CN113177752B - Route planning method and device and server - Google Patents
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- CN113177752B CN113177752B CN202110421621.7A CN202110421621A CN113177752B CN 113177752 B CN113177752 B CN 113177752B CN 202110421621 A CN202110421621 A CN 202110421621A CN 113177752 B CN113177752 B CN 113177752B
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Abstract
The invention discloses a route planning method, which comprises the following steps: acquiring logistics information of N orders, wherein the logistics information comprises order addresses, and the order addresses comprise a first address and a second address, wherein the first address is an address with a destination in a direct transmission range, the second address is an address with the destination outside the direct transmission range, and N is a positive integer; screening out M orders with the order addresses as the first addresses, determining a first initial route for distributing the M orders, and optimizing the first initial route to obtain a first optimized route, wherein M is a positive integer less than or equal to N; screening out N-M orders with the order addresses as the second addresses, determining a second initial route for distributing the N-M orders, and optimizing the second initial route to obtain a second optimized route.
Description
Technical Field
The invention relates to the field of logistics transportation, in particular to a route planning method, a route planning device and a server.
Background
With the progress of science and technology, the society gradually enters a fast-paced society, and in order to adapt to the fast-paced society, in terms of logistics transportation, how to save transportation cost while improving transportation efficiency is a main problem. To improve transportation efficiency and save transportation cost, the most direct and effective way is to plan the optimal route with the shortest transportation mileage, the least time consumption and the lowest cost.
In the prior art, a path planning method is optimized for either a basic path planning scenario or a path planning scenario in a specific scenario, and the same path planning method cannot be applied to various path planning scenarios. Therefore, the existing path planning method is difficult to plan an accurate optimized path in a complex scene, and the optimized path is not accurate enough, which results in low logistics transportation efficiency and high cost.
Disclosure of Invention
The embodiment of the application provides a route planning method, a route planning device and a server, and solves the technical problems that an accurate route is difficult to plan in a complex scene by the existing route planning method, and further the logistics transportation efficiency is low and the cost is high.
In a first aspect, the present application provides a method of route planning, the method comprising:
acquiring logistics information of N orders, wherein the logistics information comprises order addresses, and the order addresses comprise a first address and a second address, wherein the first address is an address of a destination in a direct sending range, the second address is an address of the destination outside the direct sending range, and N is a positive integer;
screening out M orders with the order addresses as the first addresses, determining a first initial route for distributing the M orders, and optimizing the first initial route to obtain a first optimized route, wherein M is a positive integer less than or equal to N;
screening out N-M orders with the order addresses as the second addresses, determining a second initial route for distributing the N-M orders, and optimizing the second initial route to obtain a second optimized route.
Preferably, the determining a first initial route for delivering M orders, and optimizing the first initial route includes:
determining a target optimization strategy according to the logistics information;
optimizing the first initial route based on the objective optimization strategy.
Preferably, determining a target optimization strategy comprises:
determining a route optimization scene to which the logistics information belongs according to the logistics information and a domain model class diagram used for representing the corresponding relation between the logistics information and the route optimization scene;
and determining an optimization strategy under the route optimization scene as the target optimization strategy based on the route optimization scene.
Preferably, the determining a first initial route for delivering M orders, and optimizing the first initial route includes:
generating a plurality of first direct transmission routes based on the M orders;
screening at least one order which does not meet a first preset condition from the plurality of first direct delivery routes to serve as a target order, and executing the following route optimization steps: generating a plurality of second direct sending routes based on the remaining orders except the target order; inserting the target orders into a plurality of second direct delivery routes according to the target optimization strategy; screening at least one order which does not meet the first preset condition from a plurality of second direct sending routes in which target orders are inserted, taking the order as the target order, and repeatedly executing the route optimization step;
when the number of times of executing the line optimization step reaches a preset number of times, obtaining a first initial optimization route;
and optimizing the first initial optimization route to obtain a first optimization route.
Preferably, said optimizing said first initial optimized route to obtain a first optimized route includes:
rearranging the order delivery sequence of each route in the first initial optimized route according to a second preset condition for rearranging the delivery sequence.
Preferably, the logistics information includes vehicle information, and the determining a first initial route for delivering the M orders includes:
determining a current available vehicle according to the vehicle information;
and determining the first initial route according to the current available vehicle and the first address corresponding to each order in the M orders.
Preferably, the determining a second initial route for delivering the N-M orders, and optimizing the second initial route includes:
determining a remaining vehicle capable of delivering the second initial route based on the delivery profile of the currently available vehicle, and determining the second initial route based on the remaining vehicle and the second address.
