CN115587742A - Vehicle entrance and exit scheduling method and device for logistics station - Google Patents
Vehicle entrance and exit scheduling method and device for logistics station Download PDFInfo
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Abstract
The application discloses a method and a device for scheduling vehicles entering and leaving a logistics station, belonging to the technical field of scheduling management, wherein the method comprises the following steps: acquiring a plurality of logistics vehicles to enter a target logistics station, and constructing a first constraint condition; acquiring index parameters of a plurality of logistics vehicles according to a plurality of logistics distribution indexes to obtain a plurality of index parameter sets; acquiring the capacity of a loading area and the capacity of an area to be loaded in a target logistics field station, acquiring first capacity information and second capacity information, and constructing a second constraint condition; randomly selecting and combining the sequence of a plurality of logistics vehicles entering a to-be-loaded area and a loading area to obtain a plurality of scheduling schemes; and carrying out dual-target optimization on the multiple scheduling schemes to obtain an optimal scheduling scheme for scheduling. The system and the method solve the technical problems that in the prior art, the vehicle scheduling intelligence degree of the logistics field station is low, and the scheduling efficiency is low, achieve the technical effects of improving scheduling coordination of the logistics field station and improving the logistics speed.
Description
Technical Field
The application relates to the technical field of scheduling management, in particular to a vehicle entrance and exit scheduling method and device for a logistics station.
Background
With the development of economy, the logistics industry in China is rapidly growing, the logistics operation amount is continuously growing, and higher requirements are put forward on the dispatching capacity of logistics stations. With the rapid increase of the traffic volume, the study on the vehicle dispatching condition of the logistics station has very important significance for improving the stable and rapid development of economy.
At present, vehicles in a logistics yard are mainly dispatched and managed manually, the sequence of the vehicles entering and exiting the logistics yard is determined according to task information of the vehicles, and the parking positions and the parking time of the logistics vehicles are controlled by workers in the yard. However, in the actual logistics field scheduling process, because the number of vehicles entering and exiting from the logistics field is large, the vehicles are easily jammed in the field only by manual management. And the efficiency of manual management is low, the information communication between the stations is not smooth, the scheduling scheme is limited by the capability of management personnel, and the vehicles in the station cannot be efficiently scheduled. The technical problems of low vehicle scheduling intelligence degree and low scheduling efficiency of the logistics stations in the prior art are solved.
Disclosure of Invention
The application aims to provide a vehicle access scheduling method and device for a logistics field station, and the method and device are used for solving the technical problems that in the prior art, vehicle scheduling of the logistics field station is low in intelligentization degree and scheduling efficiency.
In view of the foregoing problems, the present application provides a method and an apparatus for scheduling entry and exit of vehicles in a logistics yard.
In a first aspect, the present application provides a vehicle access scheduling method for a logistics yard, wherein the method includes: acquiring a plurality of logistics vehicles to enter a target logistics station; acquiring index parameters of the plurality of logistics vehicles according to a plurality of logistics distribution indexes to obtain a plurality of index parameter sets; acquiring the capacity of a loading area and the capacity of a to-be-loaded area in the target logistics field station, and acquiring first capacity information and second capacity information; constructing a first constraint condition according to the plurality of logistics vehicles; constructing a second constraint condition according to the first capacity information and the second capacity information; randomly selecting and combining the sequence of the plurality of logistics vehicles entering the area to be loaded and the loading area to obtain a plurality of scheduling schemes; and performing dual-target optimization on the plurality of scheduling schemes according to the first constraint condition, the second constraint condition and the plurality of index parameter sets to obtain an optimal scheduling scheme for scheduling, wherein the dual-target optimization comprises the steps of increasing the overall logistics speed of the plurality of logistics vehicles and increasing the logistics speed of each logistics vehicle.
On the other hand, this application still provides a vehicle access scheduling device of logistics field station, wherein, the device includes: the system comprises a logistics vehicle obtaining module, a logistics vehicle obtaining module and a logistics vehicle monitoring module, wherein the logistics vehicle obtaining module is used for obtaining a plurality of logistics vehicles to enter a target logistics station; the system comprises an index parameter acquisition module, a data acquisition module and a data processing module, wherein the index parameter acquisition module is used for acquiring index parameters of a plurality of logistics vehicles according to a plurality of logistics distribution indexes to obtain a plurality of index parameter sets; the system comprises a capacity information acquisition module, a capacity information acquisition module and a capacity information acquisition module, wherein the capacity information acquisition module is used for acquiring the capacity of a loading area and the capacity of an area to be loaded in the target logistics field station to acquire first capacity information and second capacity information; a first constraint condition construction module, configured to construct a first constraint condition according to the plurality of logistics vehicles; the second constraint condition construction module is used for constructing a second constraint condition according to the first capacity information and the second capacity information; the dispatching scheme obtaining module is used for randomly selecting and combining the sequence of the plurality of logistics vehicles entering the area to be loaded and the loading area to obtain a plurality of dispatching schemes; and the optimal scheduling scheme obtaining module is used for performing dual-target optimization on the plurality of scheduling schemes according to the first constraint condition, the second constraint condition and the plurality of index parameter sets to obtain an optimal scheduling scheme for scheduling, wherein the dual-target optimization comprises the steps of improving the overall logistics speed of the plurality of logistics vehicles and improving the logistics speed of each logistics vehicle.
