CN114706397A - Steel logistics route planning method and system based on navigation positioning - Google Patents
Steel logistics route planning method and system based on navigation positioning Download PDFInfo
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- 229910052742 iron Inorganic materials 0.000 description 1
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- 230000002285 radioactive effect Effects 0.000 description 1
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Abstract
The invention relates to a steel logistics route planning method and a steel logistics route planning system based on navigation positioning. The method comprises the steps of obtaining a starting point and a target point of the movement of an order receiving vehicle according to order information; determining an environment grid map by adopting a grid method according to the working environment of the movement of the order-receiving vehicle; and determining the steel logistics route of the order receiving vehicle by adopting a heuristic function combining an evaluation function and a transfer constraint according to the starting point and the target point of the movement of the order receiving vehicle and the environment space. The invention can effectively and quickly plan the global optimal path.
Description
Technical Field
The invention relates to the technical field of information, in particular to a method and a system for planning a steel logistics route based on navigation positioning.
Background
Urban steel logistics is steadily advancing along with the development of times, and is widely considered as another profit increasing way for enterprises to reduce material consumption and improve labor productivity. The logistics distribution industry of the current generation is developing towards informatization, networking, modernization and intellectualization, and a path planning algorithm based on navigation positioning is playing an increasingly large role in logistics distribution.
At present, the application of a vehicle navigation system in the field of logistics distribution is less, the traditional logistics industry is dominated by manpower, and most routes are judged and planned by human experience. With the development of the logistics distribution industry, many solutions to the path planning problem are still in a semi-manual state. This may cause problems, such as: road condition information obtains untimely, can't grasp vehicle situation in transit in real time, can't carry out a series of problems such as efficient balanced allotment to the vehicle, these all can influence the rationalization of enterprise's commodity circulation, cause the commodity circulation cost to last the lifting very easily, and then cause the result that the commodity circulation service level is low.
The navigation positioning based path planning algorithm technology can scientifically and reasonably carry out optimal path planning and real-time navigation guidance on the delivery vehicles, is the key for guaranteeing the high efficiency and safety of the delivery process, and is also the key for reducing the cost of enterprises, improving the delivery service level, improving the user satisfaction and the enterprise competitiveness. By accessing the algorithm, a logistics route planning platform capable of improving logistics distribution efficiency can be established, and an accurate distribution function is provided for the steel logistics industry based on a path planning and navigation algorithm. However, the heuristic function in the existing basic path planning algorithm usually needs a long search time and is not easy to search the global optimal path, that is, the existing technology also has the problem that the global optimal path cannot be planned effectively and quickly.
Disclosure of Invention
The invention aims to provide a steel logistics route planning method and a steel logistics route planning system based on navigation positioning, which can effectively and quickly plan a global optimal route.
In order to achieve the purpose, the invention provides the following scheme:
a steel logistics route planning method based on navigation positioning is applied to a steel logistics order dispatching system and comprises the following steps:
acquiring a starting point and a target point of the movement of the order receiving vehicle according to the order information;
determining an environment grid map by adopting a grid method according to the working environment of the movement of the order receiving vehicle;
and determining the steel logistics route of the order receiving vehicle by adopting a heuristic function combining an evaluation function and a transfer constraint according to the starting point and the target point of the movement of the order receiving vehicle and the environment space.
