, setting a statistical time node of the traffic flow, and statistically analyzing the classification types and the number of the vehicles according to the statistical time node to generate and store traffic flow data;
the traffic flow estimation module is used for reading the historical data of the traffic flow data and estimating the traffic flow data on the preset day according to the historical data;
the number of people/man-hour estimation module is used for analyzing estimated number of people data and estimated man-hour data required by each post of the gas station according to the traffic flow data of the preset day;
and the scheduling list generation module is used for setting a scheduling template and generating a scheduling list according to the estimated times data and the estimated working hour data required by each post.
The working principle and the advantages of the invention are as follows:
1. the arrangement of the traffic flow information acquisition module and the traffic flow estimation module can facilitate the classification of vehicles according to the characteristic information of the vehicles, so as to obtain traffic flow data. Since the traffic data is regularly cyclable over a certain period. Therefore, historical data of the traffic flow data are used as reference data to estimate the traffic flow data on the preset day, data support is provided for reasonable scheduling of personnel, and work efficiency is guaranteed.
2. The arrangement of the number of people/working hour pre-estimation module and the scheduling table generation module can reasonably arrange the scheduling of the staff according to traffic flow data and staff, posts and formulas of the gas station, so that the scheduling mode has good flexibility and the working efficiency can be guaranteed.
Further, the scheduling list generation module further comprises the following modules:
the personnel information storage module is used for storing information of personnel to be scheduled; the information of the staff to be scheduled comprises staff names and staff numbers;
and the post information storage module is used for storing the post information to be scheduled.
The generation of the scheduling list is convenient, and each worker and each work post can be reasonably arranged.
Further, the traffic flow estimation module comprises the following modules:
and the historical data storage module is used for storing the historical data of the traffic flow data and storing a scheduling list corresponding to the traffic flow data.
By storing the historical data of the traffic flow data, the schedule generated in the later period is convenient to refer.
Further, the system also comprises the following modules:
the system comprises a leave asking management module, a leave asking management module and a shift scheduling module, wherein the leave asking management module is used for receiving leave asking requests of shift scheduling personnel in a waiting shift scheduling period, analyzing whether the shift scheduling period is crossed or not when a plurality of leave asking requests exist, and acquiring shift scheduling requests to be scheduled from the shift scheduling personnel and performing shift scheduling if the shift scheduling period is crossed; and if no crossover exists, the waiting scheduling time interval of the scheduling staff who asks for is exchanged for scheduling.
The change of personnel such as the person's the time of a rest, ask for leave can carry out nimble arrangement, avoids work conflict to appear, reduces work efficiency.
Further, the leave asking management module further comprises the following modules:
and the final scheduling list generating module is used for performing scheduling according to a preset scheduling rule after generating the scheduling list and when receiving a scheduling request of a scheduled person, replacing the scheduled person with the scheduled person, and generating the final scheduling list.
The final scheduling list has flexibility, and work efficiency is guaranteed.
The invention also provides an intelligent scheduling method based on the classification guidance of the users of the gas station, and the system based on the method comprises the following steps:
a traffic flow information obtaining step, namely obtaining the characteristic information of the vehicles, classifying the vehicles according to the characteristic information, setting a statistical time node of the traffic flow, and statistically analyzing the classification types and the number of the vehicles according to the statistical time node to generate and store traffic flow data;
a traffic flow estimation step, namely reading historical data of traffic flow data and estimating the traffic flow data on a preset day according to the historical data;
estimating the number of people/working hours, namely analyzing estimated number of people data and estimated working hour data required by each post of the gas station according to traffic flow data of a preset day;
and a scheduling table generation step, namely setting a scheduling template, and generating the scheduling table according to the estimated times data and the estimated working hour data required by each post.
