A conference schedule intelligent suggestion method, system, electronic device and storage medium

Abstract

The present invention discloses a method, system, electronic device and storage medium for intelligently suggesting a meeting schedule, the method comprising: obtaining the time arrangement of meetings and participants; constructing a multi-objective optimization objective function consisting of the objective of minimizing fragmented time and the objective of maximizing meeting intervals; using a simulated annealing algorithm to obtain the optimal value of the objective function according to the time arrangement of meetings and participants, and rearranging the meeting time according to the optimal value. The present invention realizes intelligent arrangement of daily meetings of the company, can save a lot of manpower and material resources, improve organizational efficiency and meet the needs of multiple parties under the premise of considering the personal time arrangement of participants.

Description

Technical Field

[0001] The present invention relates to the field of information processing technology, and in particular to a conference schedule intelligent suggestion method, system, electronic device and storage medium. Background Art

[0002] In the daily operation of a company, there are often many meetings. These meetings usually involve multiple departments and multiple participants. If the arrangements are not reasonable, it will cause time conflicts between meetings and thus the meetings cannot be held as originally planned. Imagine such a scenario:

[0003] Project Team A is going to hold a requirements review meeting. The meeting organizer asks everyone about their free time in turn. After getting the approval of all team members, the time is set at 15:00-16:30. Shortly before the meeting, member Xiao Li suddenly realizes that he has a very important meeting from 14:00-15:30, so he cannot attend the requirements review meeting from 15:00-16:30 on time. In this case, the meeting organizer of Project Team A needs to ask everyone about other free time again and arrange it. Assume that the renegotiated time for the requirements review meeting of Project Team A is 13:30-15:00 the next day, which is the free time when all participants can attend the meeting on time. However, member Xiao Wang has to attend another project meeting at 15:00 and prepare a speech to report on his work. In this way, there is no free time between the two meetings, and he cannot make more adequate preparations for the speech at the next meeting. For Xiao Wu, he has another meeting at 16:00 in the afternoon. After this meeting, he has only one hour to attend another meeting. There is half an hour of free time before 13:30. This half hour of free time is divided into two small time periods, so he cannot have a large block to do other things. For another member, Xiao Zhang, he is not used to meetings after 1:00 in the afternoon and would rather do some other work during this time.

[0004] From the scenario, we can see that if we use manual methods to arrange meetings, the following problems may occur:

[0005] (1) It takes a lot of time and energy and is inefficient. Every time there is a meeting, the organizer needs to collect information about the free time of the participants, which consumes a lot of time and energy.

[0006] (2) The cost of modifying meeting time decisions is high. Since the statistics are manually collected, it is inevitable that someone will forget about certain meetings or the statistical information will be wrong. Re-counting will take time and effort, resulting in a very high cost of modifying meetings.

[0007] (3) Meetings are arranged too closely. For some participants who have frequent meetings (especially sales or leadership-level personnel, who usually have frequent meetings), there is almost no rest time between meetings, and they are exhausted.

[0008] (4) Fragmenting time. This breaks a large period of time into small pieces, making it impossible to have a long period of time to do something that requires concentration.

[0009] (5) Failing to consider the preferences of meeting participants. Assuming there are two alternative time periods, if the meeting time preferences of meeting participants can be considered and a time period that is more acceptable to everyone can be selected, employee satisfaction can be greatly improved. Summary of the invention

[0010] In view of the above-mentioned technical problem of unreasonable meeting time arrangement, the present invention proposes a meeting schedule intelligent suggestion method, system, electronic device and storage medium.

[0011] In a first aspect, an embodiment of the present application provides a method for intelligently suggesting a conference schedule, comprising:

[0012] Information acquisition steps: obtain the time schedule of the meeting and the participants;

[0013] Objective function construction steps: construct a multi-objective optimization objective function consisting of minimizing the fragmentation time objective and maximizing the meeting interval objective;

[0014] Meeting arrangement step: using a simulated annealing algorithm to obtain the optimal value of the objective function according to the time arrangement of the meeting and the participants, and rescheduling the meeting time according to the optimal value.

[0015] In the above-mentioned intelligent conference schedule suggestion method, the objective function construction step includes:

[0016] Goal construction step: constructing the goal of minimizing fragmented time and the goal of maximizing meeting interval according to the level of the participants and the time arrangement of the meeting and the participants;

[0017] The overall goal construction step: construct the objective function according to the objective of minimizing the fragmented time and the objective of maximizing the meeting interval and the corresponding weights.