Optionally, the determining, according to the start point and the target point of the movement of the order receiving vehicle and the environmental space, a steel logistics route of the order receiving vehicle by using a heuristic function combining an evaluation function and a transfer constraint specifically includes:
initializing the information of the order-accepting vehicle; the information includes: the system comprises the following components, namely vehicle quantity, vehicle positions, pheromone excitation factors, expected heuristic factors, pheromone volatilization coefficients, pheromone intensity coefficients, maximum iteration times, pheromone excitation factors and path directions;
determining the position of the order receiving vehicle in the environment grid map according to the initialized information;
determining a state transition probability value according to a heuristic function combining the valuation function and the transfer constraint;
determining the position of the order receiving vehicle in the environment grid map at the next moment by adopting a roulette method according to the state transition probability value; judging whether the order receiving vehicle reaches a target point or the maximum iteration number;
if the target point is not reached and the maximum iteration times are not reached, updating the information of the order taking vehicle according to the position of the order taking vehicle in the environment grid map at the next moment, and returning to the step of determining the state transition probability value according to the heuristic function combining the valuation function and the transfer constraint until the target point is reached or the maximum iteration times are reached;
and if the target point is reached or the maximum iteration number is reached, determining the steel logistics route of the order receiving vehicle according to the path of the order receiving vehicle in the environment grid map.
Optionally, if the destination point is reached or the maximum iteration number is reached, determining the steel logistics route of the order receiving vehicle according to the route of the order receiving vehicle in the environmental grid map, specifically including:
if the positions of the order-picking vehicles reach the target point and the maximum iteration times are not reached, determining the pheromone concentration of each order-picking vehicle in the path of the environment grid map according to a wolf pack algorithm;
and updating the pheromone concentration until the updated pheromone concentration converges.
Optionally, the wolf pack algorithm is a prey assignment principle.
A steel logistics route planning system based on navigation positioning is applied to a steel logistics order dispatching system and comprises:
the starting point and target point acquisition module is used for acquiring the moving starting point and target point of the order receiving vehicle according to the order information;
the environment grid map determining module is used for determining an environment grid map by adopting a grid method according to the working environment of the movement of the order receiving vehicle;
and the steel logistics route determining module is used for determining the steel logistics route of the order receiving vehicle by adopting a heuristic function combining an evaluation function and a transfer constraint according to the starting point and the target point of the movement of the order receiving vehicle and the environmental space.
Optionally, the steel logistics route determining module specifically includes:
the information initialization unit is used for initializing the information of the order-accepting vehicle; the information includes: the system comprises the following components, namely vehicle quantity, vehicle positions, pheromone excitation factors, expected heuristic factors, pheromone volatilization coefficients, pheromone intensity coefficients, maximum iteration times, pheromone excitation factors and path directions;
the position determining unit is used for determining the position of the order receiving vehicle in the environment grid map according to the initialized information;
the state transition probability value determining unit is used for determining the state transition probability value according to a heuristic function combining the valuation function and the handover constraint;
the position updating unit is used for determining the position of the order receiving vehicle in the environment grid map at the next moment by adopting a roulette method according to the state transition probability value; judging whether the order receiving vehicle reaches a target point or the maximum iteration number;
the iteration unit is used for updating the information of the order receiving vehicle according to the position of the order receiving vehicle in the environment grid map at the next moment if the order receiving vehicle does not reach the target point and does not reach the maximum iteration times, and returning to the step of determining the state transition probability value according to the heuristic function combined with the valuation function and the transfer constraint until the order receiving vehicle reaches the target point or reaches the maximum iteration times;
and the steel logistics route determining unit is used for determining the steel logistics route of the order receiving vehicle according to the route of the order receiving vehicle in the environment grid map if the order receiving vehicle reaches a target point or reaches the maximum iteration number.
Optionally, the steel logistics route determining unit specifically includes:
the pheromone concentration determining subunit is used for determining the pheromone concentration of each order-picking vehicle in the path of the environment grid map according to a wolf colony algorithm if the position of the order-picking vehicle is the arrival target point and the maximum iteration number is not reached;
and the pheromone concentration updating subunit is used for updating the pheromone concentration until the updated pheromone concentration converges.
Optionally, the wolf pack algorithm is a prey assignment principle.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
according to the method and the system for planning the steel logistics route based on navigation positioning, provided by the invention, the optimal route is searched by utilizing the heuristic function combining the valuation function and the transfer constraint, so that the problems that the heuristic function in the conventional basic route planning algorithm usually needs longer searching time and the global optimal route is not easy to search are solved. The scheme in the heuristic information in the algorithm can improve the convergence speed of the algorithm and can effectively and quickly plan the global optimal path.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise.
