CN110659819A - Automatic course arrangement system for selecting courses and walking under new high-examination mode - Google Patents
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Abstract
The invention relates to the technical field of teaching resource optimization, and discloses an automatic course arrangement system for selecting courses and walking in a new high-level examination mode, which comprises four parts of school information input arrangement, automatic course arrangement, educational administration management and class schedule generation, wherein the school information input arrangement comprises the following steps: the resource information of students and schools is input and arranged in a simple and easy-to-operate mode, and the resource information is used for follow-up course arrangement, is convenient for school management and can be automatically arranged: the combination optimization problem is solved by combining a Greedy Algorithm (Greedy Algorithm) and a Tabu Search Algorithm (Tabu Search Algorithm), and the method mainly comprises two steps, wherein the first step is to cluster all courses according to course selection conditions of students. This automatic course arrangement system of class is walked to lecture selection under new high examination mode is based on the restriction of resources such as school teacher and classroom, and application optimization algorithm integrates and optimizes relevant resource and student's the condition of selecting courses, and then provides one set of intelligence arrangement scheme, solves the difficult problem of school's arrangement of courses for the arrangement scheme of school is scientific more, reasonable.
Description
Technical Field
The invention relates to the field of teaching resource optimization, in particular to an automatic course arrangement system for selecting courses and walking under a new high-level examination mode.
Background
The new college entrance examination policy makes a series of reform for high school courses, wherein the course selection mechanism is a bright spot, which is different from the traditional literature and scientific subjects, meets different requirements of students, develops the interests and specialties of the students, simultaneously cultivates the individuality of the students, and promotes the characteristic development of schools for schools, so that the mode of study is diversified.
The course selection mechanism of 'six-out-of-three' or 'seven-out-of-three', namely, the students independently select three out of six (or seven) subjects as high-level entrance examination subjects, and the rest three (or four) subjects as high-level entrance examination subjects, under the mechanism, the course selection combination can be up to 20 combination modes, and due to the diversity of course selection of the students, a mode of moving the class appears after the class division is finished: for example, all students in a class select the same two subjects (e.g., physical and chemical) as the required course, but their third subject is different, and then they need to change to another class to go to the third required course.
At present, the fully-open course selection mode is not implemented in middle schools in all areas where new high-level entrance examination modes are implemented, the main reason is that limitation of resources of teachers and classrooms is achieved, most schools with insufficient teachers and resources combine and limit selectable subjects of students within a few, and therefore the traditional mode is not broken, the existing course selection mode is mostly the fully-open course selection mode, the mode enables schools to arrange courses, the fact that whether time and sequence of courses are reasonable or not needs to be considered like the traditional mode, and the limiting conditions that the teachers, the classrooms and the students do not conflict with each other need to be considered.
Disclosure of Invention
Technical problem to be solved
Aiming at the defects of the prior art, the invention provides an automatic course arrangement system for selecting courses and walking in a new high-level examination mode, which solves the problems that the existing course selection mode is mostly a fully-open course selection mode, and the way can ensure that the time and the sequence of courses are not only reasonable but also the limiting conditions that teachers, classrooms and students do not conflict with each other are required to be considered when a school arranges courses.
(II) technical scheme
In order to achieve the purpose, the invention provides the following technical scheme: an automatic course arrangement system for selecting courses and walking in a new high-examination mode comprises four parts of school information input arrangement, automatic course arrangement, educational administration management and class schedule generation.
Preferably, the school information is input and sorted, and the student and school resource information is input and sorted in a simple and easy-to-operate mode, so that the school information is used for subsequent course arrangement and is convenient for school management.
Preferably, the automatic course arrangement is implemented by combining a Greedy Algorithm (Greedy Algorithm) and a Tabu Search Algorithm (Tabu Search Algorithm) to solve the problem of combination optimization, and mainly comprises two steps, wherein the first step is to cluster all courses according to the course selection condition of students, and the second step is to put the combined courses into a school timetable according to the conditions of priority and prohibition.