[0018] In the above-mentioned intelligent conference schedule suggestion method, the conference arrangement step includes:

[0019] Public free time acquisition step: acquiring a number of public free time periods of the meeting and the participants according to the schedule of the meeting and the participants;

[0020] Simulated annealing algorithm search step: using the simulated annealing algorithm to search in each section of the common idle time according to the objective function;

[0021] Optimal value returning step: returning the optimal value in each section of the public free time to the user, and rescheduling the meeting according to the optimal value.

[0022] In the above-mentioned intelligent conference schedule suggestion method, the weights of the goal of minimizing fragmented time and the goal of maximizing meeting interval in the objective function are allocated according to the time arrangement of the meeting and the participants.

[0023] In a second aspect, an embodiment of the present application provides a conference schedule intelligent suggestion system, including:

[0024] Information acquisition unit: obtain the time schedule of meetings and participants;

[0025] Objective function construction unit: constructs a multi-objective optimization objective function consisting of minimizing the fragmentation time objective and maximizing the meeting interval objective;

[0026] Meeting scheduling unit: using a simulated annealing algorithm to obtain the optimal value of the objective function according to the time arrangement of the meeting and the participants, and rearranging the meeting time according to the optimal value.

[0027] In the above-mentioned intelligent conference schedule suggestion system, the objective function construction unit includes:

[0028] Goal building module: building the goal of minimizing fragmented time and the goal of maximizing meeting interval according to the level of the participants and the time arrangement of the meeting and the participants;

[0029] Overall goal construction module: constructs the objective function according to the objective of minimizing fragmented time and the objective of maximizing meeting interval and their corresponding weights.

[0030] The above-mentioned intelligent conference schedule suggestion system, wherein the conference arrangement unit includes:

[0031] Public free time acquisition module: obtains several sections of public free time of the meeting and the participants according to the time arrangement of the meeting and the participants;

[0032] Simulated annealing algorithm search module: using the simulated annealing algorithm to search in each section of the common idle time according to the objective function;

[0033] Optimal value returning module: returns the optimal value in each section of the public free time to the user, and rearranges the meeting according to the optimal value.

[0034] In the above-mentioned intelligent meeting schedule suggestion system, the overall goal construction module allocates the weights of the goal of minimizing fragmented time and the goal of maximizing meeting interval in the objective function according to the time arrangement of the meeting and the participants.

[0035] In a third aspect, an embodiment of the present application provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the method for intelligently suggesting a meeting schedule as described in the first aspect above is implemented.

[0036] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method for intelligently suggesting a meeting schedule as described in the first aspect above.

[0037] Compared with the prior art, the advantages and positive effects of the present invention are:

[0038] The present invention relates to the field of operational optimization technology, and proposes a multi-objective optimization method for selecting the optimal meeting time within the arrangable meeting time period, so as to realize the intelligent arrangement of daily meetings of the company. It can save a lot of manpower and material resources, improve organizational efficiency, and meet the needs of multiple parties while considering the personal time arrangements of the participants. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 A schematic diagram of the steps of a method for intelligently suggesting a conference schedule provided by the present invention;

[0040] Figure 2 The present invention provides Figure 1 Flow chart of step S2;

[0041] Figure 3 The present invention provides Figure 1 Flow chart of step S3;

[0042] Figure 4 A schematic diagram of the simulated annealing algorithm provided by the present invention;

[0043] Figure 5 A flow chart of the simulated annealing algorithm provided by the present invention;

[0044] Figure 6 A framework diagram of a conference schedule intelligent suggestion system provided by the present invention;

[0045] Figure 7 A framework diagram of a computer device according to an embodiment of the present application.

[0046] Wherein, the accompanying drawings are marked as follows:

[0047] 1. Information acquisition unit; 2. Objective function construction unit; 21. Objective construction module; 22. Overall objective construction module; 3. Meeting arrangement unit; 31. Public free time acquisition module; 32. Simulated annealing algorithm search module; 33. Optimal value return module; 81. Processor; 82. Memory; 83. Communication interface; 80. Bus. DETAILED DESCRIPTION

[0048] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application is described and illustrated below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application. Based on the embodiments provided in the present application, all other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the present application.

[0049] Obviously, the drawings described below are only some examples or embodiments of the present application. For ordinary technicians in this field, the present application can also be applied to other similar scenarios based on these drawings without creative work. In addition, it can also be understood that although the efforts made in this development process may be complicated and lengthy, for ordinary technicians in this field related to the content disclosed in this application, some changes in design, manufacturing or production based on the technical content disclosed in this application are just conventional technical means, and should not be understood as insufficient content disclosed in this application.