One or more technical solutions provided in the present application have at least the following technical effects or advantages:
according to the method, a plurality of logistics vehicle information to enter a target logistics station is collected, and then index parameter collection is carried out according to a plurality of logistics distribution indexes to obtain a plurality of index parameter sets; then, acquiring the capacity of a loading area and the capacity of an area to be loaded in the target logistics field station to obtain corresponding first capacity information and second capacity information; further constructing a first constraint condition according to the plurality of logistics vehicles; constructing a second constraint condition according to the first capacity information and the second capacity information; randomly selecting and combining the sequence of a plurality of logistics vehicles entering a region to be loaded and a loading region to obtain a plurality of scheduling schemes; and then performing dual-target optimization on the plurality of scheduling schemes according to the first constraint condition, the second constraint condition and the plurality of index parameter sets to obtain an optimal scheduling scheme for scheduling, wherein the dual-target optimization comprises the steps of increasing the overall logistics speed of the plurality of logistics vehicles and increasing the logistics speed of each logistics vehicle. The technical effects of carrying out logistics scheduling from two angles of a loading area and a to-be-loaded area, carrying out double-target optimization on a plurality of scheduling schemes, intelligently searching for an optimal scheduling scheme, improving scheduling efficiency and further improving logistics speed are achieved.
Drawings
In order to more clearly illustrate the technical solutions in the present application or the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only exemplary, and for those skilled in the art, other drawings can be obtained according to the provided drawings without inventive effort.
Fig. 1 is a schematic flowchart of a vehicle access scheduling method for a logistics yard according to an embodiment of the present disclosure;
fig. 2 is a schematic flowchart illustrating a first constraint condition established in a vehicle access scheduling method for a logistics yard station according to an embodiment of the present application;
fig. 3 is a schematic flowchart illustrating a second constraint condition constructed in a vehicle entrance and exit scheduling method for a logistics yard according to an embodiment of the present application;
fig. 4 is a schematic structural diagram of a vehicle entrance and exit scheduling device of a logistics yard station according to the present application.
Description of the reference numerals: the system comprises a logistics vehicle obtaining module 11, an index parameter collecting module 12, a capacity information obtaining module 13, a first constraint condition constructing module 14, a second constraint condition constructing module 15, a scheduling scheme obtaining module 16 and an optimal scheduling scheme obtaining module 17.
Detailed Description
The application provides a vehicle access scheduling method and device for a logistics field station, and solves the technical problems that in the prior art, vehicle scheduling of the logistics field station is low in intelligentization degree and scheduling efficiency. The system has the advantages that the vehicle in-out dispatching efficiency of the logistics yard is achieved, and the technical effect of improving the vehicle transportation efficiency is further achieved.
According to the technical scheme, the data acquisition, storage, use, processing and the like meet the relevant regulations of national laws and regulations.
In the following, the technical solutions in the present application will be clearly and completely described with reference to the accompanying drawings, and it is to be understood that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments of the present application, and it is to be understood that the present application is not limited by the example embodiments described herein. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments of the present application without making any creative effort belong to the protection scope of the present application. It should be further noted that, for the convenience of description, only some but not all of the relevant portions of the present application are shown in the drawings.
Example one
As shown in fig. 1, the present application provides a vehicle entrance and exit scheduling method for a logistics yard, wherein the method includes:
step S100: acquiring a plurality of logistics vehicles to enter a target logistics station;
specifically, the target logistics station refers to any station where vehicle access scheduling is to be performed. The plurality of logistics vehicles are vehicles ready to enter the target logistics station, and the models, specifications and transport products of the plurality of logistics vehicles can be different. Basic analysis data are provided for subsequent analysis of the logistics vehicles by obtaining the basic information of the logistics vehicles, including the capacity, the models and the like of the logistics vehicles, and the technical effect of providing the dispatching target of the logistics station is achieved.
Step S200: acquiring index parameters of the plurality of logistics vehicles according to a plurality of logistics distribution indexes to obtain a plurality of index parameter sets;
further, according to a plurality of logistics distribution indexes, index parameters of the plurality of logistics vehicles are collected, and step S200 in the embodiment of the present application further includes:
step S210: acquiring a plurality of logistics distribution indexes, wherein the logistics distribution indexes comprise loading time indexes and logistics requirement time indexes;
step S220: and acquiring index parameters of the plurality of logistics vehicles based on the loading time index and the logistics required time index to obtain a plurality of index parameter sets.
Specifically, the plurality of logistics distribution indexes are indexes for measuring transportation circulation in the logistics transportation process, and include loading time indexes and logistics required time indexes. The loading time index refers to the time length from loading of the plurality of logistics vehicles to loading of the transported goods, namely the time consumed by the transported vehicles in the transportation station, and is determined according to the specification, the model and the type of the logistics vehicles. The logistics required time index is the longest time index of detention in the target logistics site determined according to the respective order requirements of a plurality of logistics vehicles. For example, a medium-sized truck may transport apples from a post station in zheng to an angyang within a day from 8 am to 8 pm. The round-trip transportation time from Zhengzhou to Anyang is 2 hours, the apple unloading at Anyang requires 1 hour, and the residence time of the medium-sized and large truck at Zhengzhou logistics site is 6 hours at most.
Specifically, index parameter acquisition is carried out on the plurality of logistics vehicles according to the loading time indexes and the logistics required time indexes, namely, the plurality of loading time index parameters and the plurality of logistics required time index parameters are determined according to the specifications and the models of the plurality of logistics vehicles and the transportation tasks. The index parameter sets reflect the time parameter acquisition results of the logistics vehicles from the aspects of loading time and logistics requirements, and comprise a plurality of loading time index parameters and a plurality of logistics requirement time index parameters. The loading time index parameters refer to loading residence time of the plurality of transport vehicles in the target logistics field station. The plurality of logistics required time index parameters refer to the longest residence time of the plurality of transport vehicles in the station, which is calculated according to the transport task requirements. Therefore, the technical effects of obtaining the residence time of a plurality of transport vehicles at two angles in the station and improving the accuracy of vehicle scheduling are achieved.