The working principle and the advantages of the invention are as follows:
1. the arrangement of the traffic flow information acquisition step and the traffic flow estimation step can facilitate the classification of the vehicles according to the characteristic information of the vehicles, thereby obtaining the traffic flow data. Since the traffic data is regularly cyclable over a certain period. Therefore, historical data of the traffic flow data are used as reference data to estimate the traffic flow data on the preset day, data support is provided for reasonable scheduling of personnel, and work efficiency is guaranteed.
2. The arrangement of the personnel/working hour pre-estimation step and the scheduling list generation step can reasonably arrange the scheduling of the staff according to the traffic flow data and the staff, the post and the formula of the gas station, so that the scheduling mode has good flexibility and the working efficiency can be guaranteed.
Further, the step of generating the shift schedule further comprises the following steps:
a personnel information storage step, in which the information of personnel to be scheduled is stored; the information of the staff to be scheduled comprises staff names and staff numbers;
and a post information storage step, in which the post information to be scheduled is stored.
The generation of the scheduling list is convenient, and each worker and each work post can be reasonably arranged.
Further, the traffic flow estimation step comprises the following steps:
and a historical data storage step, namely storing historical data of the traffic flow data and storing a scheduling table corresponding to the traffic flow data.
By storing the historical data of the traffic flow data, the schedule generated in the later period is convenient to refer.
Further, the method also comprises the following steps:
a leave asking management step, namely receiving leave asking requests of the scheduling personnel in the period of time to be scheduled, analyzing whether the period of time to be scheduled has cross or not when a plurality of leave asking requests exist, and acquiring the scheduling request to be scheduled from the scheduling personnel and scheduling if the period of time to be scheduled has cross; and if no crossover exists, the waiting scheduling time interval of the scheduling staff who asks for is exchanged for scheduling.
The change of personnel such as the person's the time of a rest, ask for leave can carry out nimble arrangement, avoids work conflict to appear, reduces work efficiency.
Further, the leave asking management step further comprises the following steps:
and a final scheduling list generation step, after the scheduling list is generated and when a scheduling request of the scheduled personnel is received, scheduling according to a preset scheduling rule, replacing the scheduled personnel with the scheduled personnel, and generating the final scheduling list.
The final scheduling list has flexibility, and work efficiency is guaranteed.
Drawings
Fig. 1 is a logic block diagram of an intelligent shift arrangement system based on gas station user classification guidance according to an embodiment of the present invention.
Detailed Description
The following is further detailed by way of specific embodiments:
the first embodiment is as follows:
an intelligent scheduling system based on gas station user classification guidance, as shown in fig. 1, comprises a server, the server comprises the following modules:
the traffic flow information acquisition module is used for acquiring the characteristic information of the vehicles through the image information acquisition equipment, classifying the vehicles according to the characteristic information, setting statistical time nodes of the traffic flow, statistically analyzing the classification types and the number of the vehicles according to the statistical time nodes, generating and storing traffic flow data; the characteristic information includes a license plate number, a vehicle model number and a vehicle type. The image information acquisition equipment is in communication connection with the server, and the image information acquisition equipment adopts a camera.
The traffic flow estimation module is used for reading the historical data of the traffic flow data and estimating the traffic flow data on the preset day according to the historical data;
the number of people/man-hour estimation module is used for analyzing estimated number of people data and estimated man-hour data required by each post of the gas station according to the traffic flow data of the preset day;
and the scheduling list generation module is used for setting a scheduling template and generating a scheduling list according to the estimated times data and the estimated working hour data required by each post.
The shift list generation module further comprises the following two modules:
the personnel information storage module is used for storing information of personnel to be scheduled; the information of the staff to be scheduled comprises staff names and staff numbers;
and the post information storage module is used for storing the post information to be scheduled.
The system comprises a leave asking management module, a leave asking management module and a shift scheduling module, wherein the leave asking management module is used for receiving leave asking requests of shift scheduling personnel in a waiting shift scheduling period, analyzing whether the shift scheduling period is crossed or not when a plurality of leave asking requests exist, and acquiring shift scheduling requests to be scheduled from the shift scheduling personnel and performing shift scheduling if the shift scheduling period is crossed; and if no crossover exists, the waiting scheduling time interval of the scheduling staff who asks for is exchanged for scheduling.
