CN116579685B - Finished oil logistics optimization method, system, medium and equipment based on multiparty cooperation - Google Patents
Finished oil logistics optimization method, system, medium and equipment based on multiparty cooperation Download PDFInfo
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Abstract
The invention relates to a multi-party cooperation-based finished oil stream optimization method, a system, a medium and equipment, wherein the method comprises the following steps: establishing a finished oil pipe price data model; establishing a primary logistics optimization model of the finished oil; utilizing the product oil primary logistics optimization model to make a primary logistics plan with the lowest logistics cost as a target, thereby obtaining logistics cost and pipeline utilization rate information generated by a shipper by utilizing each transportation mode; further obtaining the common benefits of both the shipper and the carrier, and judging whether the common benefits are maximized; and finally, determining the common income distribution ratio of the shipper and the carrier. According to the method, under the current pipe delivery pricing mechanism, the pipe delivery price parameters obtained through collaborative optimization can be improved in pipe utilization rate, so that the logistics pattern is optimized, the maximized common benefits are brought to both the supporting party and the supporting party, the purpose of reducing the cost of the finished oil commodity flow of the consignor is finally achieved, and theoretical guidance can be provided for the finished oil consignor.
Description
Technical Field
The invention relates to a multi-party cooperation-based finished oil logistics optimization method and system, and belongs to the field of finished oil logistics.
Background
In recent years, petroleum and petrochemical enterprises take logistics as a third profit source subsequent to resources and manpower, and logistics optimization becomes an important means for improving benefits. In the process of the product oil transportation, petroleum and petrochemical enterprises take on the role of shippers, and the shippers such as pipelines, railways and the like need to be entrusted to complete the oil transportation. Among them, the finished oil pipeline transportation has the advantages of large quantity, continuity and rapidness compared with other modes. However, the finished oil shipper regards itself as an independent logistics node, completes logistics planning only by taking the lowest logistics cost of itself as a target, omits collaborative optimization with both sides of the carrier, and has unreasonable pipe transportation price parameters, so that the logistics cost of the shipper is high, the pipeline utilization rate is low, and the finished oil transportation structure needs to be further optimized.
The existing logistics optimization technology of the finished oil shipper is driven by taking logistics cost as a single target. In the logistics planning process, each carrier needs to provide information such as a path, a unit price, transportation capacity and the like for the shipper, and after the shipper integrates the related information, a logistics optimization technology is utilized to plan a logistics plan which meets the current transportation capacity and supply and demand conditions. The technology divides the product oil stream nodes, and the pipeline transportation advantage is not fully considered. The fixed price parameters limit the logistics cost optimization space of the shipper, and the advantages of large quantity, continuity and rapidness of the pipeline transportation mode cannot be considered. On one hand, on the basis of fixed pipeline price parameters, the logistics cost optimization space is limited; on the other hand, unreasonable pipe price parameters lead to low pipeline utilization. Eventually leading to the shipper logistics cost being high for a long time.
Disclosure of Invention
In view of the above problems, the present invention aims to provide a multi-party cooperation-based product oil logistics optimization method, which considers the cost of a shipper and the optimization space of a pipeline price parameter in the process of preparing a logistics plan, digs the common benefits of the pipeline carrier, integrally optimizes the pipeline price parameter and the logistics plan, further reduces the logistics cost, and improves the pipeline utilization rate at the same time, thereby creating a win-win situation.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
the invention provides a multi-party cooperation-based finished oil logistics optimization method, which comprises the following steps: establishing a finished oil pipe price data model, wherein the finished oil pipe price data model calculates the price of each pipe transportation path by using the mileage of the pipe transportation path and the parameters of the pipe transportation price;
establishing a primary product oil logistics optimization model based on the prices of the transportation paths, the path information of other carriers, the price information of other carriers and the supply and demand information of the shippers;
utilizing the primary product oil logistics optimization model to aim at the lowest logistics cost, and creating a primary logistics plan to obtain logistics cost and pipeline utilization rate information generated by a shipper by utilizing each transportation mode;
based on the logistics cost and the pipeline utilization rate information generated by the shipper by utilizing each transportation mode, the finished oil logistics plan evaluation module obtains the common benefits of the shipper and the carrier by calculating the cost change of the shipper and the income change condition of the pipeline carrier, further judges whether the common benefits are maximized or not, and if not, adjusts the pricing parameters according to the price data model, updates the new pipeline price into the finished oil primary logistics optimization model, and solves the logistics plan again; if yes, entering a common profit distribution module of both parties;
the common profit distribution module of both parties determines the profit distribution ratio of both the shipper and the carrier.
