CN115809752B - Low-carbon logistics path planning method, device, equipment and storage medium - Google Patents
Low-carbon logistics path planning method, device, equipment and storage medium Download PDFInfo
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- CN115809752B CN115809752B CN202310070908.9A CN202310070908A CN115809752B CN 115809752 B CN115809752 B CN 115809752B CN 202310070908 A CN202310070908 A CN 202310070908A CN 115809752 B CN115809752 B CN 115809752B
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Abstract
The invention relates to the technical field of intelligent logistics and discloses a low-carbon logistics path planning method, a device, equipment and a storage medium. The low-carbon logistics path planning method comprises the following steps: the method comprises the steps of obtaining a delivery starting point and a delivery ending point of a current stage, generating a plurality of delivery routes, calculating carbon emission generated when a delivery vehicle runs on each delivery route according to an actual load value of the current stage of the delivery vehicle, and comparing and selecting a delivery route with the minimum carbon emission as an actually adopted route. According to the invention, the carbon emission amount is calculated based on the load of the delivery vehicle, and the path planning is performed, so that the carbon emission amount of the whole delivery path is reduced, and the accuracy of the carbon emission amount calculation and the path planning accuracy are improved.
Description
Technical Field
The invention relates to the field of intelligent logistics, in particular to a low-carbon logistics path planning method, device, equipment and storage medium.
Background
Carbon emissions refer to greenhouse gas emissions that cause a greenhouse effect and raise the global air temperature, and carbon emissions refer to the average greenhouse gas emissions produced during production, transportation, use and recovery of the product. In order to protect the environment, low-carbon life is advocated in recent years, carbon emission is reduced, green development is promoted, and reasonable path planning can effectively reduce carbon emission for automobiles, particularly distribution vehicles.
In the prior art, the mainstream carbon emission formulas in the market at present calculate the carbon emission of the automobile according to energy sources or calculate the carbon emission according to the complicating factors (vehicle speed, vehicle information, travel distance and the like), however, the carbon emission formulas do not consider the influence of the weight of the vehicle body. The approximate carbon emission is estimated through the driving distance and the vehicle information, and the vehicle is loaded and unloaded each time a delivery end point is passed, so that the weight of the vehicle is reduced, and the relationship between the weight of the vehicle body and the energy consumption is considered, so that the subsequent carbon emission calculation is influenced, and the final planned simulation route is inaccurate.
Disclosure of Invention
The invention mainly aims to provide a low-carbon logistics path planning method, a device, equipment and a storage medium, and aims to solve the technical problem of inaccurate path planning based on carbon emission in the prior art.
The first aspect of the invention provides a low-carbon logistics path planning method, which comprises the following steps:
acquiring a distribution starting point and a distribution ending point of the current stage;
generating a plurality of delivery routes based on the delivery start point and the delivery end point;
acquiring an actual load value of a delivery vehicle at the current stage, and calculating the carbon emission of the delivery vehicle in each delivery route by applying a preset carbon emission formula based on the actual load value;
and comparing the carbon emission amounts, and selecting a distribution route with the smallest carbon emission amount as a logistics path adopted in the current stage.
Optionally, in a first implementation manner of the first aspect of the present invention, before the acquiring the dispensing start point and the dispensing end point of the current stage, the method further includes:
acquiring a distribution center, each point to be distributed and the weight of goods to be distributed at each point to be distributed;
and carrying out path planning by applying a preset path planning algorithm based on the distribution center, the points to be distributed and the weight of the goods to be distributed at the points to be distributed, so as to obtain the distribution sequence of the points to be distributed.
Optionally, in a second implementation manner of the first aspect of the present invention, the applying a preset path planning algorithm to perform path planning based on the weight of the goods to be delivered by the delivery center, each point to be delivered, and each point to be delivered, to obtain a delivery sequence of each point to be delivered includes:
taking the delivery center or the delivery end point of the previous stage as the delivery start point of the current stage, and determining the delivery sequence of each point to be delivered by applying a preset algorithm;
and selecting the first point to be delivered as the delivery end point of the current stage.