Step S300: acquiring the capacity of a loading area and the capacity of a to-be-loaded area in the target logistics field station, and acquiring first capacity information and second capacity information;
specifically, the area to be loaded is an area where the logistics vehicles are in a parking waiting state in the target logistics field, the loading area is an area where the logistics articles are loaded, the first capacity information refers to the number of vehicles that can be accommodated when the area to be loaded in the target logistics field is fully loaded, and the second capacity information refers to the number of vehicles that can be accommodated when the area to be loaded in the target logistics field is fully loaded. According to the first capacity information and the second capacity information, the designed vehicle containing information of the target logistics site can be obtained, and basis is provided for the subsequent scheduling range, so that the technical effects of vehicle scheduling according to the capacity condition of the target logistics site and data support provided for utilizing site resources to the maximum extent are achieved.
Step S400: constructing a first constraint condition according to the plurality of logistics vehicles;
further, as shown in fig. 2, a first constraint condition is constructed according to the plurality of logistics vehicles, and step S400 in the embodiment of the present application further includes:
step S410: acquiring the number of logistics vehicles needing to be scheduled in a preset time range by the target logistics station, and acquiring total scheduling number information;
step S420: obtaining a time range required for logistics processing of the plurality of logistics vehicles according to the total scheduling quantity information, the plurality of logistics vehicles and the preset time range;
step S430: constructing the first constraint condition that a total time required for the logistics processing of the plurality of logistics vehicles falls within the required time range.
Specifically, the preset time range is a preset time range for vehicle scheduling at the target logistics site, and optionally, the time range may be one day, half day, and the like. The total scheduling quantity information is determined according to the quantity of vehicles entering the target logistics station within a preset time range for logistics circulation. Then, according to the total scheduling quantity information, the plurality of logistics vehicles and the preset time range, determining a required time range for logistics processing according to the quantity of the plurality of logistics vehicles, namely according to the total scheduling quantity information, determining a time period for the plurality of logistics vehicles to enter a target logistics station within the preset time range by combining the quantity of the plurality of logistics vehicles, preferably, the logistics processing does not affect the logistics scheduling of other vehicles within the time period. Optionally, the required time range for performing logistics processing on the plurality of logistics vehicles is a ratio of the number of the plurality of logistics vehicles to the total scheduling number, and is multiplied by the preset time range.
The first constraint condition is that the total time of the logistics processing of the plurality of logistics vehicles is constrained to fall within the required time range, namely, the total time of the logistics processing of the plurality of logistics vehicles is limited. Therefore, the logistics time is limited, the processing time of the logistics vehicles is restrained, and the technical effect of providing basis for subsequent vehicle scheduling is achieved.
Illustratively, the total number of vehicles scheduled in the logistics field is 2000, the scheduling operation condition of 60 vehicles in the logistics field is analyzed, the operation time of the logistics field is 20 hours, the residence time of 60 vehicles in the station is controlled within 45 minutes, and otherwise the circulation condition of other vehicles in the field is influenced.
Step S500: constructing a second constraint condition according to the first capacity information and the second capacity information;
further, as shown in fig. 3, a second constraint condition is constructed according to the first capacity information and the second capacity information, and step S500 in this embodiment of the present application further includes:
step S510: acquiring vehicle quantity information when the loading area and the area to be loaded are blocked in historical time, and acquiring first quantity information and second quantity information;
step S520: calculating to obtain a first capacity threshold and a second capacity threshold according to the first quantity information, the second quantity information, the first capacity information and the second capacity information;
step S530: and taking the number of the logistics vehicles in the loading area smaller than or equal to the first capacity threshold value and the number of the logistics vehicles in the area to be loaded smaller than or equal to the second capacity threshold value as the second constraint condition.
Specifically, the second constraint condition is a constraint condition for limiting the number of real-time logistics vehicles in a loading area and a loading area in the vehicle scheduling process in the target logistics field. And acquiring the historical scheduling condition of the target station, extracting the historical scheduling condition by taking the traffic jam as a label, and acquiring the number of vehicles in the vehicle containing area in the historical time when the vehicle is jammed as first quantity information. The second quantity information is obtained by collecting the quantity of vehicles in an area to be loaded when the blockage occurs in historical time. Preferably, when congestion occurs in a plurality of acquired historical times, the number of vehicles in the loading area and the loading area to be loaded obtains a plurality of historical first quantity information and a plurality of historical second quantity information. And further carrying out averaging processing and rounding processing on the plurality of historical first quantity information and the plurality of historical second quantity information to obtain the first quantity information and the second quantity information.
Specifically, the number of vehicles in the loading area capable of accommodating the largest number of vehicles when the loading area is not blocked is obtained according to the first number information and the first capacity information, namely, the first capacity threshold. And obtaining the number of vehicles when the maximum vehicles can be accommodated in the region to be loaded when the region to be loaded is not blocked according to the second quantity information and the second capacity information, namely the second capacity threshold. The first capacity information and the second capacity information are capacities when the loading area and the loading area are fully loaded, but at this time, since the moving direction and speed of each vehicle in the station are different, congestion occurs in the station, and therefore, it is necessary to limit the number of vehicles by setting the second constraint condition. And further determining a second constraint condition that the number of the logistics vehicles in the loading area is smaller than or equal to the first capacity threshold, and meanwhile, the number of the logistics vehicles in the area to be loaded is smaller than or equal to the second capacity threshold. Therefore, the technical effects of limiting and restricting the real-time logistics quantity in the target logistics site, preventing blockage in the site and delaying logistics transportation time are achieved.
Step S600: randomly selecting and combining the sequence of the plurality of logistics vehicles entering the area to be loaded and the loading area to obtain a plurality of scheduling schemes;
further, the order of the plurality of logistics vehicles entering the area to be loaded and the target logistics field station is randomly selected and combined to obtain a plurality of scheduling schemes, and step S600 in the embodiment of the present application further includes:
step S610: identifying the plurality of logistics vehicles to obtain a plurality of identification information;
step S620: according to the plurality of identification information, randomly selecting a random number of logistics vehicles as a first logistics vehicle set from the plurality of logistics vehicles, entering the loading area, and exiting the loading area after loading is finished;
step S630: according to the identification information, randomly selecting a random number of logistics vehicles as a second logistics vehicle set from the rest logistics vehicles, entering the area to be loaded, and entering the loading area after the first logistics vehicle set exits the loading area;
step S640: and continuously randomly selecting and combining the remaining plurality of logistics vehicles to obtain the plurality of scheduling schemes.
