CN113887842B - Intelligent ladder-contracting method, system and equipment based on ant colony algorithm - Google Patents
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Abstract
The invention relates to an ant colony algorithm-based intelligent elevator-contracting method, system and equipment, wherein user requirements are acquired for sequencing, and a plurality of elevator transportation routes are formed in series based on sequencing results and the maximum passenger capacity of each elevator by adopting the ant colony algorithm and are fed back to users; the device comprises a memory, a processor for executing programs by adopting the method and a computer program which is stored on the memory and can run on the processor; the system obtains user requirements through the control end, obtains a final elevator stopping route, completes intelligent elevator contracting and feedback, and stops based on the intelligent elevator contracting result in a preset time period. The invention integrates and uniformly allocates all elevator taking requirements in a certain time period, and simplifies and processes the actual elevator taking conditions with complex changes; the regular operation of the elevator cannot be influenced under normal conditions, and the orderliness is stronger; the optimal solution can be more accurately found in limited memory and time resources; the method has the advantages of low requirement on hardware configuration, high solving efficiency and good algorithm convergence.
Description
Technical Field
The present invention relates to resource, workflow, personnel or project management, such as organizing, planning, scheduling or allocating time, personnel or machine resources; planning an enterprise; the technical field of organizational models, in particular to an ant colony algorithm-based intelligent ladder-contracting method, system and equipment.
Background
An elevator refers to a transportation device serving several specific floors in a building, which is widely used in the present high-rise building.
At present, generally all need the passenger to stand by the elevator when taking the elevator, by the manual upper and lower that can realize the elevator after pressing elevator floor button, this kind takes advantage of the mode and has following drawback:
(1) in the peak period of taking the elevator, due to the irregular running of the elevator, the waiting time is long, so that the efficiency is low, the normal time arrangement of passengers is easy to delay, and even delayed results are caused;
(2) the elevator is called and goes upstairs and downstairs by manually pressing the elevator button, so that the elevator is not sanitary and environment-friendly;
(3) on the way, some users may press wrong floors, and the like, and under the condition that the elevator is staggered for many times, a lot of inconvenience is brought to the life of the users, and the elevator runs out of order;
(4) elevator maintenance is not facilitated.
Disclosure of Invention
The invention solves the problems in the prior art and provides an optimized ant colony algorithm-based intelligent ladder-contracting method, system and equipment.
The technical scheme adopted by the invention is that the intelligent elevator-contracting method based on the ant colony algorithm is characterized in that the method obtains user requirements in a preset time period, sets a starting point and a terminal point corresponding to each elevator, carries out sequencing according to the user requirements, adopts the ant colony algorithm, and is based on a sequencing result and the maximum passenger capacity of each elevator, connected in series to form a plurality of elevator transportation routes and fed back to the user.
Preferably, the method comprises the steps of:
step 1: the user sends the user requirement to the control end, and the elevator taking plan comprises elevator taking time and associated departure floor and arrival floor; the control end acquires user requirements;
step 2: sequencing the user requirements in sequence; setting parameters;
and step 3: adopting an ant colony algorithm, obtaining a one-way elevator transportation route with the longest travel based on user requirements in a preset time period, and carrying out user requirement allocation by taking the highest floor or the lowest floor corresponding to the current elevator transportation route as a starting point and the lowest floor or the highest floor as an end point;
and 4, step 4: if all the user requirements in the current preset time period are met, performing the next step; if the user requirements are not completely met, obtaining a one-way elevator transportation route with the longest next travel, taking the highest floor or the lowest floor corresponding to the elevator transportation route as a starting point and the lowest floor or the highest floor as a terminal point, carrying out user requirement allocation, and repeating the step 4;
and 5: generating an elevator stopping route based on the user demand allocation;
step 6: calculating the minimum no-load value between the elevator stopping route and the user trip demand time window, and solving by taking the minimum no-load value as a target; and obtaining a final elevator stopping route, finishing intelligent elevator booking and feeding back to the user.