Preferably, the determining a second initial route for delivering the N-M orders and optimizing the second initial route to obtain a second optimized route includes:
optimizing the second initial route to obtain a second initial optimized route, wherein the second initial optimized route is a route from an origin to a distribution center;
and determining a third initial route for distributing the N-M orders, and optimizing the third initial route to obtain a third initial optimized route, wherein the third initial optimized route is a route from the distribution center to the second address.
In a second aspect, the present application provides a route planning apparatus, comprising:
the logistics information acquisition unit is used for acquiring logistics information of N orders, wherein the logistics information comprises order addresses, the order addresses comprise a first address and a second address, the first address is an address with a destination in a direct sending range, the second address is an address with the destination outside the direct sending range, and N is a positive integer;
the first optimization unit is used for screening out M orders with the order addresses as the first addresses, determining a first initial route for distributing the M orders, and optimizing the first initial route to obtain a first optimized route, wherein M is a positive integer less than or equal to N;
and the second optimization unit is used for screening out N-M orders with the order addresses as the second addresses, determining a second initial route for distributing the N-M orders, and optimizing the second initial route to obtain a second optimized route.
Preferably, the first optimization unit is configured to:
determining a target optimization strategy according to the logistics information;
optimizing the first initial route based on the objective optimization strategy.
Preferably, the first optimization unit is configured to:
determining a route optimization scene to which the logistics information belongs according to the logistics information and a domain model class diagram used for representing the corresponding relation between the logistics information and the route optimization scene;
and determining an optimization strategy under the route optimization scene as the target optimization strategy based on the route optimization scene.
Preferably, the first optimization unit is configured to:
generating a plurality of first direct transmission routes based on the M orders;
screening at least one order which does not meet a first preset condition from the plurality of first direct delivery routes to serve as a target order, and executing the following route optimization steps: generating a plurality of second direct delivery routes based on the remaining orders except the target order; inserting the target orders into a plurality of second direct delivery routes according to the target optimization strategy; screening at least one order which does not meet the first preset condition from the plurality of second direct sending routes in which the target orders are inserted, taking the order as the target order, and repeatedly executing the route optimization step;
when the times of executing the line optimization step reach preset times, obtaining a first initial optimization route;
and optimizing the first initial optimization route to obtain a first optimization route.
Preferably, the first optimization unit is configured to:
rearranging the order delivery sequence of each route in the first initial optimized route according to a second preset condition for rearranging the delivery sequence.
Preferably, the logistics information includes vehicle information, and the first optimization unit is configured to:
determining a current available vehicle according to the vehicle information;
and determining the first initial route according to the current available vehicle and the first address corresponding to each order in the M orders.
Preferably, the second optimization unit is configured to:
determining a remaining vehicle capable of delivering the second initial route based on the delivery profile of the currently available vehicle, and determining the second initial route based on the remaining vehicle and the second address.
Preferably, the second optimized route includes a second initial optimized route and a third initial optimized route, and the second optimization unit includes:
optimizing the second initial route to obtain a second initial optimized route, wherein the second initial optimized route is a route from an origin to a distribution center;
and determining a third initial route for distributing the N-M orders, and optimizing the third initial route to obtain a third initial optimized route, wherein the third initial optimized route is a route from the distribution center to the second address.
In a third aspect, the present application provides a server comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the route planning method when executing the program.
In a fourth aspect, the present application provides the following technical solutions according to an embodiment of the present application:
a computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method of any of the above.
One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:
in the route planning method of the embodiment of the invention, logistics information of N orders is obtained, the logistics information comprises order addresses, and the order addresses comprise a first address and a second address, wherein the first address is an address of which the destination is in a direct sending range, the second address is an address of which the destination is out of the direct sending range, and N is a positive integer; screening out M orders with the order addresses as the first addresses, determining a first initial route for distributing the M orders, and optimizing the first initial route to obtain a first optimized route, wherein M is a positive integer less than or equal to N; screening out N-M orders with the order addresses as the second addresses, determining a second initial route for distributing the N-M orders, and optimizing the second initial route to obtain a second optimized route.
According to the scheme, the order logistics information is obtained, the order distribution routes of different destinations are optimized respectively according to the order addresses, different optimized routes are obtained, the method is more careful and accurate, the logistics transportation efficiency is further improved, and the logistics transportation cost is reduced.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on the drawings without creative efforts.
Fig. 1 is a flowchart of a route planning method according to an embodiment of the present application;
FIG. 2 is a simplified diagram of an order part of a domain model diagram according to an embodiment of the present invention;
fig. 3 is a schematic diagram of a route planning device according to a second embodiment of the present invention;
fig. 4 is a schematic diagram of a server according to a third embodiment of the present invention.