Preferably, the method comprises the following steps:
the method comprises the following steps: the current courses are clustered and combined based on course selection conditions of students, and the clustering condition is that the students, classrooms and teachers can attend the courses together at the same time point, namely the courses do not conflict.
Step two: and processing school course arrangement rules as limiting conditions and outputting to the next optimization iteration process.
Step three: and (4) putting the course combination in the step (I) into a school timetable based on the limiting conditions of the step (II), and calculating the total score of the school timetable. Each iteration of the process generates a new schedule and its corresponding score. After a certain number of iterations, the class sheet with the highest score is taken as the final class sheet.
Step four: based on the school timetable obtained in step four, the school can adjust it. During the adjustment process, the system can automatically detect whether conflicts occur among students, teachers and classrooms of the adjusted course.
Step five: the school timetable which is settled after adjustment supports multi-dimensional display and export: class, classroom, teacher, or student dimensions. Wherein, the class and the teacher are the main school timetable display modes.
Preferably, the lesson management mainly adjusts the lesson schedule in the automatic lesson arrangement according to the special requirements of individual teachers and the sudden activities of schools.
Preferably, the generation of the school timetable can generate a multidimensional school timetable which mainly takes the visual angles of students, classrooms or teachers as main points, so that the students and the teachers can conveniently check the school timetable, and schools can conveniently check and manage the class taking conditions.
(III) advantageous effects
The invention provides an automatic course arrangement system for selecting courses and walking in a new high-examination mode, which has the following beneficial effects:
(1) this automatic course arrangement system of class selection on new high school mode of examining is walked on duty is based on the restriction of resources such as school teacher and classroom, application optimization algorithm integrates and optimizes relevant resource and student's the condition of selecting courses, and then provide one set of intelligent course arrangement scheme, make the course arrangement scheme of school more scientific, reasonable, the mode of selecting courses that has solved current mode of selecting courses is the open-type of selecting courses entirely, this kind of mode can make school in the course of arranging, not only need consider under the traditional mode whether time and the order of course are reasonable, but also need consider the teacher, the problem of the restriction condition of the mutual conflict of teacher and student's three-party.
(2) According to the invention, by setting and forming course combinations and arranging the course combinations into a school timetable and adjusting the course combinations, the courses can be clustered by combining a Greedy Algorithm (Greedy Algorithm) and a Tabu SearchAlgorithm (Tabu SearchAlgorithm) based on course selection results of students, and in the course of forming the course combinations, optimization iteration is carried out by taking min (number of clusterings) as a target function.
Drawings
FIG. 1 is a functional block diagram of the system of the present invention;
FIG. 2 is a flow chart of a combinatorial optimization algorithm of the present invention;
FIG. 3 is an example of a class lesson chart generation diagram of the present invention;
FIG. 4 is an example of a teacher's lesson chart generation of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example (b):
as shown in fig. 1 to 4, the present invention provides a technical solution: an automatic course arrangement system for selecting courses and walking in a new high-examination mode comprises the following steps:
the utility model provides an automatic course arrangement system of class selection on new high examination mode of walking on duty, includes four parts of school's information entry arrangement, automatic course arrangement, educational administration management, formation lesson table, school's information entry arrangement: the resource information of students and schools is input and arranged in a simple and easy-to-operate mode, and the resource information is used for follow-up course arrangement, is convenient for school management and can be automatically arranged: the combination optimization problem is solved by combining a greedy Algorithm (greedy Algorithm) and a Tabu Search Algorithm (Tabu Search Algorithm), the combination optimization problem is mainly divided into two steps, the first step is to cluster all courses according to the course selection condition of students, the second step is to put the combined courses into a school timetable according to the conditions of priority and prohibition, and the educational administration management is as follows: the class schedule in the automatic course arrangement is adjusted mainly aiming at the special requirements of individual teachers and the sudden activities of schools, and the class schedule is generated: the multi-dimensional class schedule taking the visual angles of students, classrooms or teachers as main points can be generated, so that the students and the teachers can conveniently check the class schedule, and meanwhile, schools can conveniently check and manage the class taking condition, and the problem that the schools need to choose classes is solved.