Preferably, in the step 2, parameters are initialized, the parameters include a total number N of ants in an ant colony, a total path number K, a maximum iteration number iter, a path pheromone factor τ between any parking floor and any elevator transportation route, and a pheromone variation Δ τ; respectively initializing a path pheromone factor tau and a corresponding pheromone volatilization factor delta tau to be 0, and setting the current iteration frequency to be 0.
Preferably, in step 3 and step 4, the user requirement allocation includes the following steps:
step S.1: according to the user requirements, confirming the starting time and the ending time of the requirements, sequencing the passenger trip demand points by the intermediate value of the starting time and the ending time, and placing N ant individuals at the starting point of the sequence;
step S.2: a set of ant colony candidate paths is generated,
where i corresponds to the stop level, K is the set of all paths, γ (K) is the next stop level on path K immediately following stop level i, eγ(k)And lγ(k)Respectively corresponding start time and end time of the stop layer, eiAnd liRespectively corresponding start time and end time of the parking layer i;
step S.3: determining an ant individual transfer path based on the candidate path set;
step S.4: return to step s.2 until all stopping floors have been allocated on the elevator transportation route.
Preferably, in step s.3, a random number q is taken, and a preset parameter q is set0，q0∈(0,1]；
If q is less than or equal to q0Then ant selects tauiγ(k)(t) the k-th path with the maximum value is taken as the next transfer path;
if q > q0Then a probability value p is calculated,
the ant takes the kth path with the maximum probability value in the selected path set as a transfer path of the next step;
wherein, tauiγ(k)(t) is a path pheromone factor between a stop layer immediately following the stop layer i on the kth path at time t and the stop layer i, and α is a pheromone relative influence degree factor.
Preferably, the step 6 comprises the steps of:
step 6.1: determining the pheromone variation quantity delta tau on each path;
step 6.2: updating an pheromone factor tau (t +. DELTA.t) ═ 1-rho (t) +. DELTA.tau based on the pheromone variation, wherein rho is an evaporation coefficient of the pheromone on the path, and rho is epsilon (0, 1);
step 6.3: storing the current allocation scheme, judging whether the current allocation scheme is the optimal solution in the current ant colony, namely the no-load value is the minimum, if not, returning to the step S.2 to calculate the next ant, otherwise, performing the next step;
step 6.4: and updating the pheromone factor on the global path, judging whether the current solution is the optimal solution in all iteration times, if not, adding 1 to the iteration times, returning to the step S.1 to carry out a new iteration, and if not, considering the current solution as the global optimal solution.
Preferably, the first and second electrodes are formed of a metal,
wherein, Δ τjRepresenting the pheromone variation left by the jth ant in the iteration.
Preferably, in step 6, the minimum empty load value is set to 1 when no person is in the elevator between any adjacent stopping floors in all elevator transportation routes, and all 1 s are added to obtain the minimum sum value.
A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor executing the program based on the intelligent ant colony algorithm-based approach to stairs.
The system of the intelligent ladder-contracting method based on the ant colony algorithm comprises the following steps:
the system comprises a plurality of user sides, a form page and a user interface, wherein the user sides are used for providing the form page and providing user requirements based on the form page;
the control end is used for acquiring user requirements, acquiring a final elevator stopping route based on the user requirements, completing intelligent elevator booking and feeding back the intelligent elevator booking to the user;
and the one or more elevators are used for obtaining the intelligent elevator-booking result of the control end and stopping based on the intelligent elevator-booking result in a preset time period.