Optionally, in a third implementation manner of the first aspect of the present invention, the determining, using a preset algorithm, a delivery sequence of each point to be delivered with the delivery center or a delivery end point of a previous stage as a delivery start point of a current stage includes:
s11, selecting a plurality of individuals as a first group according to the carbon emission, wherein the individuals are distribution sequences of the points to be distributed;
s12, based on the first population, sequentially performing crossover operation and mutation operation to obtain a second population;
and S13, taking the second group as a new first group, repeatedly executing the step S12 until the iteration condition is met, and selecting an individual with the highest probability as the distribution sequence of each point to be distributed.
Optionally, in a fourth implementation manner of the first aspect of the present invention, the selecting a plurality of individuals according to the carbon emission amount as the first group includes:
generating a plurality of distribution orders of the points to be distributed by a preset method and coding the generated distribution orders, wherein the distribution order of the points to be distributed is an individual, and each code corresponds to an individual;
and calculating the carbon emission generated by the delivery vehicle when each individual is used as a delivery sequence, and selecting a plurality of individuals with the smallest generated carbon emission as the first group.
Optionally, in a fifth implementation manner of the first aspect of the present invention, the sequentially performing a crossover operation and a mutation operation based on the first group to obtain a second group includes:
randomly pairing individuals in the first group, and performing cross operation on each pair of individuals by applying a sequence cross operator to obtain a third group;
and carrying out mutation operation on individuals in the third group according to preset probability to obtain the second group.
Optionally, in a sixth implementation manner of the first aspect of the present invention, the carbon emission formula is as follows:
；
wherein T represents carbon emission, S represents distance between two points, G represents vehicle body weight, C represents carbon emission factor, M 1 Representing the actual load value of the delivery vehicle, M 2 Indicating the maximum load value of the delivery vehicle.
The second aspect of the present invention provides a low-carbon logistics path planning apparatus, comprising:
the first acquisition module is used for acquiring a distribution starting point and a distribution ending point of the current stage;
the route generation module is used for generating a plurality of delivery routes based on the delivery starting point and the delivery ending point;
the calculation module is used for obtaining an actual load value of the delivery vehicle at the current stage, and calculating the carbon emission of the delivery vehicle in each delivery route by applying a preset carbon emission formula based on the actual load value;
and the comparison module is used for comparing the carbon emission amounts and selecting a distribution route with the minimum carbon emission amount as a logistics path adopted in the current stage.
Optionally, in a first implementation manner of the second aspect of the present invention, the low-carbon logistics path planning apparatus further includes:
the second acquisition module is used for acquiring the distribution center, each point to be distributed and the weight of the goods to be distributed at each point to be distributed;
and the path planning module is used for carrying out path planning by applying a preset path planning algorithm based on the distribution center, the points to be distributed and the weight of the goods to be distributed at the points to be distributed, so as to obtain the distribution sequence of the points to be distributed.
Optionally, in a second implementation manner of the second aspect of the present invention, the path planning module includes:
the calculating unit is used for determining the distribution sequence of each point to be distributed by using a preset algorithm by taking the distribution center or the distribution end point of the previous stage as the distribution start point of the current stage;
and the selection unit is used for selecting the first point to be delivered as the delivery end point of the current stage.
Optionally, in a third implementation manner of the second aspect of the present invention, the calculating unit is specifically configured to:
s11, selecting a plurality of individuals as a first group according to the carbon emission, wherein the individuals are distribution sequences of the points to be distributed;
s12, based on the first population, sequentially performing crossover operation and mutation operation to obtain a second population;
and S13, taking the second group as a new first group, repeatedly executing the step S12 until the iteration condition is met, and selecting an individual with the highest probability as the distribution sequence of each point to be distributed.
Optionally, in a fourth implementation manner of the second aspect of the present invention, the selecting a plurality of individuals as the first group according to the carbon emission amount includes:
generating a plurality of distribution orders of the points to be distributed by a preset method and coding the generated distribution orders, wherein the distribution order of the points to be distributed is an individual, and each code corresponds to an individual;
and calculating the carbon emission generated by the delivery vehicle when each individual is used as a delivery sequence, and selecting a plurality of individuals with the smallest generated carbon emission as the first group.
Optionally, in a fifth implementation manner of the second aspect of the present invention, the sequentially performing crossover and mutation operations based on the first population to obtain a second population includes:
randomly pairing individuals in the first group, and performing cross operation on each pair of individuals by applying a sequence cross operator to obtain a third group;
and carrying out mutation operation on individuals in the third group according to preset probability to obtain the second group.