Specifically, the plurality of identification information is obtained by identifying a plurality of logistics vehicles respectively, wherein the plurality of identification information corresponds to the plurality of logistics vehicles one to one. Furthermore, according to the plurality of identification information, a random number of logistics vehicles are randomly selected from the plurality of logistics vehicles as the first logistics vehicle set, namely, the selection of the logistics vehicles is not limited, and the number of the logistics vehicles is not limited. The first logistics vehicle set is a vehicle set which enters the loading area for the first time and is driven out of the loading area after loading is completed. Further, among the remaining plurality of logistics vehicles, a random number of logistics vehicles is still randomly selected as the second logistics vehicle set. Wherein the second set of logistics vehicles is a second set of vehicles entering the target logistics site. And then randomly selecting and combining the remaining plurality of logistics vehicles according to the same random selection mode until all the logistics vehicles are scheduled, thereby obtaining the scheduling scheme. Then, the sequence of the plurality of logistics vehicles entering the area to be loaded and the target logistics station is randomly selected and combined for a plurality of times based on the same method, so that the plurality of scheduling schemes are obtained. The plurality of scheduling schemes are used for scheduling logistics processing conditions of a plurality of logistics vehicles in the target logistics site. Therefore, the technical effects of randomly obtaining a plurality of scheduling schemes and laying a cushion for optimizing the subsequent scheduling schemes are achieved.
Step S700: and performing dual-target optimization on the plurality of scheduling schemes according to the first constraint condition, the second constraint condition and the plurality of index parameter sets to obtain an optimal scheduling scheme for scheduling, wherein the dual-target optimization comprises the steps of increasing the overall logistics speed of the plurality of logistics vehicles and increasing the logistics speed of each logistics vehicle.
Further, according to the first constraint condition, the second constraint condition, and the index parameter sets, performing dual-target optimization on the scheduling schemes to obtain an optimal scheduling scheme, where step S700 in this embodiment of the present application further includes:
step S710: according to the first constraint condition and the second constraint condition, constraining the plurality of scheduling schemes to obtain a scheduling scheme set;
step S720: randomly selecting a scheduling scheme from the scheduling scheme set as a first scheduling scheme and as a historical optimal scheme;
step S730: analyzing and acquiring a first scheduling score of the first scheduling scheme based on dual target optimization;
step S740: adjusting the first scheduling scheme by adopting a plurality of preset adjusting modes to construct a first neighborhood, wherein the first neighborhood comprises a plurality of adjusting scheduling schemes, the adjusting scheduling schemes are included in the scheduling scheme set, and the plurality of preset adjusting modes comprise adjusting the number and the entering sequence of logistics vehicles entering the loading area and the to-be-loaded area;
step S750: analyzing and acquiring a plurality of adjustment scheduling scores of the plurality of adjustment scheduling schemes, and acquiring a maximum value of the plurality of adjustment scheduling scores as a second scheduling score;
step S760: taking an adjustment scheduling scheme corresponding to the second scheduling score as a second scheduling scheme, judging whether the second scheduling score is larger than the first scheduling score, if so, taking the second scheduling scheme as a historical optimal scheme, adding a preset adjustment mode for obtaining the second scheduling scheme into a taboo table, wherein the taboo table comprises taboo iteration times, and if not, taking the first scheduling scheme as the historical optimal scheme;
step S770: continuing to construct a second neighborhood of the second scheduling scheme, and performing iterative optimization;
step S780: and when the preset iteration times are reached, stopping optimizing, and outputting the historical optimal scheme to obtain the optimal scheduling scheme.
Specifically, the dual-target optimization refers to iterative optimization of the overall logistics speed of the plurality of logistics vehicles and the logistics speed of each logistics vehicle. Firstly, calculating a plurality of overall processing time for logistics processing of a plurality of logistics vehicles in the plurality of scheduling schemes, and a plurality of vehicle quantity entering a loading area and a to-be-loaded area at the same time, and then screening the plurality of overall processing time and the plurality of vehicle quantity of the plurality of scheduling schemes according to the first constraint condition and the second constraint condition, and only leaving the scheduling scheme meeting the first constraint condition and the second constraint condition as the scheduling scheme set.
The method and the device for optimizing the scheduling schemes are based on a tabu search algorithm. Specifically, a scheduling scheme is randomly selected from the scheduling scheme set, and the selected scheduling scheme is used as the first scheduling scheme. The first scheduling scheme is a scheduling scheme which is preliminarily taken as scheduling and is set as a current historical optimal scheme. And further, the first scheduling score is obtained by evaluating the first scheduling scheme from the perspective of dual objectives. The first scheduling score refers to a result obtained by evaluating the first scheduling scheme from the aspects of overall logistics processing time and single vehicle logistics processing time. The multiple preset adjusting modes are preset adjusting modes for the scheduling scheme, and the multiple preset adjusting modes comprise adjusting the number and the entering sequence of logistics vehicles entering the loading area and the to-be-loaded area. The different preset adjusting modes comprise adjusting the sequence of different logistics vehicles entering the loading area and the area to be loaded, and adjusting the number of the logistics vehicles entering the loading area and the area to be loaded according to different adjusting ranges, wherein the first neighborhood is a plurality of adjusting scheduling schemes obtained after the first scheduling scheme is adjusted according to the multiple preset adjusting modes.