[0050] Reference to "embodiments" in this application means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those of ordinary skill in the art that the embodiments described in this application may be combined with other embodiments without conflict.

[0051] Unless otherwise defined, the technical terms or scientific terms involved in this application should be understood by people with ordinary skills in the technical field to which this application belongs. The words "one", "a", "a", "the" and the like involved in this application do not indicate a quantitative limitation, and may represent the singular or plural. The terms "include", "comprise", "have" and any of their variations involved in this application are intended to cover non-exclusive inclusions; for example, a process, method, system, product or device that includes a series of steps or modules (units) is not limited to the listed steps or units, but may also include steps or units that are not listed, or may also include other steps or units inherent to these processes, methods, products or devices. The words "connect", "connected", "coupled" and the like involved in this application are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The "multiple" involved in this application refers to two or more. "And / or" describes the association relationship of associated objects, indicating that there may be three relationships, for example, "A and / or B" can represent: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the objects before and after are in an "or" relationship. The terms "first", "second", "third", etc. involved in this application are only used to distinguish similar objects and do not represent a specific ordering of the objects.

[0052] The present invention is described in detail below in conjunction with the various embodiments shown in the accompanying drawings, but it should be noted that these embodiments are not limitations of the present invention, and any equivalent transformations or substitutions in functions, methods, or structures made by ordinary technicians in the field based on these embodiments are all within the scope of protection of the present invention.

[0053] Before elaborating on each embodiment of the present invention in detail, the core inventive concept of the present invention is summarized and elaborated in detail through the following several embodiments.

[0054] The present invention solves the objective function of multi-objective optimization consisting of minimizing the fragmentation time objective and maximizing the meeting interval objective by using a simulated annealing algorithm in several idle time periods between meetings and participants, obtains the optimal value of the objective function, and rearranges the meeting time according to the optimal value.

[0055] Embodiment 1:

[0056] Figure 1 The following is a schematic diagram of the steps of a method for intelligently suggesting a conference schedule provided by the present invention. Figure 1 As shown, this embodiment discloses a specific implementation method of a conference schedule intelligent suggestion method (hereinafter referred to as "method").

[0057] The present invention comprehensively considers several factors such as time-consuming and labor-intensive meeting arrangements and modifications, too tight arrangements, time fragmentation, and different preferences of participants, and makes meeting arrangements informationized, saving manpower and material resources, thereby improving the efficiency of the organization. When making time arrangements, an operations optimization algorithm is needed to select a suitable time so that the fragmentation time of participants is the shortest or the interval between meetings is the longest, so that they can better prepare for the meeting. This creates two goals, minimizing fragmented time and maximizing meeting intervals. These two goals are often conflicting, so it involves a balance between the two goals, that is, a dual-objective optimization problem. The present invention mainly provides how to use dual-objective optimization to reasonably arrange meeting times.

[0058] Multi-objective optimization usually has multiple objectives, which are often in conflict with each other, so a balance must be achieved between the objectives. There are two commonly used methods for multi-objective problems. One is to convert the multi-objective optimization problem into a single-objective optimization problem, perform weighted summation on multiple objectives, assign different weights to different objectives according to their importance, and then use a single-objective optimization method for optimization; the other is to use a multi-objective evolutionary algorithm to solve, thereby obtaining a set of Pareto optimal solutions, and select from the optimal solution set according to the actual problem. The present invention mainly considers converting the multi-objective optimization problem into a single-objective optimization problem, and then obtaining the optimal solution.

[0059] Specifically, the method disclosed in this embodiment mainly includes the following steps:

[0060] Step S1: Obtain the time schedule of the meeting and the participants;

[0061] Step S2: constructing a multi-objective optimization objective function consisting of minimizing the fragmentation time objective and maximizing the meeting interval objective;

[0062] Reference Figure 2 As shown, step S2 specifically includes the following contents:

[0063] Step S21: constructing the minimization of fragmented time target and the maximization of meeting interval target according to the level of the participants and the time arrangement of the meeting and the participants;

[0064] Step S22: constructing the objective function according to the objective of minimizing the fragmented time and the objective of maximizing the meeting interval and the corresponding weights.