Detailed Description
The embodiment of the application provides a route planning method, and solves the technical problems that the existing route planning method is difficult to plan an accurate route in a complex scene, and further the logistics transportation efficiency is low and the cost is high.
In order to solve the technical problems, the general idea of the embodiment of the application is as follows:
a method of route planning, the method comprising: acquiring logistics information of N orders, wherein the logistics information comprises order addresses, and the order addresses comprise a first address and a second address, wherein the first address is an address of a destination in a direct sending range, the second address is an address of the destination outside the direct sending range, and N is a positive integer; screening out M orders with the order addresses as the first addresses, determining a first initial route for distributing the M orders, and optimizing the first initial route to obtain a first optimized route, wherein M is a positive integer less than or equal to N; screening out N-M orders with the order addresses as the second addresses, determining a second initial route for distributing the N-M orders, and optimizing the second initial route to obtain a second optimized route. In order to better understand the technical scheme, the technical scheme is described in detail in the following with reference to the attached drawings of the specification and specific embodiments.
First, it is stated that the term "and/or" appearing herein is merely one type of associative relationship that describes an associated object, meaning that three types of relationships may exist, e.g., a and/or B may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter related objects are in an "or" relationship.
Example one
The present embodiment provides a route planning method, as shown in fig. 1, which is a flowchart of the route planning method provided in the embodiments of the present specification, and the method includes the following steps:
step S1: acquiring logistics information of N orders, wherein the logistics information comprises order addresses, and the order addresses comprise a first address and a second address, wherein the first address is an address of a destination in a direct sending range, the second address is an address of the destination outside the direct sending range, and N is a positive integer;
step S2: screening out M orders with the order addresses as the first addresses, determining a first initial route for distributing the M orders, and optimizing the first initial route to obtain a first optimized route, wherein M is a positive integer less than or equal to N;
and step S3: screening out N-M orders with the order addresses as the second addresses, determining a second initial route for distributing the N-M orders, and optimizing the second initial route to obtain a second optimized route.
First, steps S1 to S3 do not necessarily have a sequence. The route planning method provided by the embodiment of the specification is suitable for various scenes, such as transportation optimization, shop patrol management, in-warehouse goods picking and the like. For convenience of description, the embodiment mainly takes express transportation in logistics transportation as an example to describe the scheme.
Step S1: the method comprises the steps of obtaining logistics information of N orders, wherein the logistics information comprises order addresses, the order addresses comprise a first address and a second address, the first address is an address with a destination in a direct sending range, the second address is an address with the destination outside the direct sending range, and N is a positive integer.
The N orders may be all orders that a logistics company needs to deliver, or may be orders that need to be transported by express. Each order has its logistics information which may include the destination of the order, i.e. the order address, and may also include the order number, order type, train number, equipment, etc. The straight forwarding range may be a range with a certain distance around the origin, such as a range with a distance of 20km from the origin, a range with a distance of 30km from the origin, etc., and orders with order addresses within the range may be forwarded from the origin to the destination directly without passing through a transfer station or a distribution center. Orders outside the direct delivery scope, i.e., orders destined for the second address.
Step S2: screening out M orders with the order addresses as the first addresses, determining a first initial route for distributing the M orders, and optimizing the first initial route, wherein M is a positive integer less than or equal to N.
Specifically, after obtaining the logistics information of the orders, M orders at the first address may be screened out according to the order addresses, and an initial direct route, that is, a first initial route, may be generated according to the first address, for example, a route for sending the distribution center to the destination is generated for each order, and M routes may be generated, or K (less than M) routes may be generated, and one route may include destinations of multiple orders. And then, according to a preset optimization strategy, carrying out a series of optimization on the first initial route, such as route merging and route splitting, and the like, so as to obtain an optimized route of the order with the order address as the first address.
Optionally, the determining a first initial route for delivering M orders, and optimizing the first initial route includes: determining a target optimization strategy according to the logistics information; optimizing the first initial route based on the objective optimization strategy.
The target optimization strategy can be preset, or randomly selected from a preset strategy library. For example: every three kinds of logistics information have corresponding preset target optimization strategies, namely, if the logistics information a, b and c are obtained, the preset target optimization strategies X corresponding to a, b and c can be correspondingly determined; another example is: and after the logistics information is acquired, randomly selecting an optimization strategy Y from a preset strategy library containing optimization strategies X, Y and Z as a target optimization strategy and the like.
Optionally, the determining a target optimization strategy according to the logistics information includes: determining a route optimization scene to which the logistics information belongs according to the logistics information and a domain model class diagram used for representing the corresponding relation between the logistics information and the route optimization scene; and determining an optimization strategy under the route optimization scene as the target optimization strategy based on the route optimization scene.