The invention provides an optimized ant colony algorithm-based intelligent elevator-contracting method, system and equipment, wherein user requirements in a preset time period are obtained, a starting point and an end point corresponding to each elevator are set, sequencing is carried out according to the user requirements, an ant colony algorithm is adopted, a plurality of elevator transportation routes are formed in series based on a sequencing result and the maximum passenger capacity of each elevator, and the elevator transportation routes are fed back to a user; the device comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, wherein the processor executes the program by adopting the method; the system provides form pages by a plurality of user terminals, users propose user requirements based on the form pages, a control terminal obtains the user requirements and obtains a final elevator stopping route based on the user requirements, intelligent elevator booking is completed and fed back to the users, and the elevators stop based on the intelligent elevator booking results in a preset time period after the intelligent elevator booking results of the control terminal are obtained.
The invention has the beneficial effects that:
(1) integrating all elevator taking requirements in a certain time period and then uniformly allocating, and simplifying the real elevator taking conditions with complex changes; the regular operation of the elevator cannot be influenced under normal conditions, and the orderliness is stronger;
(2) the optimal solution can be more accurately found in limited memory and time resources;
(3) the method has the advantages of low requirement on hardware configuration, high solving efficiency and good algorithm convergence.
Drawings
FIG. 1 is a flow chart of the present invention;
FIG. 2 is a system structure diagram of the present invention, wherein arrows indicate the transmission direction of data and control signals;
FIG. 3 illustrates the system of the present invention acquiring authorization for elevator functions;
fig. 4 is a flowchart of an APP one-key escalator in an embodiment of the invention.
Detailed Description
The present invention is described in further detail with reference to the following examples, but the scope of the present invention is not limited thereto.
The invention relates to an ant colony algorithm-based intelligent elevator-contracting method, which comprises the steps of obtaining user requirements in a preset time period, setting a starting point and a terminal point corresponding to each elevator, sequencing according to the user requirements, adopting an ant colony algorithm, connecting a plurality of elevator transportation routes in series based on a sequencing result and the maximum passenger capacity of each elevator, and feeding back the elevator transportation routes to users.
The invention, as a whole, comprises several parts:
(1) acquiring user requirements and elevator states; the starting point and the terminal point corresponding to each elevator are set, namely, part of the elevators can be high-rise elevators or low-rise elevators, namely, the elevators only run between high floors or low floors and are suitable for different elevator riding requirements and configurations in high-rise buildings;
(2) sequencing according to the requirements of users, wherein the sequencing refers to the sequencing of taking the elevator by the users;
(3) by means of the ant colony algorithm, based on the sequencing result and the maximum passenger load of each elevator, several elevator transportation routes are connected in series, in which routes certain objectives or conditions obviously need to be met, so that some elevators are converted from ordinary elevators to "special elevators", in which elevators only limited persons can enter from a limited landing floor within a limited period of time, in principle there is no special restriction on exiting the elevator, but after exiting the elevator, the persons still need to follow established rules when entering other elevators.
According to the elevator transfer system, under the reasonable operation setting, short-time transfer among different high-rise buildings, high-rise elevators and low-rise elevators can be realized, so that the time of a user is saved to the greatest extent, and the elevator transfer system is favorable for planning elevator transfer plans for the user.
As shown in fig. 1, it is an embodiment 1 of the intelligent ladder-closing method based on the ant colony algorithm;
in example 1:
step 1: the user sends the user requirement to the control terminal, and the elevator taking plan comprises elevator taking time and associated departure floor and arrival floor, such as 8: 40-8: 50, starting layer F1, reaching layer F8 "; and the control terminal acquires the user requirements.
Step 2: sequencing the user requirements in sequence; setting parameters; wherein the parameters are all necessary parameters in the ant colony algorithm;
the ordering of the user requirements mainly refers to setting a time window for the elevator taking time in the user requirements, in fact, all the time in the time window can be regarded as the selected elevator taking time, the elevator taking time is ordered and set to different lines, and the corresponding lines must cover the departure floor and the arrival floor of the elevator taking plan.