[0065] Specifically, the constructed minimization of fragmentation time objectives and maximization of meeting interval objectives as well as the overall objective function are as follows:

[0066] Goal 1: Minimize fragmented time:

[0067]

[0068] Goal 2: Maximize the time between meetings:

[0069]

[0070] Overall goal:

[0071] Obj=w1*Obj1+w2*Obj2

[0072] Among them, P i is the level of the participants; S i is the starting time of the participant's free time period, E i is the end time of the free time period of the participants; S0 is the start time of the new meeting you want to schedule, and E0 is the end time of the new meeting you want to schedule; O j For other free time periods of the day; i is the weight (importance) of goal one and goal two.

[0073] Specifically, weights of the two goals are assigned according to the schedule of meetings and participants. Goal one is to minimize fragmented time, and goal two is to maximize meeting intervals. If a period of public free time is short, it means that the interval between two meetings is short, so the goal tends to choose to maximize the meeting interval to ensure that participants have a better rest between the two meetings; if the public free time is long, it means that the meeting interval is long, so the goal tends to choose to minimize fragmented time to ensure a long time period.

[0074] Step S3: using a simulated annealing algorithm to obtain the optimal value of the objective function according to the time arrangement of the meeting and the participants, and rescheduling the meeting time according to the optimal value.

[0075] Reference Figure 3 As shown, step S3 specifically includes the following contents:

[0076] Step S31: obtaining a number of common free time periods of the meeting and the participants according to the time arrangement of the meeting and the participants;

[0077] Step S32: using a simulated annealing algorithm to search in each section of the common idle time according to the objective function;

[0078] Step S33: returning the optimal value in each section of the public free time to the user, and rescheduling the meeting according to the optimal value.

[0079] Specifically, refer to Figure 4As shown, a simulated annealing algorithm is used to search in each section of public free time, and the optimal value in each section of public free time is returned to the user, allowing the user to decide for himself which time period to reschedule the meeting.

[0080] Reference Figure 5 As shown in Figure 2, the generation and acceptance of new solutions of the simulated annealing algorithm can be divided into the following four steps:

[0081] The first step is to generate a new solution in the solution space from the current solution using a generating function; in order to facilitate subsequent calculations and acceptance and reduce algorithm time consumption, a method is usually chosen that generates a new solution by simply transforming the current new solution.

[0082] The second step is to calculate the objective function difference corresponding to the new solution. Because the objective function difference is only generated by the transformation part, the calculation of the objective function difference is best calculated in increments.

[0083] The third step is to determine whether the new solution is accepted. The basis for the judgment is an acceptance criterion. The most commonly used acceptance criterion is the Metropolis criterion: if ΔT<0, accept S′ as the new current solution S; otherwise, accept S′ as the new current solution S with probability exp(-ΔT / T).

[0084] The fourth step is to replace the current solution with the new solution when the new solution is determined to be accepted. This only requires implementing the transformation part of the current solution corresponding to the generation of the new solution and correcting the objective function value. At this point, the current solution has achieved one iteration. The next round of experiments can be started on this basis. When the new solution is determined to be discarded, the next round of experiments will continue based on the original current solution. The simulated annealing algorithm has nothing to do with the initial value, and the solution obtained by the algorithm has nothing to do with the initial solution state S (which is the starting point of the algorithm iteration).

[0085] The simulated annealing algorithm has asymptotic convergence and has been theoretically proven to be a global optimization algorithm that converges to the global optimal solution with probability 1.

[0086] The present invention models the problem of intelligent conference arrangement suggestion as an operations optimization problem, takes minimizing fragmented time and maximizing meeting intervals as the goals, and provides a multi-objective optimization algorithm for solving the optimization problem.

[0087] Embodiment 2:

[0088] In combination with the method for intelligently suggesting a conference schedule disclosed in the first embodiment, this embodiment discloses a specific implementation example of an intelligently suggesting a conference schedule system (hereinafter referred to as the “system”).

[0089] Reference Figure 6 As shown, the system comprises:

[0090] Information acquisition unit 1: obtain the time schedule of the meeting and the participants;

[0091] Objective function construction unit 2: construct the objective function of multi-objective optimization consisting of minimizing the fragmentation time objective and maximizing the meeting interval objective;

[0092] Meeting scheduling unit 3: using a simulated annealing algorithm to obtain the optimal value of the objective function according to the time arrangement of the meeting and the participants, and rearranging the meeting time according to the optimal value.

[0093] Specifically, the objective function construction unit 2 includes:

[0094] Goal construction module 21: construct the goal of minimizing fragmented time and the goal of maximizing meeting interval according to the level of the participants and the time arrangement of the meeting and the participants;

[0095] The overall goal construction module 22 constructs the objective function according to the objective of minimizing the fragmented time and the objective of maximizing the meeting interval and the corresponding weights.