And the final scheduling list generating module is used for performing scheduling according to a preset scheduling rule after generating the scheduling list and when receiving a scheduling request of an active requirement scheduled worker, replacing the scheduled worker by the scheduled worker, and generating the final scheduling list. And (4) shift adjustment rules: and exchanging the scheduling time of the two, and considering whether the working hour matching is the same and the post matching is the same.
And the historical data storage module is used for storing the historical data of the traffic flow data and storing a scheduling list corresponding to the traffic flow data.
An intelligent scheduling method based on gas station user classification guidance is disclosed, wherein the system based on the method comprises the following steps:
a traffic flow information acquisition step, namely acquiring characteristic information of vehicles through image information acquisition equipment, classifying the vehicles according to the characteristic information, setting statistical time nodes of traffic flow, statistically analyzing classification types and the number of the vehicles according to the statistical time nodes, generating traffic flow data and storing the traffic flow data; the characteristic information includes a license plate number, a vehicle model number and a vehicle type.
A traffic flow estimation step, namely reading historical data of traffic flow data and estimating the traffic flow data on a preset day according to the historical data;
estimating the number of people/working hours, namely analyzing estimated number of people data and estimated working hour data required by each post of the gas station according to traffic flow data of a preset day;
and a scheduling table generation step, namely setting a scheduling template, and generating the scheduling table according to the estimated times data and the estimated working hour data required by each post.
The shift list generating step further comprises the following two steps:
a personnel information storage step, in which the information of personnel to be scheduled is stored; the information of the staff to be scheduled comprises staff names and staff numbers;
and a post information storage step, in which the post information to be scheduled is stored.
A leave asking management step, namely receiving leave asking requests of the scheduling personnel in the period of time to be scheduled, analyzing whether the period of time to be scheduled has cross or not when a plurality of leave asking requests exist, and acquiring the scheduling request to be scheduled from the scheduling personnel and scheduling if the period of time to be scheduled has cross; and if no crossover exists, the waiting scheduling time interval of the scheduling staff who asks for is exchanged for scheduling.
And a final scheduling list generation step, after the scheduling list is generated and when a scheduling request of the scheduled personnel is received, scheduling according to a preset scheduling rule, replacing the scheduled personnel with the scheduled personnel, and generating the final scheduling list.
And a historical data storage step, namely storing historical data of the traffic flow data and storing a scheduling table corresponding to the traffic flow data.
The specific implementation process is as follows:
because the traffic flow data are regularly circulated in a certain period, and the gas station becomes an indispensable part in the life of people, the collection of the traffic flow data at the gas station is very convenient. When the traffic flow data are collected, the scheme can classify the vehicles according to the characteristic information of the vehicles, so that the traffic flow data are obtained. And then, the historical data of the traffic flow data is used as reference data to estimate the traffic flow data on the preset day, so that data support is provided for reasonable scheduling of personnel, and the working efficiency is guaranteed.
After the traffic flow data are obtained, the scheduling of the staff can be reasonably arranged according to the traffic flow data and the staff and the posts of the gas station, so that the scheduling mode has good flexibility, and the working efficiency can be guaranteed. For example, during peak fueling periods of a vehicle, a relatively large but reasonable number of crew members are scheduled to work. In the vehicle refueling valley period of the gas station, a small number of workers with reasonable quantity are arranged to work.
In addition, the scheme can flexibly arrange the change of personnel such as the rest of the personnel, leave requests and the like, avoid the conflict of work and reduce the work efficiency.