And step 3: adopting an ant colony algorithm, obtaining a one-way elevator transportation route with the longest travel based on user requirements in a preset time period, and carrying out user requirement allocation by taking the highest floor or the lowest floor corresponding to the current elevator transportation route as a starting point and the lowest floor or the highest floor as an end point;
and 4, step 4: if all the user requirements in the current preset time period are met, performing the next step; if the user requirements are not completely met, obtaining a one-way elevator transportation route with the longest next travel, taking the highest floor or the lowest floor corresponding to the elevator transportation route as a starting point and the lowest floor or the highest floor as a terminal point, carrying out user requirement allocation, and repeating the step 4;
in the invention, the user requirement distribution is firstly carried out by the elevator transportation route with the longest one-way travel, and then the user requirement distribution is carried out by the next longest elevator transportation route.
For example, 5 users need to take the elevator in the current time period, and it is assumed that the number of people on the elevator load is 3, and the elevator taking requirements of the 5 users are respectively:
user 1, departed level F3, reached level F24;
user 2, departed level F5, arrived level F15;
user 3, departed level F10, arrived level F12;
user 4, departed level F24, arrived level F10;
user 5, departed level F11, arrived level F18;
based on the method, firstly, the one-way elevator transportation route with the longest travel, namely the departure floor F3, is taken to arrive at the floor F24, and the one-way elevator transportation route with the next longest travel, namely the departure floor F5, is prepared to arrive at the floor F15;
in the process, at most no more than 3 persons in the elevator car are allocated, and at least two schemes are provided;
the first scheme is as follows:
an elevator transportation route 1, a departure floor F3 and a arrival floor F24, wherein a door is opened at F3, a user 1 enters, a door is opened at F10, a user 3 enters, a door is opened at F12, a user 3 leaves, a door is opened at F11, a user 5 enters, a door is opened at F18, a user 5 leaves, a door is opened at F24, and a user 1 leaves;
elevator route 2, departure floor F5, arrival floor F24, then descent to F10; open the door at F5, user 2 enters, open the door at F15, user 2 leaves; no load is carried to F24, the user 4 enters and descends, the door is opened at F10, and the user 4 leaves;
scheme II:
an elevator transportation route 1, a departure floor F3 and a arrival floor F24, wherein a door is opened at F3, a user 1 enters, a door is opened at F5, a user 2 enters, a door is opened at F11, a user 5 enters, a door is opened at F15, a user 2 leaves, a door is opened at F18, a user 5 leaves, a door is opened at F24, and a user 1 leaves;
elevator route 2, departure floor F24, arrival floor F10, then upward to F12; opening a door at F24, enabling the user 4 to enter, opening a door at F10, enabling the user 4 to leave, enabling the user 3 to enter and go upwards, and opening a door at F12, enabling the user 3 to leave;
obviously, the transportation route schemes of the elevator are very many, except the two schemes, only taking the scheme two as an example, under the premise that a time window allows, the elevator transportation route 1 and the elevator transportation route 2 can be jointed, and finally, the whole transportation is carried by one elevator transportation route; therefore, an ant colony algorithm is provided, and optimization processing is realized.
And 5: generating an elevator stopping route based on the user demand allocation;
step 6: calculating the minimum no-load value between the elevator stopping route and the user trip demand time window, and solving by taking the minimum no-load value as a target; and obtaining a final elevator stopping route, finishing intelligent elevator booking and feeding back to the user.
In the embodiment, the elevator transportation route is solved by taking the minimum no-load value as a target, and after the solution is completed, the intelligent elevator-saving result is fed back to the user.
On the basis of the above embodiment, in the step 2, the initialized parameters include the total number N of ants in the ant colony, the total path amount K, the maximum iteration number iter, the path pheromone factor τ between any landing floor and any elevator transportation route, and the pheromone variation Δ τ; respectively initializing a path pheromone factor tau and a corresponding pheromone volatilization factor delta tau to be 0, and setting the current iteration frequency to be 0.