The optimized scene can be a basic optimized scene or a complex optimized scene, and the basic optimized scene comprises a simple take-out delivery scene, an express delivery scene, a cargo direct-release scene and the like; the complex optimization scene comprises a scene that the express headquarters send the express to the clients, a cross-province express mailing scene and the like. The optimization strategy may be break route (break and rearrange the number of cars with a loading rate lower than a set value), consolidate (reduce the number of cars by combining the waybills as much as possible on one car under the premise of considering various constraints), consolidate bystop (reduce the number of cars by combining the waybills according to the same starting place and destination), initialroot (direct number of cars can be generated by selecting the waybills to initialize according to conditions), routewap (iterative optimization is performed by exchanging the combined number of cars by applying a domain search algorithm, and continuously taking out and returning the cars), and the like.
The domain model class diagram is a class diagram constructed according to the association relationship of various information in the logistics information, which includes and summarizes all the known logistics information and the association of various information, and fig. 2 is a schematic diagram of a simple domain model class diagram only including an order part.
The logistics information can be roughly divided into large objects such as orders, places, equipment, train numbers and the like, each large object can be divided into a plurality of sub-objects, and each sub-object comprises various attributes. For example:
order form: a group of goods/service transportation demands from a starting place to a destination in a specified time are composed of order head information and order detail information, wherein the order head information mainly covers the attributes of order number, type, priority, lifting and unloading points, lifting and unloading time periods, cargo quantity, lifting and unloading duration, special distribution requirements and the like, and the order detail information mainly comprises the attributes of transportation units, quantity, commodity types, unit volume/weight, total volume/total weight/total value and the like;
a place: the longitude and latitude positions existing on a physical map related in the transportation process comprise multiple types such as warehouses (goods picking points), unloading points (service points), distribution centers, parking lots and the like, and comprise multiple sub-objects such as crossings, available equipment types, contacts, working calendars and the like, and the attributes such as addresses, coordinates, whether first stations/last stations exist, fixed processing time, variable loading and unloading efficiency, throughput and the like can be defined on the aspect of the location for reference in transportation plan calculation;
equipment: the transportation tool with certain dimensionality limitation can be refined into types of automobiles, trucks, containers, forklifts, airplanes and the like according to different transportation scenes, and mainly comprises attributes such as type grouping, limitation dimensionalities (such as length, width, height, load, volume, maximum kilometer number, maximum station number and maximum working time), commodity class relation and the like;
the number of the trains is as follows: a set of series of pick-up and drop-off (or call-in) tasks provided by the same carrier, having a designated origin and destination, delivered to the same transport facility, or may be summarized as a set of task schedules based on composite transport and billing constraints calculated for a given order, a train number comprising at least one trip segment, and may also comprise a plurality of trip segments. The journey section is a result formed by judging whether the journey section is required to be split into a plurality of orders or not according to the calculation of the order section by an algorithm, and may be completely consistent with the order section appointed by a user, and may also be further split on the basis of the order section, the train number is divided into two levels of a train number head and a station, the train number head comprises attributes such as train number state, start/end time, start point/destination, total weight/total volume/total number of pieces/total number of stations, full load rate, carriers and the like, and the station is a sub-object of the train number and is a place where a lifting and unloading task or a service (such as visit) task of the train number occurs. The station comprises a plurality of attributes such as station codes, sequences, planned arrival/departure time, actual arrival/departure time, total lifting and unloading weight/total volume, operation time, waiting time, distance/duration to look ahead, and the like, and a sub-object of a task, wherein the station task mainly comprises information such as service types, order numbers related to the task, weight volume numbers of cargos and the like.
After the logistics information of an order is obtained, the table is looked up in the domain model class diagram according to the logistics information, the optimal scene of the route to which the logistics information belongs can be determined, and in different scenes, the route can be optimized by adopting various preset optimization strategies. For example: the direct delivery range is 30km away from the origin, the obtained logistics information is 'order address is 20km away from the origin', and the cargo direct delivery scene of the optimized scene based on the optimized scene can be determined, wherein the route is optimized mainly by adopting optimization strategies such as Consolidate, consolidate ByStop, initialRoute, routeSwap and the like.
Optionally, the determining a first initial route for delivering M orders, and optimizing the first initial route includes: generating a plurality of first direct transmission routes based on the M orders; screening at least one order which does not meet a first preset condition from the plurality of first direct delivery routes to serve as a target order, and executing the following route optimization steps: generating a plurality of second direct delivery routes based on the remaining orders except the target order; inserting the target orders into a plurality of second direct delivery routes according to the target optimization strategy; screening at least one order which does not meet the first preset condition from a plurality of second direct sending routes in which target orders are inserted, taking the order as the target order, and repeatedly executing the route optimization step; when the times of executing the line optimization step reach preset times, obtaining a first initial optimization route; and optimizing the first initial optimization route to obtain a first optimization route.