FIG. 1 is a schematic flow chart of a steel logistics route planning method based on navigation positioning according to the present invention;
FIG. 2 is a schematic structural diagram of an iron and steel logistics order dispatching system;
FIG. 3 is an environmental grid map;
FIG. 4 is a graph of the impact of expected heuristic factors and pheromone stimulus factors on the algorithm;
FIG. 5 is a flow chart of an application of the present invention in actual path planning and navigation;
fig. 6 is a schematic structural diagram of a steel logistics route planning system based on navigation positioning provided by the invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention aims to provide a steel logistics route planning method and a steel logistics route planning system based on navigation positioning, which can effectively and quickly plan a global optimal route.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
Fig. 1 is a schematic flow diagram of a steel logistics route planning method based on navigation positioning according to the present invention, and as shown in fig. 1, the steel logistics route planning method based on navigation positioning according to the present invention is applied to a steel logistics order dispatching system, wherein the steel logistics order dispatching system is schematically shown in fig. 2 and generally includes an interface layer, an application layer, a vehicle-mounted terminal, and an enterprise terminal. The system applied by the invention carries out system layering and intermodule interaction by virtue of the architectural advantages and aiming at the problem that the prior art is not convenient, quick and flexible to check, the work of interaction with a user is left to the interface layer, and the platform application layer only processes the core logic, so that the request response time is shortened, the service quality and the resource utilization rate are improved, and the platform is lighter. The following description and description are presented in conjunction with specific implementation steps.
Step 1: and the vehicle-mounted terminal receives the order dispatching information. Firstly, an enterprise end administrator can intelligently distribute vehicles according to the detailed information such as enterprise requirements, the quantity and the types of steel, one vehicle with more single cars, one vehicle with more cars and the like. After the vehicle-mounted terminal receives the order dispatching information, the driver is reminded to take the order, and the driver can check detailed information such as order destination, order price, steel type and quantity in real time after taking the order. The driver will finish the delivery of the steel logistics outside and inside the factory according to the detailed navigation instruction of the vehicle-mounted terminal, and can report the abnormal information to the enterprise terminal when the driver or the vehicle is abnormal. And an enterprise end administrator is responsible for exception handling, so that the safety of a driver is ensured in real time.
Step 2: the interface layer ensures normal operation of data acquisition, real-time navigation and fault reporting functions. The data acquisition interface is responsible for regularly acquiring data information including vehicle position information, abnormal information and the like. And the collected information is sent to a real-time navigation interface or a fault reporting interface in a classified manner, the two interfaces can process the data information received by the data collection interface and send the data information to an application layer module in a classified manner, and the data information is delivered to an application layer for further processing.
And step 3: the application layer processes various requests received from the interface layer and responds in time. The application layer is used for providing core technical support for each function of the interface layer and comprises a data communication module for processing various data information, a path planning algorithm module for searching a global optimal path and providing response real-time property, a car warehouse matching model module for matching a car and a warehouse according to the information of the car and steel, and an exception reporting processing module. The data communication module processes various collected data information, classifies the obtained data information according to the request type, and sends the classified data information to different model modules respectively.