Step one, forming course combinations: the current courses are clustered and combined based on course selection conditions of students, and the clustering condition is that the students, classrooms and teachers can attend the courses together at the same time point, namely the courses do not conflict.
1) Training data are simulated, the training data aim at finding the most suitable scoring standard to determine the optimized route in the process of searching the optimal solution subsequently, in view of the shortage of actual school data, about 1000 training data are simulated according to the existing data and the information of schools in various regions, namely 1000 schools needing course arrangement, and the information of each variable is as follows:
| variables of | Minimum value | Maximum value | Whether based on other variables |
| Total number of students | 100 | 3000 | Whether or not |
| Number of selectable subjects | 6 | 7 | Whether or not |
| Number of student course selection combinations | 20 | 35 | Whether or not |
| School timeBy number of |
5 | 60 | Based on the total number of students |
| Number of teachers in each subject | 1 | 20 | Based on the total number of students |
In order to ensure the flexibility, the course selection combination distribution proportion of students is also randomly generated, the structure of the final simulation data is a list, and the list comprises all course information of the school: the list of teachers, classrooms and students.
2) And (3) data preprocessing, namely processing on the basis of training data to ensure the efficiency of the optimization process, and obtaining a query list of all courses for detecting the conflict between each course and the course, wherein the conflict detection needs to consider teachers, classrooms and students at the same time.
3) Establishing an initial combination, wherein a classroom can only have a previous course at the same time point due to the limitation of classroom resources, establishing a list R, wherein an element R in the list R is also a list and contains all courses required to have a course in the current classroom, namely:
R＝list(r1,r2,r3...rn)
r1＝list(c1,c4,c6...)
…
rn＝list(c18,c24,c30...)
where r represents each classroom, c represents the class in the current classroom
Selecting the R list with the most elements in the R list, namely all R lists with the list length equal to max ([ len (R1), len (R2),.. len (rn)) ], scoring the lists according to the course conflict conditions in the lists, and generating the initial combination by using the list with the highest score: putting each class in the list into a single combination and calculating the current combination score from the current class (see the specific method for calculating the score 4)), because classes in the same classroom cannot appear in the same combination, using classroom as a basis to generate the initial combination is a convenient, stable and effective method.
4) Circulating the course list, putting the courses into the combination, building the initial combination, wherein each combination has one course and a combination score, and scoring the rest courses in the course list, wherein the scoring rule is as follows:
| combined score | Course scoring | |
| There is a classroom conflict with the combination in the current course | +1 | +1 |
| Teacher conflict between current course and combination | +1 | +1 |
| The number n of courses in which the current course conflicts with the students in the combination | +n | +n |
And repeating the scoring procedure and updating the scores of each combination and the courses until all the courses have the corresponding combination.
A special case occurs during cycling: the list of the unscheduled courses has the remaining courses, but the courses conflict with all combinations, in which case, an additional program needs to be started, the courses which are already placed in the combination but conflict with the current unscheduled course are moved to other combinations, and then the current course is put into the vacant combination, and the flow chart of course combination optimization is shown in fig. 2.
Step two, processing course arrangement rules: before the course arrangement is formally carried out, the course arrangement rules of schools need to be collated and processed into variables which can be absorbed by programs, and all the arrangeable course arrangement rules are as follows:
1. forbidding course arrangement: teachers, classrooms and courses may be set to prohibit course scheduling in certain classes.
2. And (3) priority course arrangement: teachers, classrooms, and classes may all set priorities to arrange classes in specific classes.