The first preset condition may be a distance between every two order addresses, a cargo size, and the like, and for an order with an order address being the first address, the optimization process may be such that: firstly, generating a direct transmission route for each order address of M orders, screening one or more orders which do not meet a first preset condition from the M direct transmission routes, and screening the orders which do not meet the first preset condition by taking the first preset condition as 'the distance between every two order addresses does not exceed 5 km' as an example. Replanning, merging or splitting the remaining direct transmission routes to generate a plurality of new direct transmission routes, namely a second direct transmission route, for example: and the order addresses A, B, C, D and E are combined to generate a direct transmission route, wherein the order addresses A, B and C are arranged on a direct transmission route, the order addresses D which do not meet the first preset condition are screened out on the direct transmission route, the route is re-planned, and the order addresses A, B, C and E meet the first preset condition when the order addresses A, B, C and E are arranged on the direct transmission route. Then, inserting orders which do not meet the first preset condition into each position in the second direct delivery route according to a target optimization strategy RouteSwap (combined train number is exchanged by using a domain search algorithm, and iterative optimization is performed by continuously taking out and putting back), and taking the order addresses of the orders A, B, C, D and E as examples: the screened order addresses D are sequentially inserted between the order addresses A and B of the direct delivery routes A, B, C and E, if a first preset condition is met, the routes are determined to be A, D, B, C and E, if the first preset condition is not met, D is continuously inserted between the order addresses B and C \8230, until all the order addresses meet the first preset condition, and if D cannot meet the preset condition at each position, a direct delivery route is independently planned for D. And after all the target orders are inserted, repeatedly screening new orders which do not meet the first preset condition to serve as the target orders, and repeatedly executing the optimization steps. It should be noted that the route is only used to determine which order addresses are on the same route. And if the repeated optimization times reach the preset optimization times or the optimization route is obtained before the preset optimization times, stopping the optimization, wherein the obtained optimization route is the first initial optimization route. And after the first initial optimization route is further optimized, obtaining a first optimization route.
Optionally, the optimizing the first initial optimized route to obtain a first optimized route includes: and rearranging the order delivery sequence of each route in the first initial optimized route according to a second preset condition for rearranging the delivery sequence.
The second preset condition may be an optimization strategy Resequence (sequential rearrangement for each route). After obtaining a plurality of first initial optimized routes, on the premise of not merging or splitting the first initial optimized routes, adjusting the timing sequence of order distribution in each first initial optimized route through an optimization strategy response, and obtaining a route with the shortest total distribution route through adjustment, namely the first optimized route, by taking the order addresses a, B, C, D and E as an example, if the first initial optimized route has two routes, namely a, D, B, C and E, wherein C is closer to the origin than E, D is closer to the origin than a, and D is closer to the origin than a, the distribution sequence of the routes a, D and B is determined as D → a → B, and the distribution sequence of the routes C and E is determined as E → C.
Optionally, the logistics information includes vehicle information, and the determining a first initial route for delivering the M orders includes: determining a current available vehicle according to the vehicle information; and determining the first initial route according to the current available vehicle and the first address corresponding to each order in the M orders.
The vehicle information may include the size of the vehicle, the cargo capacity, the vehicle type, the longest route of transportation, and the like. And after the vehicle information is acquired, determining the currently available vehicle according to information such as an order address in the logistics information. Different vehicles may also have different transportation routes, for example, a large truck may not be able to enter the urban area. For example: the distance between the order address in the logistics information and the origin is 200km, the total weight of the order is 20t, the truck information comprises a truck with the length of 9.6m and the weight limit of 20t and a truck with the length of 12.5 m and the weight limit of 50t, and the truck with the length of 12.5 m and the weight limit of 50t is determined by considering the weight limit, and a proper first initial route is generated according to the weight limit, the driving limit and the charging conditions on different highways.
And step S3: screening out N-M orders with the order addresses as the second addresses, determining a second initial route for distributing the N-M orders, and optimizing the second initial route to obtain a second optimized route.
The N-M orders may be orders other than M orders with an order address that is a first address, i.e., orders with an order address that is a second address. When N = M, N-M is 0, i.e. there is only optimization for the first address order. The route from the starting place to the order address generated by the order addresses of the N-M orders is a second initial route, and the second initial route can be a straight-through route or a general name of a multi-section branch route. And optimizing the second initial route, wherein the finally obtained route is the second optimized route.
Optionally, the determining a second initial route for delivering the N-M orders, and optimizing the second initial route includes:
determining a remaining vehicle capable of delivering the second initial route based on the delivery of the currently available vehicle, and determining the second initial route based on the remaining vehicle and the second address.