Optionally, in a sixth implementation manner of the second aspect of the present invention, the carbon emission formula is as follows:
；
wherein T represents carbon emission, S represents distance between two points, G represents vehicle body weight, C represents carbon emission factor, M 1 Representing the actual load value of the delivery vehicle, M 2 Indicating the maximum load value of the delivery vehicle.
A third aspect of the present invention provides an electronic device, comprising: a memory and at least one processor, the memory having instructions stored therein; the at least one processor invokes the instructions in the memory to cause the electronic device to perform the low carbon logistics path planning method described above.
A fourth aspect of the present invention provides a computer readable storage medium having instructions stored therein which, when run on a computer, cause the computer to perform the above-described low carbon logistics path planning method.
According to the technical scheme provided by the invention, the distribution starting point and the distribution ending point of the current stage are obtained, a plurality of distribution routes are generated, the carbon emission generated when the distribution vehicle runs on each distribution route is calculated according to the actual load value of the current stage of the distribution vehicle, and the distribution route with the minimum carbon emission is compared and selected as the actual adopted route. According to the invention, the carbon emission amount is calculated based on the load of the delivery vehicle, and the path planning is performed, so that the carbon emission amount of the whole delivery path is reduced, and the accuracy of the carbon emission amount calculation and the path planning accuracy are improved.
Drawings
FIG. 1 is a schematic diagram of an embodiment of a method for planning a low-carbon logistics path according to the present invention;
FIG. 2 is a schematic diagram of another embodiment of a method for planning a path of a low-carbon stream according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of an embodiment of a low-carbon logistics path planning apparatus according to the present invention;
FIG. 4 is a schematic diagram of another embodiment of a low-carbon logistics path planning apparatus according to the embodiment of the present invention;
fig. 5 is a schematic diagram of an embodiment of an electronic device according to an embodiment of the present invention.
Detailed Description
The embodiment of the invention provides a low-carbon logistics path planning method, a device, equipment and a storage medium, which are used for calculating carbon emission based on the load of a delivery vehicle and planning a path, so that the carbon emission of the whole delivery path is reduced, and the accuracy of the carbon emission calculation and the accuracy of the path planning are improved.
The terms "first," "second," "third," "fourth" and the like in the description and in the claims and in the above drawings, if any, are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments described herein may be implemented in other sequences than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed or inherent to such process, method, article, or apparatus.
For ease of understanding, a specific flow of an embodiment of the present invention is described below, referring to fig. 1, and an embodiment of a low-carbon logistics path planning method in an embodiment of the present invention includes:
101. acquiring a distribution starting point and a distribution ending point of the current stage;
it can be understood that the execution body of the present invention may be a low-carbon logistics path planning device, and may also be a terminal or a server, which is not limited herein. The embodiment of the invention is described by taking a server as an execution main body as an example.
In this embodiment, the distribution vehicle starts from the distribution center in the whole distribution process, sequentially passes through each distribution point according to a preset distribution sequence, and needs to be unloaded when passing through one distribution point until reaching the last distribution point, and returns to the distribution center after all the cargoes are delivered.
In this embodiment, the logistics distribution includes a plurality of stages, and the logistics distribution sequentially passes through each distribution point according to a preset distribution sequence, wherein the distribution end point of the previous stage is the distribution start point of the current stage, and when the logistics distribution end point of the current stage is reached and the unloading is completed, the distribution of the current stage is completed.
In this embodiment, the weight of the goods to be delivered at each delivery point is not limited, and the total weight of the goods to be delivered at each delivery point does not exceed the maximum load value of the delivery vehicle.
102. Generating a plurality of delivery routes based on the delivery start point and the delivery end point;
in this embodiment, the delivery route is a feasible route from the delivery start point to the delivery end point, and the generation method is not limited.
Optionally, in an embodiment, the feasible routes are obtained through an existing map API, such as: the feasible routes are determined by a Goldmap API, a Tencel map API, or a hundred degree map API.
103. Acquiring an actual load value of a delivery vehicle at the current stage, and calculating the carbon emission of the delivery vehicle in each delivery route by applying a preset carbon emission formula based on the actual load value;
in this embodiment, the actual load value of the delivery vehicle at the current stage is the total weight of the load carried by the delivery vehicle at the current stage.
Optionally, in an embodiment, the carbon emission formula is as follows:
；
wherein T represents carbon emission, S represents distance between two points, G represents vehicle body weight, C represents carbon emission factor, M 1 Representing the actual load value of the delivery vehicle, M 2 Indicating the maximum load value of the delivery vehicle.