[0096] Specifically, the conference arrangement unit 3 includes:

[0097] Public free time acquisition module 31: obtains several sections of public free time of the meeting and the participants according to the time arrangement of the meeting and the participants;

[0098] A simulated annealing algorithm search module 32: uses a simulated annealing algorithm to search in each section of the common idle time according to the objective function;

[0099] The optimal value returning module 33 returns the optimal value in each section of the public free time to the user, and rearranges the meeting according to the optimal value.

[0100] Specifically, the overall goal construction module 22 allocates the weights of the goal of minimizing fragmented time and the goal of maximizing meeting interval in the objective function according to the time arrangement of the meeting and the participants.

[0101] For the technical solutions of the other parts of the intelligent conference schedule suggestion system disclosed in this embodiment and the intelligent conference schedule suggestion method disclosed in the first embodiment, please refer to the description of the first embodiment, which will not be repeated here.

[0102] Embodiment three:

[0103] Combination Figure 7 As shown, this embodiment discloses a specific implementation of a computer device. The computer device may include a processor 81 and a memory 82 storing computer program instructions.

[0104] Specifically, the processor 81 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application.

[0105] Among them, the memory 82 may include a large-capacity memory for data or instructions. By way of example and not limitation, the memory 82 may include a hard disk drive (HDD), a floppy disk drive, a solid-state drive (SSD), a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive, or a combination of two or more of these. Where appropriate, the memory 82 may include a removable or non-removable (or fixed) medium. Where appropriate, the memory 82 may be inside or outside the data processing device. In a specific embodiment, the memory 82 is a non-volatile memory. In a specific embodiment, the memory 82 includes a read-only memory (ROM) and a random access memory (RAM). Where appropriate, the ROM may be a mask-programmed ROM, a programmable ROM (Programmable Read-Only Memory, PROM for short), an erasable PROM (Erasable ProgrammableRead-Only Memory, EPROM for short), an electrically erasable PROM (Electrically Erasable ProgrammableRead-Only Memory, EEPROM for short), an electrically alterable ROM (Electrically Alterable Read-Only Memory, EAROM for short) or a flash memory (FLASH) or a combination of two or more of these. Under appropriate circumstances, the RAM can be a static random access memory (SRAM) or a dynamic random access memory (DRAM), wherein the DRAM can be a fast page mode dynamic random access memory (FPMDRAM), an extended data output dynamic random access memory (EDODRAM), a synchronous dynamic random access memory (SDRAM), etc.

[0106] The memory 82 may be used to store or cache various data files required for processing and / or communication, as well as possible computer program instructions executed by the processor 81 .

[0107] The processor 81 implements any one of the conference schedule intelligent suggestion methods in the above embodiments by reading and executing computer program instructions stored in the memory 82 .

[0108] In some of these embodiments, the computer device may further include a communication interface 83 and a bus 80. Figure 7 As shown, the processor 81, the memory 82, and the communication interface 83 are connected via a bus 80 and communicate with each other.

[0109] The communication interface 83 is used to implement communication between the modules, devices, units and / or equipment in the embodiment of the present application. The communication port 83 can also implement data communication with other components such as: external devices, image / data acquisition equipment, databases, external storage, and image / data processing workstations.

[0110] The bus 80 includes hardware, software or both, and couples the components of the computer device to each other. The bus 80 includes but is not limited to at least one of the following: a data bus, an address bus, a control bus, an expansion bus, and a local bus. By way of example and not limitation, bus 80 may include an Accelerated Graphics Port (AGP) or other graphics bus, an Extended Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a Hyper Transport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an InfiniBand interconnect, a Low Pin Count (LPC) bus, a memory bus, a Micro Channel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local Bus (VLB) bus, or other suitable buses or a combination of two or more of these. Where appropriate, bus 80 may include one or more buses. Although embodiments of the present application describe and illustrate a particular bus, the present application contemplates any suitable bus or interconnect.

[0111] In addition, in combination with the intelligent conference schedule suggestion method in the above embodiments, the present application embodiment can provide a computer-readable storage medium for implementation. The computer-readable storage medium stores computer program instructions; when the computer program instructions are executed by a processor, any one of the intelligent conference schedule suggestion methods in the above embodiments is implemented.