In the invention, all paths of the whole ant colony form a solution space of a problem to be optimized, the quantity of pheromones released by ants with shorter paths is more, the concentration of the pheromones accumulated on the shorter paths is gradually increased along with the advance of time, and the quantity of ants selecting the paths is increased more and more; finally, the whole ant can be concentrated on the optimal path under the action of positive feedback, and the optimal solution of the problem to be optimized corresponds to the ant;
on the basis, N and K respectively correspond to the total number of ants in an ant colony and the total number of corresponding paths, each path is continuously calculated in an iterative mode, the pheromone concentration is updated, the maximum iteration times are limited, the pheromone factor refers to pheromones left by the ants after the ants pass through the paths and is used for accumulating the selected probability of a certain road section, and the pheromone variable quantity is used for pointing to the increment of the pheromone on the certain path so as to confirm the forward feedback of the certain path.
On the basis of the above embodiment, in the step 3 and the step 4, the user requirement allocation includes the following steps:
step S.1: according to the user requirements, confirming the starting time and the ending time of the requirements, sequencing the passenger trip demand points by the intermediate value of the starting time and the ending time, and placing N ant individuals at the starting point of the sequence;
step S.2: a set of ant colony candidate paths is generated,
where i corresponds to the stop level, K is the set of all paths, γ (K) is the next stop level on path K immediately following stop level i, eγ(k)And lγ(k)Respectively corresponding start time and end time of the stop layer, eiAnd liRespectively corresponding start time and end time of the parking layer i;
step S.3: determining an ant individual transfer path based on the candidate path set;
in step S.3, a random number q is taken, and a preset parameter q is ordered0，q0∈(0,1]；
If q is less than or equal to q0Then ant selects tauiγ(k)(t) the k-th path with the maximum value is taken as the next transfer path;
if q > q0Then a probability value p is calculated,
the ant takes the kth path with the maximum probability value in the selected path set as a transfer path of the next step;
wherein, tauiγ(k)(t) is a path pheromone factor between a stop layer immediately following the stop layer i on the kth path at time t and the stop layer i, and α is a pheromone relative influence degree factor.
Step S.4: return to step s.2 until all stopping floors have been allocated on the elevator transportation route.
In the method, whether a certain ant individual selects the kth path as a travel route or not is judged according to a generation rule of an ant colony candidate path set, wherein the rule indicates that the ant selects the kth path to transfer to the next position only when a condition is met.
In the invention, a random number q and a preset parameter q0When k is such that τ isiγ(k)(t) when the value reaches the maximum path label, the ant will select the kth path, and in practical application, the parameters of the attraction degree of the ant can be matched for optimal setting; otherwise, selecting the path with the maximum probability value in the path set as the next transfer path according to the probability value p.
On the basis of the above embodiment, the step 6 includes the following steps:
step 6.1: determining the pheromone variation quantity delta tau on each path;
Step 6.2: updating an pheromone factor tau (t +. DELTA.t) ═ 1-rho (t) +. DELTA.tau based on the pheromone variation, wherein rho is an evaporation coefficient of the pheromone on the path, and rho is epsilon (0, 1);
step 6.3: storing the current allocation scheme, judging whether the current allocation scheme is the optimal solution in the current ant colony, namely the no-load value is the minimum, if not, returning to the step S.2 to calculate the next ant, otherwise, performing the next step;
step 6.4: and updating the pheromone factor on the global path, judging whether the current solution is the optimal solution in all iteration times, if not, adding 1 to the iteration times, returning to the step S.1 to carry out a new iteration, and if not, considering the current solution as the global optimal solution.
On the basis of the above embodiment, in the step 6, the minimum empty load value is set to 1 when no person is in the elevator between any adjacent stopping floors in all elevator transportation routes, and all 1 s are added to obtain the minimum sum value.