In the present embodiment, S represents the travel distance of the selected delivery route.
104. And comparing the carbon emission amounts, and selecting a distribution route with the smallest carbon emission amount as a logistics path adopted in the current stage.
In this embodiment, the delivery route with the smallest carbon emission is selected as the actual travel route in the current stage, and the route with the smallest carbon emission is selected in each stage, and when the preset delivery sequence of each delivery point is the delivery sequence with the smallest carbon emission, the carbon emission of the whole delivery process is the smallest.
In the embodiment of the invention, a delivery starting point and a delivery ending point of the current stage are obtained, a plurality of delivery routes are generated, the carbon emission generated when the delivery vehicle runs on each delivery route is calculated according to the actual load value of the current stage of the delivery vehicle, and the delivery route with the minimum carbon emission is compared and selected as the actual adopted route. According to the invention, the carbon emission amount is calculated based on the load of the delivery vehicle, and the path planning is performed, so that the carbon emission amount of the whole delivery path is reduced, and the accuracy of the carbon emission amount calculation and the path planning accuracy are improved.
Referring to fig. 2, another embodiment of a low-carbon logistics path planning method according to the embodiment of the present invention includes:
201. acquiring a distribution center, each point to be distributed and the weight of goods to be distributed at each point to be distributed;
202. based on the distribution center, the points to be distributed and the weight of the goods to be distributed at the points to be distributed, a preset path planning algorithm is applied to carry out path planning, and the distribution sequence of the points to be distributed is obtained;
in this embodiment, the path planning algorithm is not limited, but the result should be the optimal solution with the least carbon emissions in all possible paths.
Optionally, in an embodiment, the step 202 includes:
taking the delivery center or the delivery end point of the previous stage as the delivery start point of the current stage, and determining the delivery sequence of each point to be delivered by applying a preset algorithm;
and selecting the first point to be delivered as the delivery end point of the current stage.
In this embodiment, each stage needs to apply a preset path planning algorithm to perform path planning, so as to obtain the distribution sequence of each point to be distributed calculated in the current stage, and select the first point to be distributed in the distribution sequence of the current stage as the distribution end point of the previous stage.
In this embodiment, the first stage uses the delivery center as the delivery start point, and the delivery end point of the subsequent stage is the delivery start point.
In this embodiment, a preset algorithm is used to obtain the distribution sequence of each point to be distributed, and the adopted algorithm is not limited, and includes, but is not limited to, a genetic algorithm, a simulated annealing algorithm, a neural network, and the like.
In this embodiment, after determining the delivery sequence of each point to be delivered, the first point to be delivered is the delivery end point of the current stage, and the weight of the delivery vehicle in each stage is different during the delivery process, and the weight of the delivery vehicle in the current stage is calculated during the calculation of the algorithm, so that the delivery sequence of the remaining points to be delivered needs to be determined by reapplying the preset algorithm in each stage.
Optionally, in an embodiment, the determining, using a preset algorithm, the dispensing sequence of each point to be dispensed with the dispensing center or the dispensing end point of the previous stage as the dispensing start point of the current stage includes:
s11, selecting a plurality of individuals as a first group according to the carbon emission, wherein the individuals are distribution sequences of the points to be distributed;
s12, based on the first population, sequentially performing crossover operation and mutation operation to obtain a second population;
and S13, taking the second group as a new first group, repeatedly executing the step S12 until the iteration condition is met, and selecting an individual with the highest probability as the distribution sequence of each point to be distributed.
In this embodiment, each individual is a distribution sequence of points to be distributed, and the determining method of the population scale (the number of individuals) of the first population in step S11 is not limited, but the population scale is too large, which results in an increase in calculation amount, and the population scale is too small and is easy to fall into a locally optimal solution, so that the population scale needs to be comprehensively considered based on the calculation amount and the accuracy.
In this embodiment, the fitness is used to evaluate the quality of each individual, and a plurality of optimal individuals are selected according to the fitness, and the specific selection method is not limited.