3. Selecting time to move: for setting up a work-taking lesson schedule to attend a class for a specific period of time.
4. Closing the class: for setting up a particular class to compose a class.
The first three rules are all expressed in the form of lessons, for example, teacher t1 does not list lessons in the first lessons of monday, third and fifth as: { t1: [1,9,17] }, default eight classes per day, and class-on class is expressed in the form of class number, for example, 1 and 2 music classes are expressed as: { subject: 'music', class _ num: [1,2] }.
Step three, assigning lessons: the school sets several classes a week, several lessons in the morning and afternoon, respectively, and taking five days a week and four lessons each day as an example, the class schedule should be shown as follows:
| monday | Zhou Di | Wednesday | Week four | ZhouWu for treating viral hepatitis |
| 1 | 5 | 9 | 13 | 17 |
| 2 | 6 | 10 | 14 | 18 |
| 3 | 7 | 11 | 15 | 19 |
| 4 | 8 | 12 | 16 | 30 |
(the number represents the number of each class)
And arranging the lessons with conditional constraints and the corresponding courses according to the rule setting. The rest course combinations are arranged into vacant lessons in sequence according to the following priority levels and are properly adjusted:
the subject (Chinese, math, English) is prioritized in the morning of each day.
Interest classes (art, music, sports) are not ranked as far as possible in the first two of the day.
Dispersion over a single week: assuming that a course has 5 lessons per week, the score of each lesson is arranged to be the highest every day.
The same subjects on the same day try to arrange to have a class.
Step four, educational administration management: based on the fact that each school has campus activity arrangement, each teacher also has requirements and special conditions, after a basic school timetable is obtained, school teachers can adjust individual teachers and lessons, and in the adjusting process, the system can automatically detect conflicts among all parties so as to ensure that the adjusted school timetable has no conflicts.
Step five, generating a class schedule: under the course selection and shift system, the class schedule is displayed and exported in a multi-dimensional mode: student schedules, teacher schedules, and student schedules, the generated class representations are shown in fig. 3, for example, and the generated teacher class representations are shown in fig. 4, for example.
The invention provides an automatic course arrangement system aiming at the course selection characteristics in a new college entrance examination mode, and based on the limitation of resources such as school teachers, classrooms and the like, an optimization algorithm is applied to integrate and optimize related resources and the course selection condition of students, so that a set of intelligent course arrangement scheme is provided, the problem of difficult course arrangement of schools is solved, and the course arrangement scheme of the schools is more scientific and reasonable.
In conclusion, the automatic course arrangement system for selecting courses and going to work in the new high-level examination mode integrates and optimizes related resources and course selection conditions of students by using an optimization Algorithm based on the limitation of resources such as school teachers and classrooms, further provides a set of intelligent course arrangement scheme, so that the course arrangement scheme of the school is more scientific and reasonable, can cluster courses by setting course combinations and arranging the course combinations into a school timetable and adjusting the course combinations based on the course selection results of the students and using a Greedy Algorithm (Greedy Algorithm) and a Tabu Search Algorithm (Tabu Search Algorithm), performs optimization iteration by taking min (number of customers) as a target function in the course of forming the course combinations, solves the problem that the existing course selection modes are mostly fully open course selection modes, and can ensure that whether the time and sequence of courses are reasonable or not only need to be considered in the course arrangement process of the school in the traditional mode, but also considering the problem of non-conflicting restriction conditions among teachers, classrooms and students
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (6)
1. The utility model provides an automatic course arrangement system of class selection on new high examination mode of going on duty which characterized in that: the method comprises four parts of school information input and arrangement, automatic course arrangement, educational administration management and generation of a class schedule.
2. The system of claim 1, wherein the system comprises: school information inputting and arranging: the resource information of students and schools is input and sorted in a simple and easy-to-operate mode, and the resource information is used for subsequent course arrangement and is convenient for school management.