Specifically, based on the method for obtaining the first scheduling score, the multiple adjusted scheduling schemes are scored to obtain multiple adjusted scheduling scores, and then the maximum value of the multiple adjusted scheduling scores is screened and used as the second scheduling score. And the second scheduling score is the highest scheduling score obtained by performing score screening on a plurality of adjusted scheduling schemes obtained by adjusting the first scheduling scheme. And if so, the second scheduling scheme is more excellent than the first scheduling scheme, the first scheduling scheme is abandoned, and the second scheduling scheme is taken as a historical optimal scheme. Further, a preset adjusting mode for adjusting to obtain a second scheduling scheme is added into the tabu table, so that the situation that optimization is trapped in local optimization is avoided, wherein the tabu table is a summary table of the preset adjusting mode forbidden to be used in the subsequent adjusting process. The taboo iteration times refer to the times of forbidden use of a preset adjusting mode in the random adjusting process, and when the optimizing iteration reaches the taboo iteration times, the preset adjusting mode is deleted from a taboo table. When the second scheduling score is not greater than the first scheduling score, the first scheduling scheme is still taken as the historically optimal scheme.
Specifically, optimization iteration is further performed, a second neighborhood of the second scheduling scheme is constructed, and then iterative optimization is performed. The method of constructing the second neighbourhood comprising a plurality of adjusted scheduling schemes is identical to the method of constructing the first neighbourhood.
And continuously carrying out optimization iteration, wherein the preset iteration times are preset iteration optimization times. And stopping iteration optimization when the preset iteration times are reached, and outputting a historical optimal scheme to obtain the optimal scheduling scheme. Therefore, the technical effects of carrying out dual-target optimization on the scheduling scheme and improving the adjustment quality of the scheduling scheme are achieved.
Further, based on the dual-target optimization, the first scheduling score of the first scheduling scheme is obtained through analysis, and step S730 in the embodiment of the present application further includes:
step S731: calculating and obtaining total time for carrying out all logistics loading processing on the plurality of logistics vehicles in the first scheduling scheme according to the index parameter sets and the loading time indexes to obtain first total time information;
step S732: carrying out scheduling score evaluation according to the first total time information to obtain a first sub-scheduling score;
step S733: acquiring the time for finishing logistics loading processing of the logistics vehicles in the first scheduling scheme, and acquiring information of a plurality of finishing times;
step S734: calculating and acquiring a plurality of logistics time qualification degree information of the plurality of logistics vehicles in the first scheduling scheme according to the plurality of index parameter sets and the logistics required time index;
step S735: calculating to obtain average logistics time qualification degree information according to the logistics time qualification degree information;
step S736: performing scheduling score evaluation according to the average logistics time qualification degree information to obtain a second sub-scheduling score;
step S737: and summing the first sub-scheduling score and the second sub-scheduling score to obtain the first scheduling score.
Specifically, a plurality of index parameter sets and loading time indexes of the plurality of logistics vehicles are extracted, and a plurality of loading time index parameters of the plurality of logistics vehicles in the first scheduling scheme are obtained according to the vehicle identification information in the first scheduling scheme. And then calculating the running time of a plurality of logistics vehicles entering the area to be loaded and the loading area in the first scheduling scheme, and the time required for loading to obtain the first total time information required by the first scheduling scheme. The first total time information reflects the total time of all the logistics vehicles for logistics loading processing.
Specifically, scheduling score evaluation is performed based on the first total time information, and corresponding scores are obtained according to the time, wherein the shorter the time is, the higher the score is. Preferably, a time scoring table is established according to the historical scheduling condition of the target logistics field, the number of logistics vehicles is used as a main classification basis, and corresponding scoring standards are obtained in the time scoring table according to the number of vehicles in the first scheduling scheme. Illustratively, when 60 logistics vehicles are scheduled in the scheduling scheme, the loading processing time in the logistics field station is within 40 minutes, the score is A, the score is B in 40-60 minutes, and the score is C above 60 minutes. Thus, the first sub-scheduling score is obtained by performing scheduling score evaluation according to the time score table. Wherein the first sub-scheduling score reflects a total vehicle time scheduling score condition of the first scheduling scheme.
Further, according to the first scheduling scheme, the time from the time when a plurality of logistics vehicles in the first scheduling scheme wait to arrive at a target logistics site to the time when loading is carried out and logistics loading processing is completed is obtained, and the information of the completion time of the plurality of logistics vehicles is obtained. Wherein the plurality of completion times correspond to the plurality of logistics vehicles one-to-one. And then according to the index parameter sets and the logistics required time index, obtaining the logistics required time determined by the logistics vehicles according to the order requirements of the logistics vehicles. And then, obtaining the qualification degree information of the logistics time according to the ratio of the completion time information in the first scheduling scheme to the logistics required time. And the information of the qualification degrees of the logistics time reflects the qualification degrees of the logistics processing time of the logistics vehicles when the logistics scheduling is carried out according to the first scheduling scheme. And further carrying out averaging processing on the information of the qualification degrees of the plurality of logistics time to obtain the information of the qualification degrees of the average logistics time. The average logistics time qualification degree information reflects the logistics processing time qualification degree of each vehicle when logistics scheduling is performed according to the first scheduling scheme.
Specifically, scheduling score evaluation is carried out according to the average logistics time qualification degree information, and a second sub-scheduling score is obtained. And the second sub-scheduling score reflects the reasonable scheduling time degree of scheduling each vehicle according to the first scheduling scheme. Preferably, when the qualified degree of the average logistics time reaches 60%, the second sub-scheduling score is three, when the qualified degree of the average logistics time is between 60% and 80%, the second sub-scheduling score is two, and when the qualified degree of the average logistics time exceeds 80%, the second sub-scheduling score is one. The first grade scores are the highest, and the third grade scores are the lowest. And summing the first sub-scheduling score and the second sub-scheduling score, and synthesizing to obtain the first scheduling score. Therefore, the target of evaluating the first scheduling scheme at two angles of the whole vehicle and the single vehicle is achieved, and the technical effect of improving the evaluation accuracy of the scheduling scheme is achieved.