Optionally, in an embodiment, a fourth population with a preset population size is randomly generated, wherein each individual in the fourth population is different, the fitness of each individual in the fourth population is calculated and converted into a maximized problem, the converted value is calculated to be a percentage of the total conversion value of the fourth population, the value is used as the probability of each individual being selected, each probability value corresponds to a region, the sum of the probability values is 1, the regions together form a complete region, a random number with the population size of 0-1 is randomly generated, the number of times that each individual is selected is determined according to the number of times that the random number appears in the probability region, and the selected result is used as the first population, wherein the number of the individuals of the first population is the same as that of the fourth population.
Alternatively, in one embodiment, a number of individuals are randomly selected from the population at a time, and one of the individuals that is optimal is selected to enter the offspring population based on the fitness value, and the operation is repeated until the new offspring population size reaches the original population size, the new offspring population being the first population.
In this embodiment, the crossover operation and the mutation operation are used to change the individual with a certain probability, and generate a new individual to find the optimal solution individual.
In this embodiment, the iteration conditions are not limited, for example: and (5) reaching the preset iteration times, and enabling the probability of one individual in the second group to reach a preset probability value.
In this embodiment, the probability of an individual, i.e., its fitness, is a proportion of the total fitness of the individuals in the population currently being generated.
Optionally, in an embodiment, the selecting a number of individuals as the first population according to the carbon emissions includes:
generating a plurality of distribution orders of the points to be distributed by a preset method and coding the generated distribution orders, wherein the distribution order of the points to be distributed is an individual, and each code corresponds to an individual;
and calculating the carbon emission generated by the delivery vehicle when each individual is used as a delivery sequence, and selecting a plurality of individuals with the smallest generated carbon emission as the first group.
In this embodiment, the method for generating the distribution sequence of each to-be-distributed point is not limited by the distribution sequence of each to-be-distributed point.
Optionally, in an embodiment, conditions are set according to a priori knowledge, and based on these conditions, a delivery order is generated, such as: all the points to be distributed need to appear and only appear once, and the distribution sequence of the points to be distributed is randomly generated based on the conditions.
In this embodiment, the encoding mode is not limited, for example: five points to be dispensed are represented by capital A, B, C, D, E, and randomly generated individuals CDEAB represent the order in which the individuals were C-D-E-A-B.
In this embodiment, the individual fitness, that is, the amount of carbon emissions generated by the delivery vehicle when the individual is in the delivery order.
Optionally, in an embodiment, based on the first group, sequentially performing a crossover operation and a mutation operation to obtain a second group includes:
randomly pairing individuals in the first group, and performing cross operation on each pair of individuals by applying a sequence cross operator to obtain a third group;
and carrying out mutation operation on individuals in the third group according to preset probability to obtain the second group.
In this embodiment, one individual indicates the distribution sequence of all distribution points for which the distribution sequence is not determined, and a group is formed by selecting a plurality of individuals with the smallest carbon emission, where the number of individuals in the group can be adjusted before the algorithm is applied, and the number of individuals in the first group is equal to the number of individuals in the second group.
In this embodiment, the individuals are encoded, and each individual is represented by a symbol string, such as: expressed as unsigned binary integers.
In this embodiment, the cross operation is an operation of exchanging a part of symbols between two individuals with a certain small probability, and the specific method adopted in the cross operation is not limited, and includes, but is not limited to, single-point cross, two-point cross, multi-point cross, uniform cross, and sequential cross.
Optionally, in an embodiment, the individuals in the first population are paired two by adopting a sequential crossing method, each pair includes a first individual and a second individual, a start position and an end position of crossing in a symbol string are randomly selected, the selected area of the first individual is copied to the same position of a third individual, symbols missing from the third individual in the second individual are sequentially filled into the third individual, the selected area of the second individual is copied to the same position of a fourth individual, symbols missing from the fourth individual in the first individual are sequentially filled into the fourth individual, and each third individual and each fourth individual form a third population after the crossover operation.
In this embodiment, the mutation operation is to change a certain character or a certain characters of an individual with a smaller probability, and the method adopted in the mutation operation is not limited.
Alternatively, in one embodiment, two characters of an individual are randomly selected for exchange, i.e., the order of delivery of two points to be delivered is exchanged.
203. Acquiring a distribution starting point and a distribution ending point of the current stage;
in this embodiment, the first point to be delivered in the delivery sequence of the current stage is selected as the delivery end point of the previous stage.
204. Generating a plurality of delivery routes based on the delivery start point and the delivery end point;
205. acquiring an actual load value of a delivery vehicle at the current stage, and calculating the carbon emission of the delivery vehicle in each delivery route by applying a preset carbon emission formula based on the actual load value;
206. and comparing the carbon emission amounts, and selecting a distribution route with the smallest carbon emission amount as a logistics path adopted in the current stage.