Example two:
the difference between the second embodiment and the first embodiment is that the server further comprises the following modules:
a monitoring module: the system is used for monitoring the scheduling execution data of the staff according to the final scheduling list; the scheduling execution data comprises historical scheduling information, good posts, leave information and working hour data of the staff;
an analysis module: the system is used for analyzing the scheduling data monitored by the monitoring module and screening out a plurality of optimal employees according to different optimal conditions; the preferred conditions include: the number of leave requests is small, the post technical capability is high, the service attitude is good, and the working hour data is high.
A selection module: the scheduling optimization table is used for obtaining the working hour data, the post mastering difficulty data and the post income data of all the posts, screening out a plurality of optimal posts according to the working hour data, the post mastering difficulty data and the post income data, and then matching each selected optimal employee with the optimal post to generate the scheduling optimization table.
A scheduling module: the scheduling optimization table is used for obtaining the scheduling willingness of the best staff, performing scheduling optimization on the scheduling optimization table according to the scheduling willingness and scheduling execution data monitored by the monitoring module, and generating a scheduling final scheduling table.
The intelligent scheduling method further comprises the following steps:
a monitoring step: monitoring the scheduling execution data of the staff according to the final scheduling table; the scheduling execution data comprises historical scheduling information, good posts, leave information and working hour data of the staff;
and (3) an analysis step: analyzing the shift arrangement data monitored in the monitoring step, and screening out a plurality of optimal employees according to different optimal conditions; the preferred conditions include: the number of leave requests is small, the post technical capability is high, the service attitude is good, and the working hour data is high.
Selecting: the method comprises the steps of obtaining working hour data, post mastering difficulty data and post income data of all posts, screening out a plurality of optimal posts according to the working hour data, the post mastering difficulty data and the post income data, and then matching selected optimal staff with the optimal posts to generate a scheduling optimization table.
A scheduling step: and acquiring the scheduling willingness of the best staff, and performing scheduling optimization on the scheduling optimization table according to the scheduling willingness and the scheduling execution data monitored in the monitoring step to generate a scheduling final scheduling table.
The specific implementation process is as follows:
for excellent employees, the excellent employees can be arranged in the optimal time period or the optimal post, so that the utilization rate of the existing employees is improved, the high-quality service is ensured, meanwhile, the incentive to other employees is achieved, and the working enthusiasm of the employees is promoted.
The foregoing is merely an example of the present invention, and common general knowledge in the field of known specific structures and characteristics is not described herein in any greater extent than that known in the art at the filing date or prior to the priority date of the application, so that those skilled in the art can now appreciate that all of the above-described techniques in this field and have the ability to apply routine experimentation before this date can be combined with one or more of the present teachings to complete and implement the present invention, and that certain typical known structures or known methods do not pose any impediments to the implementation of the present invention by those skilled in the art. It should be noted that, for those skilled in the art, without departing from the structure of the present invention, several changes and modifications can be made, which should also be regarded as the protection scope of the present invention, and these will not affect the effect of the implementation of the present invention and the practicability of the patent. The scope of the claims of the present application shall be determined by the contents of the claims, and the description of the embodiments and the like in the specification shall be used to explain the contents of the claims.
Claims (10)
1. Intelligent scheduling system based on filling station user classification guide, its characterized in that: the server comprises the following modules:
the traffic flow information acquisition module is used for acquiring the characteristic information of the vehicles, classifying the vehicles according to the characteristic information, setting a statistical time node of the traffic flow, and statistically analyzing the classification types and the number of the vehicles according to the statistical time node to generate and store traffic flow data;
the traffic flow estimation module is used for reading the historical data of the traffic flow data and estimating the traffic flow data on the preset day according to the historical data;
the number of people/man-hour estimation module is used for analyzing estimated number of people data and estimated man-hour data required by each post of the gas station according to the traffic flow data of the preset day;
and the scheduling list generation module is used for setting a scheduling template and generating a scheduling list according to the estimated times data and the estimated working hour data required by each post.