In summary, the vehicle access scheduling method for the logistics field station provided by the present application has the following technical effects:
1. according to the method, a plurality of logistics vehicles to enter a target logistics field station are collected, index parameters of the logistics vehicles are collected according to a plurality of logistics distribution indexes, a target for collecting basic conditions of the logistics vehicles is achieved, first capacity information is obtained according to capacity of a loading area in the target logistics field station, second capacity information is obtained according to capacity of the loading area to be loaded, the target for collecting the number of vehicles when the target logistics field station is fully loaded is achieved, data are provided for subsequent vehicle scheduling, a first constraint condition is established according to the logistics vehicles, loading time of logistics is limited, the number of vehicles entering the target logistics field station is limited according to the second constraint condition, then random selection and combination are conducted on sequences of the logistics vehicles entering the loading area to be loaded and the loading area, a plurality of scheduling schemes are obtained, then a plurality of scheduling schemes are limited, screening and iteration are conducted according to the first constraint condition, the second constraint condition and a plurality of index parameter sets, overall scheduling time and loading time are considered in the process of searching, optimal scheduling of the vehicles are achieved, and accordingly, target vehicle scheduling accuracy is improved. The technical effect of improving the vehicle dispatching efficiency and the intelligent degree of the target logistics station is achieved.
2. The method comprises the steps of collecting the number of logistics vehicles needing to be scheduled in a preset time range by a target logistics field station, obtaining scheduling tasks in the preset time range, obtaining total scheduling quantity information, determining the required time range for logistics processing of the logistics vehicles according to the total scheduling quantity information, the logistics vehicles and the preset time range, limiting the total time for logistics processing of the logistics vehicles in the required time range, ensuring that the whole logistics scheduling operation of the target logistics field station is normal, and obtaining a first constraint condition. The technical effects of carrying out processing time constraint on a plurality of logistics vehicles according to the total scheduling condition of the target logistics station, giving consideration to the overall scheduling efficiency and the scheduling efficiency of partial vehicles and improving the scheduling processing quality are achieved.
Example two
Based on the same inventive concept as the vehicle access scheduling method of the logistics field station in the foregoing embodiment, as shown in fig. 4, the present application further provides a vehicle access scheduling device of the logistics field station, wherein the device includes:
the logistics vehicle acquisition module 11 is used for acquiring a plurality of logistics vehicles to enter a target logistics station;
the system comprises an index parameter acquisition module 12, an index parameter acquisition module 12 and a control module, wherein the index parameter acquisition module 12 is used for acquiring index parameters of a plurality of logistics vehicles according to a plurality of logistics distribution indexes to obtain a plurality of index parameter sets;
a capacity information obtaining module 13, where the capacity information obtaining module 13 is configured to obtain a capacity of a loading area and a capacity of an area to be loaded in the target logistics field station, and obtain first capacity information and second capacity information;
a first constraint building module 14, wherein the first constraint building module 14 is used for building a first constraint according to the plurality of logistics vehicles;
a second constraint condition construction module 15, where the second constraint condition construction module 15 is configured to construct a second constraint condition according to the first capacity information and the second capacity information;
a scheduling scheme obtaining module 16, where the scheduling scheme obtaining module 16 is configured to randomly select and combine orders of the plurality of logistics vehicles entering the area to be loaded and the loading area to obtain a plurality of scheduling schemes;
an optimal scheduling scheme obtaining module 17, where the optimal scheduling scheme obtaining module 17 is configured to perform dual-target optimization on the multiple scheduling schemes according to the first constraint condition, the second constraint condition, and the multiple index parameter sets, to obtain an optimal scheduling scheme, and perform scheduling, where the dual-target optimization includes increasing an overall logistics speed of the multiple logistics vehicles and increasing a logistics speed of each logistics vehicle.
Further, the apparatus further comprises:
a distribution index obtaining unit, configured to obtain the multiple logistics distribution indexes, where the multiple logistics distribution indexes include a loading time index and a logistics required time index;
and the parameter acquisition unit is used for acquiring the index parameters of the plurality of logistics vehicles based on the loading time index and the logistics required time index to obtain a plurality of index parameter sets.
Further, the apparatus further comprises:
a total scheduling quantity obtaining unit, configured to obtain the quantity of logistics vehicles that need to be scheduled in a preset time range at the target logistics site, and obtain total scheduling quantity information;
a required time range obtaining unit, configured to obtain a required time range for performing logistics processing on the plurality of logistics vehicles according to the total scheduling quantity information, the plurality of logistics vehicles, and the preset time range;
a first constraint building unit configured to build, as the first constraint condition, a total time required for the logistics processing for the plurality of logistics vehicles to fall within the required time range.
Further, the apparatus further comprises:
the vehicle quantity information acquisition unit is used for acquiring vehicle quantity information when the loading area and the area to be loaded are blocked in historical time, and acquiring first quantity information and second quantity information;
a capacity threshold obtaining unit, configured to obtain a first capacity threshold and a second capacity threshold by calculation according to the first quantity information, the second quantity information, the first capacity information, and the second capacity information;
and the second constraint setting unit is used for taking the number of the logistics vehicles in the loading area smaller than or equal to the first capacity threshold value and the number of the logistics vehicles in the area to be loaded smaller than or equal to the second capacity threshold value as the second constraint condition.