[0112] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0113] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A method for intelligently suggesting a meeting schedule, characterized in that: include: Information acquisition steps: obtain the time schedule of the meeting and the participants; Objective function construction steps: construct a multi-objective optimization objective function consisting of minimizing the fragmentation time objective and maximizing the meeting interval objective; Meeting arrangement step: using a simulated annealing algorithm to obtain the optimal value of the objective function according to the time arrangement of the meeting and the participants, and rescheduling the meeting time according to the optimal value; Among them, the objective function construction steps include: Goal construction step: construct the goal of minimizing fragmented time and the goal of maximizing meeting interval according to the level of the participants and the time arrangement of the meeting and the participants. Goal 1 is to minimize fragmented time: Goal 2 is to maximize the time between meetings: The overall goal construction step: constructing the objective function according to the objective of minimizing the fragmented time and the objective of maximizing the meeting interval and the corresponding weights, and the overall objective function is Obj=w1*Obj1+w2*Obj2; Among them, P i is the level of the participants; S i is the starting time of the participant's free time period, E i is the end time of the free time period of the participants; S0 is the start time of the new meeting you want to schedule, and E0 is the end time of the new meeting you want to schedule; O j For other free time periods of the day; i is the weight of goal one and goal two; The meeting arrangement steps include: Public free time acquisition step: acquiring a number of public free time periods of the meeting and the participants according to the schedule of the meeting and the participants; Simulated annealing algorithm search step: using the simulated annealing algorithm to search in each section of the common idle time according to the objective function, wherein the simulated annealing algorithm includes generating a new solution located in the solution space from the current solution by a generating function, calculating the objective function difference corresponding to the new solution, and judging whether the new solution is accepted. When the new solution is determined to be accepted, the new solution is used to replace the current solution. When the new solution is determined to be discarded, the next round of calculation is continued based on the original current solution. Optimal value returning step: returning the optimal value in each section of the public free time to the user, and rescheduling the meeting according to the optimal value.

2. A method for intelligently suggesting a meeting schedule according to claim 1, characterized in that: The weights of the objective of minimizing fragmented time and the objective of maximizing meeting interval in the objective function are allocated according to the time arrangement of the meeting and the participants.

3. A meeting schedule intelligent suggestion system, characterized in that: include: Information acquisition unit: obtain the time schedule of meetings and participants; Objective function construction unit: constructs a multi-objective optimization objective function consisting of minimizing the fragmentation time objective and maximizing the meeting interval objective; Meeting scheduling unit: using a simulated annealing algorithm to obtain the optimal value of the objective function according to the time arrangement of the meeting and the participants, and rescheduling the meeting time according to the optimal value; Among them, the objective function construction unit includes: Goal building module: construct the goal of minimizing fragmented time and the goal of maximizing meeting interval according to the level of the participants and the time arrangement of the meeting and the participants. Goal 1 is to minimize fragmented time: Goal 2 is to maximize the time between meetings: Overall goal construction module: construct the objective function according to the objective of minimizing the fragmentation time and the objective of maximizing the meeting interval and the corresponding weights, and the overall objective function is Obj=w1*Obj1+w2*Obj2; Among them, P i is the level of the participants; S i is the starting time of the participant's free time period, E i is the end time of the free time period of the participants; S0 is the start time of the new meeting you want to schedule, and E0 is the end time of the new meeting you want to schedule; O j For other free time periods of the day; i is the weight of goal one and goal two; The meeting arrangement unit includes: Public free time acquisition module: obtains several sections of public free time of the meeting and the participants according to the time arrangement of the meeting and the participants; Simulated annealing algorithm search module: using the simulated annealing algorithm to search in each section of the common idle time according to the objective function, wherein the simulated annealing algorithm includes generating a new solution in the solution space from the current solution by a generating function, calculating the objective function difference corresponding to the new solution, and judging whether the new solution is accepted. When the new solution is determined to be accepted, the new solution is used to replace the current solution. When the new solution is determined to be discarded, the next round of calculation is continued based on the original current solution; Optimal value returning module: returns the optimal value in each section of the public free time to the user, and rearranges the meeting according to the optimal value.

4. The intelligent conference schedule suggestion system according to claim 3, characterized in that: The overall goal building module allocates the weights of the goal of minimizing fragmented time and the goal of maximizing meeting interval in the objective function according to the time arrangement of the meeting and the participants.

5. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the conference schedule intelligent suggestion method according to any one of claims 1 to 2 is implemented.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the conference schedule intelligent suggestion method as described in any one of claims 1 to 2 is implemented.

Images