Further, the finished oil pipe price data model is shown in formula (1):
wherein P is m Representing the price of the pipe transportation path m, yuan/ton；C1 w,m Basic price 1, yuan/ton of the regional w pipe transportation path m is represented; C2C 2 w,m The basic price 2 of the regional w pipe transmission path m is represented, and yuan/ton kilometer is represented; l (L) m The mileage of the pipe transmission path m is represented.
Further, R is given as r= {1,2,3 max -represents a set of shipper resource point numbers r; d= {1,2,3 max -represents a set of shipper demand point numbers d; the method is carried out as o= {1,2,3., O (O) max -the collection of the consignor oil product type number o; the method is performed at j= {1,2,3., J (J) max And } represents a collection of transport means j, where f 1 Refers to the consignment fee, f generated by logistics plan 2 Penalty fee, f, generated by oil retention at resource point 3 The punishment fee generated by the lack of oil products at the demand points is indicated, the primary logistics optimization model of the finished oil aims at the lowest logistics cost, and the model is specifically shown in the formulas (2) to (5):
min f＝f 1 +f 2 +f 3 (2)
in the method, in the process of the invention,representing unit cost, yuan/ton of oil product o transported from resource point r to demand point d through mode j;representing the quantity of oil products o transported from a resource point r to a demand point d in a mode j, and carrying out ton; />Unit for indicating retention/absence of oil o at resource point r/demand point dPunishment fees, yuan/ton; />Representing the amount of oil o retention/shortage at resource point r/demand point d, and ton;
further, the constraint condition of the primary product oil logistics optimization model includes a shipper resource point related constraint, and the shipper resource point related constraint includes:
the resource points have oil supply quantity ranges, and the planned supply quantity of the primary logistics optimization model of the finished oil meets the upper and lower limit requirements;
and considering the transport capacity of each carrier, the resource amount of the resource point is not necessarily completely supplied to the demand point, and the hold-up amount is equal to the difference between the planned supply amount and the actual supply amount;
the planned supply amount of the primary logistics optimization model of the finished oil meets the upper and lower limit requirements, and the planned supply amount is specifically shown as formulas (6) and (7):
in the method, in the process of the invention,representing the planned supply quantity of oil products o of resource points r and tons; />Representing the lower limit/upper limit of the supply quantity of oil products o of resource points r and tons;
the difference between the planned supply amount and the actual supply amount is specifically represented by formula (8):
further, the constraint condition of the primary product oil logistics optimization model further includes a shipper demand point related constraint, and the shipper demand point related constraint includes:
the oil product demand range exists at the demand point, and the planned receiving amount of the primary logistics optimization model of the finished oil product meets the upper limit and the lower limit;
the demand of the demand point is not necessarily fully satisfied, so that a shortage is introduced, which is equal to the difference between the planned received amount and the actual received amount;
the planned receiving amount of the primary logistics optimization model of the finished oil meets the upper and lower limit requirements, and the method is specifically shown in formulas (9) - (10):
in the method, in the process of the invention,representing the planned receiving quantity of the oil product o at the demand point d and ton; />The lower limit/upper limit of the demand of the oil product o at the demand point d is represented, and ton is represented;
the shortage amount satisfies that the shortage amount is equal to the difference between the planned received amount and the actual received amount, specifically as shown in formula (11):
further, the constraint condition of the product oil primary logistics optimization model further comprises a carrier path related constraint, wherein the carrier path related constraint comprises:
ensuring a minimum shipping volume specified by the benefit, as shown in formula (12); or the maximum shipping capacity due to vehicle speed, capacity, as shown in equation (13),
in the method, in the process of the invention,representing the lower limit/upper limit of the consignment amount of the oil product o transported from the resource point r to the demand point d in a mode j, and carrying out ton;
the carrier's transport needs to satisfy relationship (14) between the shipping volume of the transportation path and the unit shipping volume and integer variables:
in the method, in the process of the invention,representing the specified unit carrying capacity of oil products o from a resource point r to a demand point d in a mode j, and carrying out ton/batch; />Is an integer variable representing the number of unit shipments of oil o transported from resource point r to demand point d by means of j.