And 4, step 4: and the core algorithm module classifies the request. The core model of the application layer mainly comprises a path planning algorithm module, a car cabin matching model module and an exception reporting processing module. The path planning algorithm is mainly realized based on basic algorithms such as a path planning algorithm of navigation and positioning. The route planning algorithm module solves the route planning and scheduling problem of the vehicle in steel delivery by introducing a shortest path planning algorithm, and improves the delivery efficiency of the vehicle in the processes of loading, unloading, transporting and the like. The vehicle cabin matching model is matched, and the requirements of few queuing and rapid loading and unloading of vehicles in and out of a field in the whole transportation process can be well met. The vehicle cabin matching module is responsible for referring to the type of the vehicle, such as whether the vehicle is a dump truck or not, the specification and the size of the vehicle and the like, and selecting a cargo allocation or unloading workshop for the vehicle according to the type of the warehouse, such as the type of goods, whether the warehouse has a waste processing workshop or not and the like. The exception reporting module can process exception requests of drivers and report the exception requests to an enterprise terminal, so that the safety of the drivers and goods is guaranteed.
And 5: the enterprise administrator can monitor the order and the vehicle information in real time, including the estimated delivery time of the order, the real-time position of the vehicle and the like. And according to the received abnormal information of the vehicle, timely performing fault response processing.
The path planning algorithm module is combined with the two environments inside and outside the factory to perform real-time navigation on the vehicle so as to perform accurate and user-friendly real-time navigation. For the navigation technologies of the navigation technology required by the logistics distribution of the steel plant, the specific navigation steps are to obtain a proper path according to an electronic map and a path planning algorithm, and then to guide the vehicle route through navigation.
The purchasing and logistics are different distribution functions, and the navigation scenes outside the factory are similar, while the navigation scenes inside the factory are different. For a purchasing module, a navigation system is required to provide driving direction information meeting the requirements of a factory according to the type of a vehicle and the type of raw materials in the factory, and the vehicle is guided to complete links such as sign-in, weighing, radioactive inspection, quality inspection and unloading according to a specified path. For the sales module, the system is required to provide a positioning navigation function from the whole transportation vehicle, provide driving direction information meeting the requirements of a factory according to the vehicle type and the product type in the factory and guide the vehicle to complete links such as sign-in, printing, picking-up and distributing orders, weighing, loading and leaving according to a specified path.
The invention provides a steel logistics route planning method based on navigation positioning, which comprises the following steps:
s101, acquiring a starting point and a target point of the movement of the order receiving vehicle according to order information;
s102, determining an environment grid map by adopting a grid method according to the working environment of the movement of the order receiving vehicle; the grid array is used for representing the path condition. Each grid point is either in free space or in obstacle space. If one part of the grid points is free space and the other part of the grid points is obstacles, the grid points are assigned to the free space or the obstacle space according to the proportion occupied by the free space and the obstacles.
The grid is represented as follows:
s103, determining the steel logistics route of the order receiving vehicle by adopting a heuristic function combining an evaluation function and a transfer constraint according to the starting point and the target point of the movement of the order receiving vehicle and the environment space.
S103 specifically comprises the following steps:
initializing the information of the order-accepting vehicle; the information includes: the method comprises the following steps of (1) vehicle number m, vehicle positions, pheromone excitation factors alpha, expected heuristic factors beta, pheromone volatilization coefficients rho, pheromone intensity coefficients Q, maximum iteration times N, pheromone excitation factors and path directions;
determining the position of the order receiving vehicle in the environment grid map according to the initialized information; i.e. vehicle k (k ═ 1, 2, …, n) is placed on the current (grid) node.
As shown in figure 3 of the drawings,
wherein tau is0Is an initial value of pheromone, C is greater than tau0Is constant.
Determining a state transition probability value according to a heuristic function combining the valuation function and the transfer constraint;
using formula specifically
Determining a state transition probability value; and comprehensively judging and selecting the next moving grid based on the factors such as pheromone concentration, heuristic factors, path direction and the like, and calculating the probability from the current node to the next node.
Wherein, tauijPheromone values from grid i to grid j, and alpha is a pheromone exciting factor and represents the influence degree of the pheromone values on path selection. Beta is an expected heuristic factor representing the degree of influence of heuristic information on the vehicle routing;
ηijheuristic information for grid i to grid j:
dijrepresents the Euclidean distance between node i and node j, (x)i，yi) And (x)j，yj) Is the coordinates of grid i and grid j:
the allowedk stores the grid set that can be selected by the vehicle in grid i at this time.