2. The intelligent scheduling system based on gas station user classification guidance of claim 1, wherein: the shift list generation module further comprises the following modules:
the personnel information storage module is used for storing information of personnel to be scheduled; the information of the staff to be scheduled comprises staff names and staff numbers;
and the post information storage module is used for storing the post information to be scheduled.
3. The intelligent scheduling system based on gas station user classification guidance of claim 1, wherein: the traffic flow estimation module comprises the following modules:
and the historical data storage module is used for storing the historical data of the traffic flow data and storing a scheduling list corresponding to the traffic flow data.
4. The intelligent scheduling system based on gas station user classification guidance of claim 1, wherein: the system also comprises the following modules:
the system comprises a leave asking management module, a leave asking management module and a shift scheduling module, wherein the leave asking management module is used for receiving leave asking requests of shift scheduling personnel in a waiting shift scheduling period, analyzing whether the shift scheduling period is crossed or not when a plurality of leave asking requests exist, and acquiring shift scheduling requests to be scheduled from the shift scheduling personnel and performing shift scheduling if the shift scheduling period is crossed; and if no crossover exists, the waiting scheduling time interval of the scheduling staff who asks for is exchanged for scheduling.
5. The intelligent scheduling system based on gas station user classification guidance of claim 4, wherein: the leave asking management module further comprises the following modules:
and the final scheduling list generating module is used for performing scheduling according to a preset scheduling rule after generating the scheduling list and when receiving a scheduling request of a scheduled person, replacing the scheduled person with the scheduled person, and generating the final scheduling list.
6. The intelligent scheduling method based on the gas station user classification guidance is characterized by comprising the following steps: the method comprises the following steps:
a traffic flow information obtaining step, namely obtaining the characteristic information of the vehicles, classifying the vehicles according to the characteristic information, setting a statistical time node of the traffic flow, and statistically analyzing the classification types and the number of the vehicles according to the statistical time node to generate and store traffic flow data;
a traffic flow estimation step, namely reading historical data of traffic flow data and estimating the traffic flow data on a preset day according to the historical data;
estimating the number of people/working hours, namely analyzing estimated number of people data and estimated working hour data required by each post of the gas station according to traffic flow data of a preset day;
and a scheduling table generation step, namely setting a scheduling template, and generating the scheduling table according to the estimated times data and the estimated working hour data required by each post.
7. The intelligent scheduling method based on the gas station user classification guidance as claimed in claim 6, wherein: the shift schedule generating step further comprises the steps of:
a personnel information storage step, in which the information of personnel to be scheduled is stored; the information of the staff to be scheduled comprises staff names and staff numbers;
and a post information storage step, in which the post information to be scheduled is stored.
8. The intelligent scheduling method based on the gas station user classification guidance as claimed in claim 6, wherein: the traffic flow estimation step comprises the following steps:
and a historical data storage step, namely storing historical data of the traffic flow data and storing a scheduling table corresponding to the traffic flow data.
9. The intelligent scheduling method based on the gas station user classification guidance as claimed in claim 6, wherein: further comprising the steps of:
a leave asking management step, namely receiving leave asking requests of the scheduling personnel in the period of time to be scheduled, analyzing whether the period of time to be scheduled has cross or not when a plurality of leave asking requests exist, and acquiring the scheduling request to be scheduled from the scheduling personnel and scheduling if the period of time to be scheduled has cross; and if no crossover exists, the waiting scheduling time interval of the scheduling staff who asks for is exchanged for scheduling.
10. The intelligent scheduling method based on the gas station user classification guidance as claimed in claim 9, wherein: the leave asking management step further comprises the following steps:
and a final scheduling list generation step, after the scheduling list is generated and when a scheduling request of the scheduled personnel is received, scheduling according to a preset scheduling rule, replacing the scheduled personnel with the scheduled personnel, and generating the final scheduling list.
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| CN115271372B (en) * | 2022-07-04 | 2023-09-12 | 无锡喔趣信息科技有限公司 | Human resource scheduling management system and method based on regional linkage |
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Application publication date: 20191224 |