Further, the apparatus further comprises:
an identification information obtaining unit configured to identify the plurality of logistics vehicles and obtain a plurality of identification information;
a first logistics vehicle obtaining unit, configured to randomly select, according to the plurality of identification information, a random number of logistics vehicles as a first logistics vehicle set from the plurality of logistics vehicles, enter the loading area, and exit the loading area after loading is completed;
a second logistics vehicle obtaining unit, configured to randomly select a random number of logistics vehicles from the remaining multiple logistics vehicles according to the multiple pieces of identification information, enter the area to be loaded, and enter the loading area after the first logistics vehicle set exits the loading area;
and the scheduling schemes are obtained by a plurality of scheduling scheme obtaining units, and the scheduling scheme obtaining units are used for continuously randomly selecting and combining the remaining logistics vehicles to obtain the scheduling schemes.
Further, the apparatus further comprises:
a scheduling scheme constraining unit, configured to constrain the multiple scheduling schemes according to the first constraint condition and the second constraint condition, to obtain a scheduling scheme set;
a historical optimal scheme setting unit, configured to randomly select a scheduling scheme from the scheduling scheme set as a first scheduling scheme and as a historical optimal scheme;
the first scheduling scoring unit is used for analyzing and acquiring a first scheduling score of the first scheduling scheme based on dual-target optimization;
a first neighborhood building unit, configured to adjust the first scheduling scheme by using multiple preset adjustment manners to build a first neighborhood, where the first neighborhood includes multiple adjusted scheduling schemes, the multiple adjusted scheduling schemes are included in the scheduling scheme set, and the multiple preset adjustment manners include adjusting the number and entering order of logistics vehicles entering the loading area and the area to be loaded;
the second scheduling scoring unit is used for analyzing and acquiring a plurality of adjusting scheduling scores of the plurality of adjusting scheduling schemes, and acquiring the maximum value of the plurality of adjusting scheduling scores as a second scheduling score;
a scheduling score judging unit, configured to use an adjusted scheduling scheme corresponding to the second scheduling score as a second scheduling scheme, judge whether the second scheduling score is greater than the first scheduling score, if so, use the second scheduling scheme as a historical optimal scheme, and add a preset adjustment mode for obtaining the second scheduling scheme into a taboo table, where the taboo table includes a taboo iteration number, and if not, use the first scheduling scheme as the historical optimal scheme;
an iterative optimization unit, configured to continue to construct a second neighborhood of the second scheduling scheme, and perform iterative optimization;
and the optimal scheme obtaining unit is used for stopping optimizing when the preset iteration times are reached, and outputting the historical optimal scheme to obtain the optimal scheduling scheme.
Further, the apparatus further comprises:
a total time calculation unit, configured to calculate and obtain, according to the multiple index parameter sets and the loading time index, total time for performing all logistics loading processing on the multiple logistics vehicles in the first scheduling scheme, and obtain first total time information;
the first sub-scheduling scoring unit is used for performing scheduling scoring evaluation according to the first total time information to obtain a first sub-scheduling score;
a completion time obtaining unit, configured to obtain time for the multiple logistics vehicles to complete logistics loading processing in the first scheduling scheme, and obtain multiple completion time information;
the logistics time qualification degree calculating unit is used for calculating and acquiring a plurality of logistics time qualification degree information of the plurality of logistics vehicles in the first scheduling scheme according to the plurality of index parameter sets and the logistics required time index;
the average qualification degree calculating unit is used for calculating and obtaining average logistics time qualification degree information according to the plurality of logistics time qualification degree information;
the second sub-scheduling scoring unit is used for performing scheduling scoring evaluation according to the average logistics time qualification degree information to obtain a second sub-scheduling score;
and the first scheduling score obtaining unit is used for summing the first sub-scheduling score and the second sub-scheduling score to obtain the first scheduling score.
In this specification, each embodiment is described in a progressive manner, and the main point of each embodiment is that the embodiment is different from other embodiments, the vehicle access dispatching method and the specific example of the first embodiment in fig. 1 are also applicable to the vehicle access dispatching device of the logistics field station of this embodiment, and through the foregoing detailed description of the vehicle access dispatching method of the logistics field station, a person skilled in the art can clearly know the vehicle access dispatching device of the logistics field station in this embodiment, so for the sake of brevity of the description, detailed description is not repeated here. The device disclosed in the embodiment corresponds to the method disclosed in the embodiment, so that the description is simple, and the relevant points can be referred to the description of the method part.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (8)
1. A vehicle access scheduling method for a logistics station is characterized by comprising the following steps:
acquiring a plurality of logistics vehicles to enter a target logistics station;
acquiring index parameters of the plurality of logistics vehicles according to a plurality of logistics distribution indexes to obtain a plurality of index parameter sets;
acquiring the capacity of a loading area and the capacity of a to-be-loaded area in the target logistics field station, and acquiring first capacity information and second capacity information;
constructing a first constraint condition according to the plurality of logistics vehicles;
constructing a second constraint condition according to the first capacity information and the second capacity information;
randomly selecting and combining the sequence of the plurality of logistics vehicles entering the area to be loaded and the loading area to obtain a plurality of scheduling schemes;
and performing dual-target optimization on the plurality of scheduling schemes according to the first constraint condition, the second constraint condition and the plurality of index parameter sets to obtain an optimal scheduling scheme for scheduling, wherein the dual-target optimization comprises the steps of improving the overall logistics speed of the plurality of logistics vehicles and improving the logistics speed of each logistics vehicle.
2. The method of claim 1, wherein collecting index parameters of the plurality of logistics vehicles according to a plurality of logistics distribution indexes comprises:
acquiring a plurality of logistics distribution indexes, wherein the logistics distribution indexes comprise loading time indexes and logistics required time indexes;
and acquiring index parameters of the plurality of logistics vehicles based on the loading time index and the logistics required time index to obtain a plurality of index parameter sets.
3. The method of claim 1, wherein constructing a first constraint from the plurality of logistics vehicles comprises:
acquiring the number of logistics vehicles needing to be scheduled in a preset time range by the target logistics station, and acquiring total scheduling number information;
obtaining a time range required for logistics processing of the plurality of logistics vehicles according to the total scheduling quantity information, the plurality of logistics vehicles and the preset time range;
constructing the first constraint condition that a total time required for the logistics processing of the plurality of logistics vehicles falls within the required time range.