Determining the position of the order receiving vehicle in the environment grid map at the next moment by adopting a roulette method according to the state transition probability value; judging whether the order receiving vehicle reaches a target point or the maximum iteration number;
if the target point is not reached and the maximum iteration times are not reached, updating the information of the order taking vehicle according to the position of the order taking vehicle in the environment grid map at the next moment, and returning to the step of determining the state transition probability value according to the heuristic function combining the valuation function and the transfer constraint until the target point is reached or the maximum iteration times are reached;
and if the order receiving vehicle reaches the target point or the maximum iteration number is reached, determining the steel logistics route of the order receiving vehicle according to the path of the order receiving vehicle in the environment grid map.
If the positions of the order-picking vehicles reach the target point and the maximum iteration times are not reached, determining the pheromone concentration of each order-picking vehicle in the path of the environment grid map according to a wolf pack algorithm; the wolf pack algorithm is a prey allocation principle.
The prey distribution principle in the wolf colony algorithm is fused in the path planning algorithm, the fusion process can be roughly understood as that the pheromone concentration on the high-quality path in the ant colony algorithm is enhanced, the experience of a weaker individual is not considered in a focused manner due to low reference value, more vehicles can absorb the experience of the high-quality individual conveniently, and the convergence speed is improved.
By adopting an updating mechanism of 'strong person survival' in the wolf colony algorithm, the global searching capability can be effectively improved, the situation that the solution falls into the local optimal solution is avoided, and the continuously updated pheromone represents the route-finding intelligence formed by the ant colony in the whole path searching process, so that the intelligent optimization algorithm is favorable for better learning a solution space.
Calculating the length of the motion trail of each vehicle, enhancing the pheromone left by the vehicle with the shortest route reaching the target point, weakening the pheromone left by the vehicle with the longest route, and highlighting different routes
The pheromone is differentiated.
And updating the pheromone concentration until the updated pheromone concentration converges.
The pheromone updating formula corresponding to the prey matching principle is as follows:
wherein, Delta tauijAnd Δ τijRespectively representing the sizes of pheromones of the optimal path and the worst path passing through the nodes i and j in each iteration, wherein the detailed formula is represented in an interval form:
wherein, L and L respectively represent the shortest motion track and the longest motion track of each vehicle reaching the target point, and delta and omega respectively represent the number of vehicles finding the shortest path and the longest path in each search; q2To enhance the factor, it is set here to 1; r is1To reduce the factor, set its value to 0.5;
meanwhile, the number of the pheromones is ensured to meet the following conditions:
turning factors are added into the consideration range in the path planning algorithm, and if the number of times of turning of the vehicle is too large, the delivery time length and the delivery cost of the vehicle are increased. Therefore, the invention enables the vehicle to select paths with smaller turning angles and fewer times as much as possible, and if the turning angles between nodes in one path are too large, the heuristic function value is reduced. And finally, the vehicle is optimally selected based on two factors of the path length and the turning angle. The final improved heuristic function is as follows:
where Q1 is a constant greater than 1.
The algorithm should communicate with the server, the monitoring center, and the in-vehicle terminal, as shown in fig. 5. The steel logistics server can make reasonable path planning for the running route of the vehicle through communication with the communication base station and the vehicle-mounted mobile driver end, and send a real-time navigation instruction to the driver end. The client, namely the mobile driver terminal, sends navigation requirements to the server terminal through the wireless communication network, receives scheduling commands, drives vehicles and delivers goods according to the navigation instructions, and can also feed back the running conditions of the delivered vehicles to the enterprise terminal, and the enterprise terminal can monitor and guarantee the safety of the vehicles and drivers in real time.