In the embodiment of the invention, based on the weight of goods to be delivered at each point to be delivered, a preset path planning algorithm is applied to carry out path planning to obtain the delivery sequence of each point to be delivered, the delivery starting point and the delivery ending point of the current stage are obtained, a plurality of delivery routes are generated, the carbon emission generated when the delivery vehicle runs on each delivery route is calculated according to the actual load value of the current stage of the delivery vehicle, and the delivery route with the minimum carbon emission is compared and selected as the actually adopted route. According to the invention, the carbon emission amount is calculated and the path planning is performed based on the load of the delivery vehicle, and meanwhile, the change of the load of the delivery vehicle after each delivery point is taken into consideration, so that the carbon emission amount of the whole delivery path is reduced, and the accuracy of the carbon emission amount calculation and the path planning accuracy are improved.
The method for planning a low-carbon logistics path in the embodiment of the present invention is described above, and the apparatus for planning a low-carbon logistics path in the embodiment of the present invention is described below, referring to fig. 3, where an embodiment of the apparatus for planning a low-carbon logistics path in the embodiment of the present invention includes:
a first obtaining module 301, configured to obtain a delivery start point and a delivery end point in a current stage;
a route generation module 302, configured to generate a plurality of delivery routes based on the delivery start point and the delivery end point;
a calculating module 303, configured to obtain an actual load value of a delivery vehicle at a current stage, and calculate, based on the actual load value, a carbon emission amount of the delivery vehicle traveling on each delivery route by applying a preset carbon emission formula;
and the comparison module 304 is configured to compare the carbon emissions, and select a distribution route with the smallest carbon emissions as a current flow path.
Optionally, the carbon emission formula is as follows:
；
wherein T represents carbon emission, S represents distance between two points, G represents vehicle body weight, C represents carbon emission factor, M 1 Representing the actual load value of the delivery vehicle, M 2 Representation ofThe maximum load value of the vehicle is distributed.
In the embodiment of the invention, a delivery starting point and a delivery ending point of the current stage are obtained, a plurality of delivery routes are generated, the carbon emission generated when the delivery vehicle runs on each delivery route is calculated according to the actual load value of the current stage of the delivery vehicle, and the delivery route with the minimum carbon emission is compared and selected as the actual adopted route. According to the invention, the carbon emission amount is calculated based on the load of the delivery vehicle, and the path planning is performed, so that the carbon emission amount of the whole delivery path is reduced, and the accuracy of the carbon emission amount calculation and the path planning accuracy are improved.
Referring to fig. 4, another embodiment of the low-carbon logistics path planning apparatus according to the embodiment of the present invention includes:
a first obtaining module 301, configured to obtain a delivery start point and a delivery end point in a current stage;
a route generation module 302, configured to generate a plurality of delivery routes based on the delivery start point and the delivery end point;
a calculating module 303, configured to obtain an actual load value of a delivery vehicle at a current stage, and calculate, based on the actual load value, a carbon emission amount of the delivery vehicle traveling on each delivery route by applying a preset carbon emission formula;
a comparison module 304, configured to compare the carbon emissions, and select a distribution route with the smallest carbon emissions as a current-stage logistics path;
a second obtaining module 305, configured to obtain the weight of the goods to be delivered from the delivery center to each point to be delivered;
and the path planning module 306 is configured to apply a preset path planning algorithm to perform path planning based on the distribution center, each point to be distributed, and the weight of the goods to be distributed at each point to be distributed, so as to obtain the distribution sequence of each point to be distributed.
Optionally, the path planning module 306 includes:
the calculating unit 3061 is configured to determine a delivery sequence of each point to be delivered by using a preset algorithm with the delivery center or a delivery end point of a previous stage as a delivery start point of a current stage;
a selecting unit 3062 for selecting the first point to be dispensed as the dispensing end point of the current stage
Optionally, the computing unit 3062 is specifically configured to:
s11, selecting a plurality of individuals as a first group according to the carbon emission, wherein the individuals are distribution sequences of the points to be distributed;
s12, based on the first population, sequentially performing crossover operation and mutation operation to obtain a second population;
and S13, taking the second group as a new first group, repeatedly executing the step S12 until the iteration condition is met, and selecting an individual with the highest probability as the distribution sequence of each point to be distributed.