In order to implement the above embodiments, a computer-readable storage medium is provided, on which an ant colony algorithm-based intelligent elevator-booking program is stored, and when the program is executed by a processor, the ant colony algorithm-based intelligent elevator-booking method is implemented, which mainly solves the problem of unordered elevator-booking in the prior art, so that a user can successfully board an elevator from a departure floor to an arrival floor within a planning time.
In order to implement the above embodiments, the present invention further relates to a computer device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program, and the intelligent ladder-contracting method based on the ant colony algorithm is provided.
In order to implement the above embodiments, as shown in fig. 2 and fig. 3, the present invention further relates to a system of the intelligent ladder-closing method based on the ant colony algorithm, including:
the system comprises a plurality of user sides, a form page and a user interface, wherein the user sides are used for providing the form page and providing user requirements based on the form page;
the control end is used for acquiring user requirements, acquiring a final elevator stopping route based on the user requirements, completing intelligent elevator booking and feeding back the intelligent elevator booking to the user;
and the one or more elevators are used for obtaining the intelligent elevator-booking result of the control end and stopping based on the intelligent elevator-booking result in a preset time period.
In the system, a controller applies function authorization to the elevator, and if the authorization is successful, the controller acquires the up-down command authority of the elevator, controls the starting floor, the arriving floor and the stopping floor of the elevator at preset time, and can acquire information of the safety condition, the running state, the running speed and the arriving floor of the elevator.
In order to implement the above-described embodiment, as shown in fig. 4, in the system of the present invention, all function authorizations of the elevators are acquired, and big data calculation is performed. The user operates on the APP of cell-phone, need not to touch the elevator button, can advance a key reservation elevator from top to bottom.
When a user selects an elevator of a specific building, the appointment time, the current floor and the destination floor on the APP, and the API is called successfully, the control end generates an elevator appointment work order, and sends a call calling instruction to the authorized elevator at the appointed time, so that the elevator can automatically reach the user floor.
The user can look over reservation elevator place floor on APP, look over the time that still needs to wait at present, when the elevator arrives soon, APP can also remind the user to make preparation in advance in order to avoid missing the elevator, if every 15s voice broadcast elevator reachs the remaining time, the voice broadcast elevator has arrived, still can show current elevator safety situation, service conditions on the APP, to special weather condition, APP can also remind the user, if take the umbrella, save the time that the user went upstairs and downstairs, it is convenient to bring for user's life.
If the elevator has operation failure and safety problems temporarily, the user is reminded to make an appointment again, and the sectional type appointment can be expanded in the later period, so that the rapid taking of different elevators in the floors is realized.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (6)
1. An intelligent ladder-contracting method based on an ant colony algorithm is characterized in that: the method comprises the steps of obtaining user requirements in a preset time period, setting a starting point and a terminal point corresponding to each elevator, sequencing according to the user requirements, adopting an ant colony algorithm, connecting a plurality of elevator transportation routes in series based on a sequencing result and the maximum passenger capacity of each elevator, and feeding back the elevator transportation routes to users;
the method comprises the following steps:
step 1: a user sends a user demand to a control end, wherein the user demand comprises elevator taking time and associated departure floor and arrival floor; the control end acquires user requirements;
step 2: sequencing the user requirements in sequence; setting parameters;
and step 3: adopting an ant colony algorithm, obtaining a one-way elevator transportation route with the longest travel based on user requirements in a preset time period, and carrying out user requirement allocation by taking the highest floor or the lowest floor corresponding to the current elevator transportation route as a starting point and the lowest floor or the highest floor as an end point; the user demand allocation comprises the following steps:
step S.1: according to the user requirements, confirming the starting time and the ending time of the requirements, sequencing the passenger trip demand points by the intermediate value of the starting time and the ending time, and placing N ant individuals at the starting point of the sequence;