Fig. 6 is a schematic structural diagram of a steel logistics route planning system based on navigation positioning, as shown in fig. 6, the steel logistics route planning system based on navigation positioning, provided by the invention, includes:
an origin and target point obtaining module 601, configured to obtain an origin and a target point of a motion of an order receiving vehicle according to the order information;
an environment grid map determining module 602, configured to determine an environment grid map by using a grid method according to a working environment of movement of the order receiving vehicle;
and the steel logistics route determining module 603 is used for determining the steel logistics route of the order receiving vehicle by adopting a heuristic function combining an evaluation function and a transfer constraint according to the starting point and the target point of the movement of the order receiving vehicle and the environment space.
The steel logistics route determining module 603 specifically includes:
the information initialization unit is used for initializing the information of the order-accepting vehicle; the information includes: the system comprises the following components, namely vehicle quantity, vehicle positions, pheromone excitation factors, expected heuristic factors, pheromone volatilization coefficients, pheromone intensity coefficients, maximum iteration times, pheromone excitation factors and path directions;
the position determining unit is used for determining the position of the order receiving vehicle in the environment grid map according to the initialized information;
the state transition probability value determining unit is used for determining the state transition probability value according to a heuristic function combining the valuation function and the handover constraint;
the position updating unit is used for determining the position of the order receiving vehicle in the environment grid map at the next moment by adopting a roulette method according to the state transition probability value; judging whether the order receiving vehicle reaches a target point or the maximum iteration number;
the iteration unit is used for updating the information of the order receiving vehicle according to the position of the order receiving vehicle in the environment grid map at the next moment if the order receiving vehicle does not reach the target point and the maximum iteration times are not reached, and returning to the step of determining the state transition probability value according to the heuristic function combining the evaluation function and the transfer-of constraint until the target point is reached or the maximum iteration times are reached;
and the steel logistics route determining unit is used for determining the steel logistics route of the order receiving vehicle according to the route of the order receiving vehicle in the environment grid map if the order receiving vehicle reaches a target point or reaches the maximum iteration number.
The steel logistics route determining unit specifically comprises:
the pheromone concentration determining subunit is used for determining the pheromone concentration of each order-picking vehicle in the path of the environment grid map according to a wolf pack algorithm if the position of the order-picking vehicle is the arrival target point and the maximum iteration number is not reached;
and the pheromone concentration updating subunit is used for updating the pheromone concentration until the updated pheromone concentration converges.
The wolf pack algorithm is a prey allocation principle.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. For the system disclosed by the embodiment, the description is relatively simple because the system corresponds to the method disclosed by the embodiment, and the relevant points can be referred to the method part for description.
The principles and embodiments of the present invention have been described herein using specific examples, which are provided only to help understand the method and the core concept of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In view of the above, the present disclosure should not be construed as limiting the invention.
Claims (8)
1. A steel logistics route planning method based on navigation positioning is applied to a steel logistics order dispatching system and is characterized by comprising the following steps:
acquiring a starting point and a target point of the movement of the order receiving vehicle according to the order information;
determining an environment grid map by adopting a grid method according to the working environment of the movement of the order receiving vehicle;
and determining the steel logistics route of the order receiving vehicle by adopting a heuristic function combining an evaluation function and a transfer constraint according to the starting point and the target point of the movement of the order receiving vehicle and the environment space.