Optionally, the selecting a number of individuals as the first group according to the carbon emission amount includes:
generating a plurality of distribution orders of the points to be distributed by a preset method and coding the generated distribution orders, wherein the distribution order of the points to be distributed is an individual, and each code corresponds to an individual;
and calculating the carbon emission generated by the delivery vehicle when each individual is used as a delivery sequence, and selecting a plurality of individuals with the smallest generated carbon emission as the first group.
Optionally, the step of sequentially performing the crossover and mutation operations based on the first population to obtain a second population includes:
randomly pairing individuals in the first group, and performing cross operation on each pair of individuals by applying a sequence cross operator to obtain a third group;
and carrying out mutation operation on individuals in the third group according to preset probability to obtain the second group.
In the embodiment of the invention, based on the weight of goods to be delivered at each point to be delivered, a preset path planning algorithm is applied to carry out path planning to obtain the delivery sequence of each point to be delivered, the delivery starting point and the delivery ending point of the current stage are obtained, a plurality of delivery routes are generated, the carbon emission generated when the delivery vehicle runs on each delivery route is calculated according to the actual load value of the current stage of the delivery vehicle, and the delivery route with the minimum carbon emission is compared and selected as the actually adopted route. According to the invention, the carbon emission amount is calculated and the path planning is performed based on the load of the delivery vehicle, and meanwhile, the change of the load of the delivery vehicle after each delivery point is taken into consideration, so that the carbon emission amount of the whole delivery path is reduced, and the accuracy of the carbon emission amount calculation and the path planning accuracy are improved.
The low-carbon logistics path planning device in the embodiment of the present invention is described in detail from the point of view of modularized functional entities in fig. 3 and fig. 4, and the electronic device in the embodiment of the present invention is described in detail from the point of view of hardware processing.
Fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present invention, where the electronic device 500 may have a relatively large difference due to different configurations or performances, and may include one or more processors (central processing units, CPU) 510 (e.g., one or more processors) and a memory 520, and one or more storage media 530 (e.g., one or more mass storage devices) storing application programs 533 or data 532. Wherein memory 520 and storage medium 530 may be transitory or persistent storage. The program stored on the storage medium 530 may include one or more modules (not shown), each of which may include a series of instruction operations in the electronic device 500. Still further, the processor 510 may be arranged to communicate with a storage medium 530 and to execute a series of instruction operations in the storage medium 530 on the electronic device 500.
The electronic device 500 may also include one or more power supplies 540, one or more wired or wireless network interfaces 550, one or more input/output interfaces 560, and/or one or more operating systems 531, such as Windows Serve, macOS X, unix, linux, freeBSD, and the like. It will be appreciated by those skilled in the art that the electronic device structure shown in fig. 5 is not limiting of the electronic device and may include more or fewer components than shown, or may combine certain components, or may be arranged in a different arrangement of components.
The invention also provides an electronic device comprising a memory and a processor, wherein the memory stores computer readable instructions which, when executed by the processor, cause the processor to execute the steps of the low-carbon logistics path planning method in the above embodiments.
The present invention also provides a computer readable storage medium, which may be a non-volatile computer readable storage medium, and may also be a volatile computer readable storage medium, where instructions are stored in the computer readable storage medium, when the instructions are executed on a computer, cause the computer to perform the steps of the low-carbon logistics path planning method.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, which are not repeated herein.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied essentially or in part or all of the technical solution or in part in the form of a software product stored in a storage medium, including instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a read-only memory (ROM), a random access memory (randomaccess memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (6)
1. The low-carbon logistics path planning method is characterized by comprising the following steps of:
acquiring a distribution center, each point to be distributed and the weight of goods to be distributed at each point to be distributed;
based on the distribution center, each point to be distributed and the weight of the goods to be distributed at each point to be distributed, a preset path planning algorithm is applied to carry out path planning to obtain the distribution sequence of each point to be distributed, which comprises,
taking the delivery center or the delivery end point of the previous stage as the delivery start point of the current stage, and determining the delivery sequence of each point to be delivered by applying a preset path planning algorithm;
selecting a first point to be distributed as a distribution end point of the current stage;
the determining the delivery sequence of each point to be delivered by applying a preset path planning algorithm comprises the following steps:
s11, selecting a plurality of individuals as a first group according to the carbon emission, wherein the individuals are distribution sequences of the points to be distributed;
s12, based on the first population, sequentially performing crossover operation and mutation operation to obtain a second population;
s13, taking the second group as a new first group, repeatedly executing the step S12 until the iteration condition is met, and selecting an individual with the highest probability as the distribution sequence of each point to be distributed;
acquiring a distribution starting point and a distribution ending point of the current stage;
generating a plurality of delivery routes based on the delivery start point and the delivery end point;
acquiring an actual load value of a delivery vehicle at the current stage, and calculating the carbon emission of the delivery vehicle in each delivery route by applying a preset carbon emission formula based on the delivery distance, the weight of the vehicle body and the actual load value;
comparing the carbon emission of each distribution route, and selecting the distribution route with the minimum carbon emission as a logistics path adopted in the current stage;
wherein, the carbon emission formula is:
wherein T represents the carbon emission amount, S represents the distance between two points, G represents the vehicle body weight, C represents the carbon emission factor, M1 represents the actual load value of the delivery vehicle, and M2 represents the maximum load value of the delivery vehicle.