After the first initial route of the first address is optimized and the first optimized route is determined, the vehicle for delivering the order address as the first address is correspondingly determined, when the second initial route of the second address is determined, the available vehicle amount needs to be determined in the vehicle information, specifically, the vehicle which is not selected can be selected, or the vehicle which has completed the delivery task before the delivery time of the second route is performed is used for delivering the second initial route. The optimization scenario for the second initial route may be the same as the optimization scenario for the first initial route, wherein the selection of the optimization strategy should be determined according to different optimization scenarios.
Optionally, the determining a second initial route for dispatching the N-M orders and optimizing the second initial route to obtain a second optimized route includes: optimizing the second initial route to obtain a second initial optimized route, wherein the second initial optimized route is a route from a starting place to a distribution center; and determining a third initial route for distributing the N-M orders, and optimizing the third initial route to obtain a third initial optimized route, wherein the third initial optimized route is a route from the distribution center to the second address.
Optimizing the second initial route may result in a second initial optimized route, i.e., a route from the origin to the distribution center. And continuing to generate N-M routes of orders sent to the second address by the distribution center, namely a third initial route. And optimizing the third initial route to obtain a third initial optimized route. The optimization scheme of the third route may be the same as the optimization scheme of the first route, and the selection of the optimization strategy should be determined according to different optimization scenarios. It should be noted that, for the optimization of the third route, the preset delivery time of each of the N-M orders needs to be considered, and the preset delivery time may be selected by the customer or automatically allocated in the logistics information, so as to avoid delivering the order to the second address too early or too late. In more complex scenarios, for example: in a scene of 'sending an order to each distribution center by a general logistics center, sending the order to each dispatching point by each distribution center, and then distributing the order to each receiving point by each dispatching point', aiming at each layer of distribution, different optimization strategies need to be selected according to a path optimization scene to execute path optimization once so as to achieve an accurate and detailed general optimization route.
Optionally, at each route optimization, the optimized route is defined according to the parameter list.
The parameter list can be a preset key value pair with a default value, and each parameter has a corresponding value; or may be set by the user through a front-end UI, or may be transmitted through a message when called by an Application Programming Interface (API). And during route optimization, if the user provides a parameter list, the route optimization scheme is limited according to the provided parameter list, and if the user does not provide the parameter list, the route optimization scheme is optimized and limited according to a default parameter list. For example, there are three parameters in the parameter list:
low Cross User Define Zone: the system only searches for proper order split loading in the same area, and only when the system is set to true, the system considers releasing the constraint and tries the split loading in the cross region;
max Allow Cross Max Zones Count: the method is used for limiting the maximum number of Cross-areas of an order during the loading under the condition that the above low Cross User Define Zone is set to true, namely, the Cross-area loading is allowed, wherein the parameter value is 0 or is empty, the number of the Cross-areas is not limited (unlimited Cross-areas are allowed), the parameter value is 1, the number of a train is only loaded in one area, 2, one train can be loaded in two areas, and the like, and when the Cross-area parameter is not started, the parameter is not effective;
max Distance Between Stops: the method is used for limiting the maximum distance between adjacent stations in the same line, the unit is kilometer, the default value is 0, the setting parameter value is 0 or the space is empty, the distance between any adjacent stations is not limited, and otherwise, the constraint is considered during the loading.
The technical scheme in the embodiment of the application at least has the following technical effects or advantages:
1. by acquiring the order logistics information and respectively optimizing the order distribution routes of different destinations according to the order addresses, different optimized routes are obtained, and the method is more careful and accurate, further improves the logistics transportation efficiency and reduces the logistics transportation cost.
2. By constructing the field model class diagram, determining the route optimization scene based on the field model class diagram and the logistics information, and determining different target optimization strategies according to different route optimization scenes, the adaptability and compatibility of route optimization are improved.
3. And the route is continuously optimized in an iterative way by circulating the route optimization steps, so that the optimized route is more reasonable and approaches to the optimal route.
4. By setting the parameters according to the parameter list, the user can precisely define the line optimization.
Example two
Based on the same inventive concept, as shown in fig. 3, an embodiment of the present specification provides a route planning apparatus 200, including:
a logistics information obtaining unit 201, configured to obtain logistics information of N orders, where the logistics information includes an order address, and the order address includes a first address and a second address, where the first address is an address of which a destination is in a direct sending range, the second address is an address of which the destination is outside the direct sending range, and N is a positive integer;
a first optimizing unit 202, configured to screen out M orders whose order addresses are the first addresses, determine a first initial route for delivering the M orders, and optimize the first initial route to obtain a first optimized route, where M is a positive integer less than or equal to N;
the second optimizing unit 203 is configured to filter out N-M orders whose order addresses are the second addresses, determine a second initial route for distributing the N-M orders, and optimize the second initial route to obtain a second optimized route.