4. The method of claim 1, wherein constructing a second constraint based on the first capacity information and the second capacity information comprises:
acquiring vehicle quantity information when the loading area and the area to be loaded are blocked in historical time, and acquiring first quantity information and second quantity information;
calculating to obtain a first capacity threshold and a second capacity threshold according to the first quantity information, the second quantity information, the first capacity information and the second capacity information;
and taking the number of the logistics vehicles in the loading area smaller than or equal to the first capacity threshold value and the number of the logistics vehicles in the area to be loaded smaller than or equal to the second capacity threshold value as the second constraint condition.
5. The method of claim 1, wherein the order of the plurality of logistics vehicles entering the area to be loaded and the target logistics site is randomly selected and combined to obtain a plurality of scheduling schemes, comprising:
identifying the plurality of logistics vehicles to obtain a plurality of identification information;
according to the plurality of identification information, randomly selecting a random number of logistics vehicles from the plurality of logistics vehicles as a first logistics vehicle set, entering the loading area, and exiting the loading area after loading is finished;
according to the identification information, randomly selecting a random number of logistics vehicles as a second logistics vehicle set from the rest logistics vehicles, entering the area to be loaded, and entering the loading area after the first logistics vehicle set exits the loading area;
and continuously randomly selecting and combining the remaining plurality of logistics vehicles to obtain the plurality of scheduling schemes.
6. The method of claim 2, wherein performing dual target optimization on the plurality of scheduling schemes according to the first constraint condition, the second constraint condition and the plurality of index parameter sets to obtain an optimal scheduling scheme comprises:
according to the first constraint condition and the second constraint condition, constraining the plurality of scheduling schemes to obtain a scheduling scheme set;
randomly selecting a scheduling scheme from the scheduling scheme set as a first scheduling scheme and as a historical optimal scheme;
analyzing and acquiring a first scheduling score of the first scheduling scheme based on dual target optimization;
adjusting the first scheduling scheme by adopting a plurality of preset adjusting modes to construct a first neighborhood, wherein the first neighborhood comprises a plurality of adjusting scheduling schemes, the adjusting scheduling schemes are included in the scheduling scheme set, and the plurality of preset adjusting modes comprise adjusting the number and the entering sequence of logistics vehicles entering the loading area and the to-be-loaded area;
analyzing and acquiring a plurality of adjustment scheduling scores of the plurality of adjustment scheduling schemes, and acquiring a maximum value of the plurality of adjustment scheduling scores as a second scheduling score;
taking an adjustment scheduling scheme corresponding to the second scheduling score as a second scheduling scheme, judging whether the second scheduling score is larger than the first scheduling score, if so, taking the second scheduling scheme as a historical optimal scheme, adding a preset adjustment mode for obtaining the second scheduling scheme into a taboo table, wherein the taboo table comprises taboo iteration times, and if not, taking the first scheduling scheme as the historical optimal scheme;
continuing to construct a second neighborhood of the second scheduling scheme, and performing iterative optimization;
and when the preset iteration times are reached, stopping optimizing, and outputting the historical optimal scheme to obtain the optimal scheduling scheme.
7. The method of claim 6, wherein analyzing the first scheduling score for the first scheduling scheme based on dual target optimization comprises:
calculating and obtaining the total time for carrying out all logistics loading processing on the plurality of logistics vehicles in the first scheduling scheme according to the index parameter sets and the loading time indexes to obtain first total time information;
carrying out scheduling score evaluation according to the first total time information to obtain a first sub-scheduling score;
acquiring time for finishing logistics loading processing of the logistics vehicles in the first scheduling scheme, and acquiring information of a plurality of finishing times;
calculating and acquiring a plurality of logistics time qualification degree information of the plurality of logistics vehicles in the first scheduling scheme according to the plurality of index parameter sets and the logistics required time index;
calculating to obtain average logistics time qualification degree information according to the logistics time qualification degree information;
performing scheduling score evaluation according to the average logistics time qualified degree information to obtain a second sub-scheduling score;
and summing the first sub-scheduling score and the second sub-scheduling score to obtain the first scheduling score.
8. A vehicle access scheduling device of a logistics station is characterized in that the device comprises:
the system comprises a logistics vehicle obtaining module, a logistics vehicle obtaining module and a logistics vehicle monitoring module, wherein the logistics vehicle obtaining module is used for obtaining a plurality of logistics vehicles to enter a target logistics station;
the system comprises an index parameter acquisition module, a data acquisition module and a data processing module, wherein the index parameter acquisition module is used for acquiring index parameters of a plurality of logistics vehicles according to a plurality of logistics distribution indexes to obtain a plurality of index parameter sets;
the system comprises a capacity information acquisition module, a capacity information acquisition module and a capacity information acquisition module, wherein the capacity information acquisition module is used for acquiring the capacity of a loading area and the capacity of an area to be loaded in the target logistics field station to acquire first capacity information and second capacity information;
a first constraint condition construction module, configured to construct a first constraint condition according to the plurality of logistics vehicles;
a second constraint condition construction module, configured to construct a second constraint condition according to the first capacity information and the second capacity information;
the dispatching scheme obtaining module is used for randomly selecting and combining the sequence of the plurality of logistics vehicles entering the area to be loaded and the loading area to obtain a plurality of dispatching schemes;
and the optimal scheduling scheme obtaining module is used for performing dual-target optimization on the plurality of scheduling schemes according to the first constraint condition, the second constraint condition and the plurality of index parameter sets to obtain an optimal scheduling scheme for scheduling, wherein the dual-target optimization comprises the steps of improving the overall logistics speed of the plurality of logistics vehicles and improving the logistics speed of each logistics vehicle.
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