The invention also provides a finished oil logistics optimization system based on multiparty cooperation, which comprises the following steps:
the finished oil pipe price data module comprises a finished oil pipe price data model, wherein the finished oil pipe price data model is used for calculating the price of each pipe transportation path by using the mileage of the pipe transportation path and the parameters of the pipe transportation price;
the product oil primary logistics optimization module comprises a product oil primary logistics optimization model, wherein the product oil primary logistics optimization model is used for compiling a primary logistics plan to obtain logistics cost and pipeline utilization rate information generated by a shipper by utilizing each transportation mode based on the prices of each transportation path and other carrier path information, other carrier price information and shipper supply and demand information with the lowest logistics cost as targets;
the finished oil logistics plan evaluation module is used for obtaining common benefits of both shippers and carriers by calculating the cost change of the shippers and the income change condition of the pipeline carriers based on logistics cost and pipeline utilization rate information generated by the shippers by utilizing each transportation mode, further judging whether the common benefits are maximized or not, if not, adjusting pricing parameters according to a price data model, updating new pipeline prices into a finished oil primary logistics optimization model, and re-solving the logistics plan; if yes, entering a common profit distribution module of both parties;
and the two parties share a profit distribution module for determining the profit distribution ratio of the shipper and the carrier.
The invention also provides a computer readable storage medium storing computer instructions for implementing the multiparty collaboration-based product oil stream optimization method when executed by a processor.
The invention also provides a computer device comprising a memory, a processor and a computer program stored on the memory and running on the processor, characterized in that the processor implements the multi-party cooperation-based product oil stream optimization method when executing the computer program.
Due to the adoption of the technical scheme, the invention has the following advantages:
the invention solves the problem of high logistics cost caused by taking the shipper as a logistics partition node when carrying out primary logistics optimization of the finished oil, and provides a method for collaborative optimization of a finished oil logistics support and a carrier by considering the utilization rate of a pipeline. By applying the method and the system, under the current pipe delivery pricing mechanism, the pipe delivery price parameters obtained through collaborative optimization can be improved in pipe utilization rate, so that the logistics pattern is optimized, the maximized common benefits are brought to both the supporting party and the supporting party, the purpose of reducing the cost of the finished oil commodity flow of the consignor is finally achieved, and theoretical guidance can be provided for the finished oil consignor.
Drawings
Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Like parts are designated with like reference numerals throughout the drawings.
In the drawings:
FIG. 1 is a flow chart of a multi-party collaboration-based process for optimizing a product oil stream provided by the present invention;
FIG. 2 is a shipper resource oil supply plan;
FIG. 3 is a demand plan view of a shipper's resource oil portion demand points.
Detailed Description
Exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present invention are shown in the drawings, it should be understood that the present invention may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.
The invention provides a multi-party cooperation-based finished oil logistics optimization method, which is characterized in that in the logistics plan making process, besides the cost of a consignor, the optimization space of a pipeline price parameter is considered, the common income of a pipeline carrier is excavated, the pipeline price parameter and the logistics plan are optimized in a comprehensive way, the logistics cost is further reduced, the pipeline utilization rate is improved, and the win-win situation is created.