Optionally, the first optimization unit 202 is configured to: determining a target optimization strategy according to the logistics information; optimizing the first initial route based on the objective optimization strategy.
Optionally, the first optimization unit 202 is configured to: determining a route optimization scene to which the logistics information belongs according to the logistics information and a domain model class diagram used for representing the corresponding relation between the logistics information and the route optimization scene; and determining an optimization strategy under the route optimization scene as the target optimization strategy based on the route optimization scene.
Optionally, the first optimization unit 202 is configured to: generating a plurality of first direct transmission routes based on the M orders; screening at least one order which does not meet a first preset condition from the plurality of first direct transmission routes to serve as a target order, and executing the following route optimization steps: generating a plurality of second direct delivery routes based on the remaining orders except the target order; inserting the target orders into a plurality of second direct delivery routes according to the target optimization strategy; screening at least one order which does not meet the first preset condition from a plurality of second direct sending routes in which target orders are inserted, taking the order as the target order, and repeatedly executing the route optimization step; when the number of times of executing the line optimization step reaches a preset number of times, obtaining a first initial optimization route; and optimizing the first initial optimized route to obtain a first optimized route.
Optionally, the first optimization unit 202 is configured to: rearranging the order delivery sequence of each route in the first initial optimized route according to a second preset condition for rearranging the delivery sequence.
Optionally, the logistics information includes vehicle information, and the first optimization unit 202 is configured to: determining a current available vehicle according to the vehicle information; and determining the first initial route according to the current available vehicle and the first address corresponding to each order in the M orders.
Optionally, the second optimizing unit 203 is configured to: determining a remaining vehicle capable of delivering the second initial route based on the delivery of the currently available vehicle, and determining the second initial route based on the remaining vehicle and the second address.
Optionally, the second optimized route includes a second initial optimized route and a third initial optimized route, and the second optimization unit 203 includes: optimizing the second initial route to obtain a second initial optimized route, wherein the second initial optimized route is a route from an origin to a distribution center; and determining a third initial route for distributing the N-M orders, and optimizing the third initial route to obtain a third initial optimized route, wherein the third initial optimized route is a route from the distribution center to the second address.
With regard to the above-mentioned apparatus, the specific functions of the respective units have been described in detail in the embodiment of the route planning method provided in the embodiment of the present specification, and will not be described in detail here.
EXAMPLE III
Based on the same inventive concept as the route planning method in the foregoing embodiment, an embodiment of this specification further provides a server, as shown in fig. 4, including:
a memory 304, a processor 302 and a computer program stored on the memory 304 and executable on the processor 302, the processor 302 when executing the program implementing the steps of the route planning method described hereinbefore.
Wherein in fig. 4 a bus architecture (represented by bus 300), bus 300 may include any number of interconnected buses and bridges, bus 300 linking together various circuits including one or more processors, represented by processor 302, and memory, represented by memory 304. The bus 300 may also link together various other circuits such as peripherals, voltage regulators, power management circuits, and the like, which are well known in the art, and therefore, will not be described any further herein. A bus interface 306 provides an interface between the bus 300 and the receiver 301 and transmitter 303. The receiver 301 and the transmitter 303 may be the same element, i.e., a transceiver, providing a means for communicating with various other apparatus over a transmission medium. The processor 302 is responsible for managing the bus 300 and general processing, and the memory 304 may be used for storing data used by the processor 302 in performing operations.
Example four
Based on the same inventive concept, the embodiments of the present specification provide a computer-readable storage medium, on which a computer program is stored, which when executed by a processor, implements the steps of any one of the route planning methods described above.
Since the electronic device described in this embodiment is an electronic device used for implementing the method for processing information in the embodiment of the present application, a person skilled in the art can understand the specific implementation of the electronic device of this embodiment and various modifications thereof based on the method for processing information described in this embodiment of the present application, and therefore, how to implement the method in the embodiment of the present application by the electronic device is not described in detail herein. Electronic devices used by those skilled in the art to implement the method for processing information in the embodiments of the present application are all within the scope of the present application.