step S.2: a set of ant colony candidate paths is generated,
where i corresponds to the stop level, K is the set of all paths, γ (K) is the next stop level on path K immediately following stop level i, eγ(k)And lγ(k)Respectively corresponding start time and end time of the stop layer, eiAnd liRespectively corresponding start time and end time of the parking layer i;
step S.3: determining an ant individual transfer path based on the candidate path set;
step S.4: returning to the step S.2 until all the stopping floors are allocated to the elevator transportation route;
and 4, step 4: if all the user requirements in the current preset time period are met, performing the next step; if the user requirements are not completely met, obtaining a one-way elevator transportation route with the longest next travel, taking the highest floor or the lowest floor corresponding to the elevator transportation route as a starting point and the lowest floor or the highest floor as a terminal point, carrying out user requirement allocation, and repeating the step 4;
and 5: generating an elevator stopping route based on the user demand allocation;
step 6: calculating the minimum no-load value between the elevator stopping route and the user trip demand time window, and solving by taking the minimum no-load value as a target; the step 6 comprises the following steps:
step 6.1: determining the pheromone variation quantity delta tau on each path;
step 6.2: updating an pheromone factor tau (t +. DELTA.t) ═ 1-rho (t) +. DELTA.tau based on the pheromone variation, wherein rho is an evaporation coefficient of the pheromone on the path, and rho is epsilon (0, 1);
step 6.3: storing the current allocation scheme, judging whether the current allocation scheme is the optimal solution in the current ant colony, namely the no-load value is the minimum, if not, returning to the step S.2 to calculate the next ant, otherwise, performing the next step;
step 6.4: updating the pheromone factor on the global path, judging whether the pheromone factor is the optimal solution in all iteration times, if not, adding 1 to the iteration times, returning to the step S.1 to carry out a new iteration, otherwise, considering the current solution as the global optimal solution;
the minimum no-load value is that the situation that no person exists in the elevator between any adjacent stopping floors in all elevator transportation routes is 1, all 1 s are added, and the obtained sum value is minimum; and obtaining a final elevator stopping route, finishing intelligent elevator booking and feeding back to the user.
2. The intelligent ladder-contracting method based on the ant colony algorithm as claimed in claim 1, wherein: in the step 2, initializing parameters, wherein the parameters comprise the total number N of ants in an ant colony, the total path K, the maximum iteration number iter, a path pheromone factor tau between any stopping layer and any elevator transportation route, and pheromone variation delta tau; respectively initializing a path pheromone factor tau and a corresponding pheromone variation delta tau to be 0, and setting the current iteration frequency to be 0.
3. The intelligent ladder-contracting method based on the ant colony algorithm as claimed in claim 1, wherein: in step S.3, a random number q is taken, and a preset parameter q is ordered0，q0∈(0,1]；
If q is less than or equal to q0Then ant selects tauiγ(k)(t) the k-th path with the maximum value is taken as the next transfer path;
if q > q0Then a probability value p is calculated,
the ant takes the kth path with the maximum probability value in the selected path set as a transfer path of the next step;
wherein, tauiγ(k)(t) is a path pheromone factor between a stop layer immediately following the stop layer i on the kth path at time t and the stop layer i, and α is a pheromone relative influence degree factor.
4. The intelligent ladder-contracting method based on the ant colony algorithm as claimed in claim 1, wherein:
wherein, Δ τjRepresenting the pheromone variation left by the jth ant in the iteration.
5. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor executes the program based on the ant colony algorithm based intelligent escalator approach as claimed in any one of claims 1 to 4.
6. A system adopting the ant colony algorithm-based intelligent elevator-contracting method as claimed in any one of claims 1 to 4, wherein: the method comprises the following steps:
the system comprises a plurality of user sides, a form page and a user interface, wherein the user sides are used for providing the form page and providing user requirements based on the form page;
the control end is used for acquiring user requirements, acquiring a final elevator stopping route based on the user requirements, completing intelligent elevator booking and feeding back the intelligent elevator booking to the user;
and the one or more elevators are used for obtaining the intelligent elevator-booking result of the control end and stopping based on the intelligent elevator-booking result in a preset time period.
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