2. The method as claimed in claim 1, wherein the step of determining the steel logistics route of the order receiving vehicle by using a heuristic function combining an evaluation function and a transfer constraint according to the starting point and the target point of the movement of the order receiving vehicle and the environmental space comprises:
initializing the information of the order-accepting vehicle; the information includes: the system comprises the following components, namely vehicle quantity, vehicle positions, pheromone excitation factors, expected heuristic factors, pheromone volatilization coefficients, pheromone intensity coefficients, maximum iteration times, pheromone excitation factors and path directions;
determining the position of the order receiving vehicle in the environment grid map according to the initialized information;
determining a state transition probability value according to a heuristic function combining the valuation function and the transfer constraint;
determining the position of the order receiving vehicle in the environment grid map at the next moment by adopting a roulette method according to the state transition probability value; judging whether the order receiving vehicle reaches a target point or the maximum iteration number;
if the target point is not reached and the maximum iteration times are not reached, updating the information of the order taking vehicle according to the position of the order taking vehicle in the environment grid map at the next moment, and returning to the step of determining the state transition probability value according to the heuristic function combining the valuation function and the transfer constraint until the target point is reached or the maximum iteration times are reached;
and if the order receiving vehicle reaches the target point or the maximum iteration number is reached, determining the steel logistics route of the order receiving vehicle according to the path of the order receiving vehicle in the environment grid map.
3. The steel logistics route planning method based on navigation and positioning as claimed in claim 2, wherein if the destination point is reached or the maximum number of iterations is reached, the steel logistics route of the order receiving vehicle is determined according to the route of the order receiving vehicle in the environmental grid map, specifically comprising:
if the positions of the order-picking vehicles reach the target point and the maximum iteration times are not reached, determining the pheromone concentration of each order-picking vehicle in the path of the environment grid map according to a wolf pack algorithm;
and updating the pheromone concentration until the updated pheromone concentration converges.
4. The steel logistics routing method based on navigation positioning as claimed in claim 3, wherein the wolf pack algorithm is a prey allocation principle.
5. A steel logistics route planning system based on navigation positioning is applied to a steel logistics order dispatching system, and is characterized by comprising:
the starting point and target point acquisition module is used for acquiring the moving starting point and target point of the order receiving vehicle according to the order information;
the environment grid map determining module is used for determining an environment grid map by adopting a grid method according to the working environment of the movement of the order receiving vehicle;
and the steel logistics route determining module is used for determining the steel logistics route of the order receiving vehicle by adopting a heuristic function combining an evaluation function and a transfer constraint according to the starting point and the target point of the movement of the order receiving vehicle and the environment space.
6. The system of claim 5, wherein the steel logistics route determination module specifically comprises:
the information initialization unit is used for initializing the information of the order-accepting vehicle; the information includes: the system comprises the following components, namely vehicle quantity, vehicle positions, pheromone excitation factors, expected heuristic factors, pheromone volatilization coefficients, pheromone intensity coefficients, maximum iteration times, pheromone excitation factors and path directions;
the position determining unit is used for determining the position of the order receiving vehicle in the environment grid map according to the initialized information;
the state transition probability value determining unit is used for determining the state transition probability value according to a heuristic function combining the valuation function and the handover constraint;
the position updating unit is used for determining the position of the order receiving vehicle in the environment grid map at the next moment by adopting a roulette method according to the state transition probability value; judging whether the order receiving vehicle reaches a target point or the maximum iteration number;
the iteration unit is used for updating the information of the order receiving vehicle according to the position of the order receiving vehicle in the environment grid map at the next moment if the order receiving vehicle does not reach the target point and does not reach the maximum iteration times, and returning to the step of determining the state transition probability value according to the heuristic function combined with the valuation function and the transfer constraint until the order receiving vehicle reaches the target point or reaches the maximum iteration times;
and the steel logistics route determining unit is used for determining the steel logistics route of the order receiving vehicle according to the route of the order receiving vehicle in the environment grid map if the order receiving vehicle reaches a target point or reaches the maximum iteration number.
7. The system of claim 6, wherein the steel logistics route determination unit specifically comprises:
the pheromone concentration determining subunit is used for determining the pheromone concentration of each order-picking vehicle in the path of the environment grid map according to a wolf colony algorithm if the position of the order-picking vehicle is the arrival target point and the maximum iteration number is not reached;
and the pheromone concentration updating subunit is used for updating the pheromone concentration until the updated pheromone concentration converges.
8. The system of claim 7, wherein the wolf pack algorithm is game assignment rule.
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