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 has been 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 (9)
1. A method of route planning, the method comprising:
acquiring logistics information of N orders, wherein the logistics information comprises order addresses, and the order addresses comprise a first address and a second address, wherein the first address is an address of a destination in a direct sending range, the second address is an address of the destination outside the direct sending range, and N is a positive integer;
screening out M orders with the order addresses as the first addresses, determining a first initial route for distributing the M orders, and optimizing the first initial route to obtain a first optimized route, wherein M is a positive integer less than or equal to N;
screening out N-M orders with the order addresses as the second addresses, determining a second initial route for distributing the N-M orders, and optimizing the second initial route to obtain a second optimized route;
the process of obtaining the first optimized route and the second optimized route comprises the following steps:
determining a route optimization scene to which the logistics information belongs according to the logistics information and a domain model class diagram used for representing the corresponding relation between the logistics information and the route optimization scene; the field model class diagram is a class diagram constructed according to the incidence relation of various information in the logistics information;
the route optimization scene is a basic optimization scene or a complex optimization scene; the basic optimization scene comprises a take-out delivery scene, an express delivery scene and a cargo direct-distribution scene; the complex optimization scene comprises a scene that an express headquarter sends to a client and a cross-province express mailing scene;
and determining an optimization strategy under the route optimization scene based on the route optimization scene as a target optimization strategy.
2. The method of claim 1, wherein said determining a first initial route for delivering M orders, said first initial route being optimized, comprises:
determining a target optimization strategy according to the logistics information;
optimizing the first initial route based on the objective optimization strategy.
3. The method of claim 2, wherein said determining a first initial route for delivering M orders, optimizing said first initial route, comprises:
generating a plurality of first direct transmission routes based on the M orders;
screening at least one order which does not meet a first preset condition from the plurality of first direct delivery routes to serve as a target order, and executing the following route optimization steps: generating a plurality of second direct delivery routes based on the remaining orders except the target order; inserting the target orders into a plurality of second direct delivery routes according to the target optimization strategy; screening at least one order which does not meet the first preset condition from a plurality of second direct sending routes in which target orders are inserted, taking the order as the target order, and repeatedly executing the route optimization step;
when the number of times of executing the line optimization step reaches a preset number of times, obtaining a first initial optimization route;
and optimizing the first initial optimization route to obtain a first optimization route.
4. The method of claim 3, wherein said optimizing said first initial optimized route to obtain a first optimized route comprises:
and rearranging the order delivery sequence of each route in the first initial optimized route according to a second preset condition for rearranging the delivery sequence.
5. The method of claim 4, wherein the logistics information includes vehicle information, and wherein determining a first initial route for delivering the M orders comprises:
determining a current available vehicle according to the vehicle information;
and determining the first initial route according to the current available vehicle and the first address corresponding to each order in the M orders.
6. The method of claim 5, wherein said determining a second initial route for delivering said N-M orders, optimizing said second initial route comprises:
determining a remaining vehicle capable of delivering the second initial route based on the delivery of the currently available vehicle, and determining the second initial route based on the remaining vehicle and the second address.
7. The method of claim 1, wherein the second optimized route comprises a second initial optimized route and a third initial optimized route, and wherein determining the second initial route for dispatching the N-M orders, optimizing the second initial route to obtain the second optimized route comprises:
optimizing the second initial route to obtain a second initial optimized route, wherein the second initial optimized route is a route from an origin to a distribution center;
and determining a third initial route for distributing the N-M orders, and optimizing the third initial route to obtain a third initial optimized route, wherein the third initial optimized route is a route from the distribution center to the second address.
8. A route planning apparatus, comprising:
the logistics information acquisition unit is used for acquiring logistics information of N orders, wherein the logistics information comprises order addresses, and the order addresses comprise a first address and a second address, the first address is an address of which the destination is in a direct transmission range, the second address is an address of which the destination is out of the direct transmission range, and N is a positive integer;
the first optimization unit is used for screening out M orders with the order addresses as the first addresses, determining a first initial route for distributing the M orders, and optimizing the first initial route to obtain a first optimized route, wherein M is a positive integer less than or equal to N;
the second optimization unit is used for screening out N-M orders with the order addresses as the second addresses, determining a second initial route for distributing the N-M orders, and optimizing the second initial route to obtain a second optimized route;
the process of obtaining the first optimized route and the second optimized route comprises the following steps:
determining a route optimization scene to which the logistics information belongs according to the logistics information and a domain model class diagram used for representing the corresponding relation between the logistics information and the route optimization scene; the field model class diagram is a class diagram constructed according to the incidence relation of various information in the logistics information;
the route optimization scene is a basic optimization scene or a complex optimization scene; the basic optimization scene comprises a take-out delivery scene, an express delivery scene and a cargo direct-release scene; the complex optimization scene comprises a scene that an express headquarter sends the complex optimization scene to a client and a trans-provincial express mailing scene;
and determining an optimization strategy under the route optimization scene based on the route optimization scene as a target optimization strategy.
9. A server, comprising a processor and a memory:
the memory is used for storing a program for executing the method in any one of claims 1 to 7;
the processor is configured to execute programs stored in the memory.
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