2. The low carbon logistics route planning method of claim 1, wherein said selecting a number of individuals as a first population based on carbon emissions comprises:
generating a plurality of distribution orders of the points to be distributed by a preset method and coding the generated distribution orders, wherein the distribution order of the points to be distributed is an individual, and each code corresponds to an individual;
and calculating the carbon emission generated by the delivery vehicle when each individual is used as a delivery sequence, and selecting a plurality of individuals with the smallest generated carbon emission as the first group.
3. The method for planning a low-carbon logistics path according to claim 2, wherein the step of sequentially performing crossover operation and mutation operation based on the first population to obtain a second population comprises:
randomly pairing individuals in the first group, and performing cross operation on each pair of individuals by applying a sequence cross operator to obtain a third group;
and carrying out mutation operation on individuals in the third group according to preset probability to obtain the second group.
4. A low carbon logistics path planning apparatus, characterized in that the low carbon logistics path planning apparatus comprises:
the second acquisition module is used for acquiring the distribution center, each point to be distributed and the weight of the goods to be distributed at each point to be distributed;
the path planning module is configured to apply a preset path planning algorithm to perform path planning based on the distribution center, each point to be distributed, and the weight of the goods to be distributed at each point to be distributed, so as to obtain a distribution sequence of each point to be distributed, where the path planning module includes:
the calculating unit is used for determining the delivery sequence of each point to be delivered by applying a preset path planning algorithm by taking the delivery center or the delivery end point of the previous stage as the delivery start point of the current stage;
a selecting unit, configured to select a first point to be delivered as a delivery end point of a current stage; the computing unit is specifically configured to:
s11, selecting a plurality of individuals as a first group according to the carbon emission, wherein the individuals are distribution sequences of the points to be distributed;
s12, based on the first population, sequentially performing crossover operation and mutation operation to obtain a second population;
s13, taking the second group as a new first group, repeatedly executing the step S12 until the iteration condition is met, and selecting an individual with the highest probability as the distribution sequence of each point to be distributed;
the first acquisition module is used for acquiring a distribution starting point and a distribution ending point of the current stage;
the route generation module is used for generating a plurality of delivery routes based on the delivery starting point and the delivery ending point;
the calculation module is used for obtaining an actual load value of the delivery vehicle at the current stage, and calculating the carbon emission of the delivery vehicle in each delivery route by applying a preset carbon emission formula based on the delivery distance, the weight of the vehicle body and the actual load value;
the comparison module is used for comparing the carbon emission of each distribution route and selecting the distribution route with the minimum carbon emission as a logistics path adopted in the current stage;
wherein, the carbon emission formula is:
wherein T represents the carbon emission amount, S represents the distance between two points, G represents the weight of the vehicle body, C represents the carbon emission factor, M 1 Representing the actual load value of the delivery vehicle, M 2 Indicating the maximum load value of the delivery vehicle.
5. An electronic device, the electronic device comprising: a memory and at least one processor, the memory having instructions stored therein;
the at least one processor invoking the instructions in the memory to cause the electronic device to perform the low carbon logistics path planning method of any one of claims 1-3.
6. A computer readable storage medium having instructions stored thereon, which when executed by a processor, implement the low carbon logistics path planning method of any one of claims 1-3.
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