3. The system of claim 1, wherein the system comprises: automatic course arrangement: the combination optimization problem is solved by combining a Greedy Algorithm (Greedy Algorithm) and a Tabu search Algorithm (Tabu search Algorithm), and the method mainly comprises two steps, wherein the first step is to cluster all courses according to the course selection condition of students, and the second step is to put the combined courses into a school timetable according to the conditions of priority and prohibition.
4. The system of claim 3, wherein the system comprises: the method comprises the following steps:
the method comprises the following steps: clustering combination is carried out on the current courses based on course selection conditions of students, and the clustering conditions are that the courses can be taken together at the same time point, namely, the courses are not conflicted among the students, the classrooms and the teachers;
step two: processing school course arrangement rules as limiting conditions, and outputting to the next optimization iteration process;
step three: and (4) putting the course combination in the step (I) into a school timetable based on the limiting conditions of the step (II), and calculating the total score of the school timetable. Each iteration of the process generates a new schedule and its corresponding score. After a certain number of iterations, taking the class sheet with the highest score as a final class sheet;
step four: based on the school timetable obtained in step four, the school can adjust it. In the adjusting process, the system can automatically detect whether the students, teachers and classrooms of the adjusted course conflict or not;
step five: the school timetable which is settled after adjustment supports multi-dimensional display and export: class, classroom, teacher, or student dimensions. Wherein, the class and the teacher are the main school timetable display modes.
5. The system of claim 1, wherein the system comprises: and (3) educational administration management: the school timetable in the automatic course arrangement is adjusted mainly according to the special requirements of individual teachers and the sudden activities of schools.
6. The system of claim 1, wherein the system comprises: and (3) generating a class schedule: the multi-dimensional school timetable with the visual angles of students, classrooms or teachers as main points can be generated, so that the students and the teachers can conveniently check the school timetable, and schools can conveniently check and manage the class taking conditions.
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112149950A (en) * | 2020-08-07 | 2020-12-29 | 湖南强智科技发展有限公司 | Course information arrangement method, device, equipment and storage medium |
| CN112700206A (en) * | 2020-12-07 | 2021-04-23 | 北京晓羊教育科技集团有限公司 | Method, device and equipment for constructing course arrangement behavior model and computer readable storage medium |
| CN113434132A (en) * | 2021-05-08 | 2021-09-24 | 西安电子科技大学 | Intelligent course arrangement modeling verification method and system |
| CN114399191A (en) * | 2022-01-11 | 2022-04-26 | 西安建筑科技大学 | College course arrangement system and method based on building energy conservation |
| CN117151947A (en) * | 2023-10-31 | 2023-12-01 | 沈阳卡得智能科技有限公司 | Intelligent course arrangement method and system based on greedy algorithm |
-
2019
- 2019-09-19 CN CN201910884272.5A patent/CN110659819A/en not_active Withdrawn
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112149950A (en) * | 2020-08-07 | 2020-12-29 | 湖南强智科技发展有限公司 | Course information arrangement method, device, equipment and storage medium |
| CN112700206A (en) * | 2020-12-07 | 2021-04-23 | 北京晓羊教育科技集团有限公司 | Method, device and equipment for constructing course arrangement behavior model and computer readable storage medium |
| CN113434132A (en) * | 2021-05-08 | 2021-09-24 | 西安电子科技大学 | Intelligent course arrangement modeling verification method and system |
| CN114399191A (en) * | 2022-01-11 | 2022-04-26 | 西安建筑科技大学 | College course arrangement system and method based on building energy conservation |
| CN114399191B (en) * | 2022-01-11 | 2024-05-07 | 西安建筑科技大学 | University course arrangement system and method based on building energy conservation |
| CN117151947A (en) * | 2023-10-31 | 2023-12-01 | 沈阳卡得智能科技有限公司 | Intelligent course arrangement method and system based on greedy algorithm |
| CN117151947B (en) * | 2023-10-31 | 2024-01-30 | 沈阳卡得智能科技有限公司 | Intelligent course arrangement method and system based on greedy algorithm |
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