As shown in fig. 1, the method for optimizing a product oil stream based on multiparty cooperation provided by the embodiment of the invention comprises the following steps:
s1, establishing a finished oil pipe price data model, wherein the finished oil pipe price data model is a parameter preprocessing layer of the technology, and has the function of calculating the price of each pipe transportation path by using the mileage of the pipe transportation path and the parameters of the pipe transportation price;
the finished oil pipe price data model is shown as (1):
wherein P is m Representing the price of the pipe conveying path m, yuan/ton; C1C 1 w,m Basic price 1, yuan/ton of the regional w pipe transportation path m is represented; C2C 2 w,m The basic price 2 of the regional w pipe transmission path m is represented, and yuan/ton kilometer is represented; l (L) m The mileage of the pipe transmission path m is represented.
S2, establishing a primary logistics optimization model of the finished oil;
the once logistics optimization model of the finished oil is a core calculation layer of the system, and the function of the once logistics optimization model is to realize the logistics planning function based on input information. The model is a technical key of the whole method and is introduced as follows.
The product oil primary logistics optimization model comprehensively considers carrier path information, carrier price information and shipper supply and demand information. The carrier route and price information includes, among other things, pipeline carriers and other carriers such as railways, waterways, highways, etc.
In the model, R is given as r= {1,2,3 max -represents a set of shipper resource point numbers r; d= {1,2,3 max -represents a set of shipper demand point numbers d; the method is carried out as o= {1,2,3., O (O) max -the collection of the consignor oil product type number o; the method is performed at j= {1,2,3., J (J) max And } represents a collection of transport means j. The optimization objective of the model is to minimize shipper logistics costs as shown in formulas (2) - (5), wherein f 1 Refers to the consignment fee, f generated by logistics plan 2 Penalty fee, f, generated by oil retention at resource point 3 Refers to punishment fees generated by the lack of oil products at the demand points.
min f＝f 1 +f 2 +f 3 (2)
In the method, in the process of the invention,representing unit cost, yuan/ton of oil product o transported from resource point r to demand point d through mode j;representing the quantity of oil products o transported from a resource point r to a demand point d in a mode j, and carrying out ton; />Unit penalty cost, yuan/ton, for oil o retention/backdrop at resource point r/demand point d; />And represents the amount of oil o retention/stock shortage at the resource point r/demand point d, and ton.
Constraint conditions to be considered by the logistic optimization model are as follows.
(1) Shipper resource point related constraints
For resource points, the oil supply range exists, and the planned supply of the model meets the upper and lower limit requirements as shown in formulas (6) - (7).
In the method, in the process of the invention,representing the planned supply quantity of oil products o of resource points r and tons; />The lower limit/upper limit of the supply amount of oil o at the resource point r is expressed as ton.
Considering the transport capacity of each carrier, the amount of resources at the resource point is not necessarily completely supplied to the demand point, and thus a hold-up is introduced as shown in equation (8). The hold-up is equal to the difference between the planned supply amount and the actual supply amount.
(2) Shipper demand point related constraints
For the demand points, there is a range of oil demand, and the planned receiving amount of the model should meet the upper and lower limit requirements, as shown in formulas (9) - (10).
In the method, in the process of the invention,representing the planned receiving quantity of the oil product o at the demand point d and ton; />The lower/upper demand limit of the oil o at the demand point d is expressed as ton.
Similarly, the demand at the demand point is not necessarily fully satisfied, and thus the amount of the shortage is introduced as shown in the formula (11). The amount of the missing goods is equal to the difference between the planned received amount and the actual received amount.
(3) Carrier path related constraints
For carriers, the carrier paths provided have certain transportation capacity limitations, such as minimum shipping volume specified for revenue assurance (see equation (12)) or maximum shipping volume due to vehicle speed, capacity (see equation (13)).
In the method, in the process of the invention,the lower limit/upper limit of the delivery amount of the oil product o transported from the resource point r to the demand point d in the mode j is represented, and ton is represented.
In addition, carriers specify unit shipments (or batches) to ensure full transport. If the volume of the tank truck is 50, the delivery capacity of the path needs to be a multiple of 50. The expression is as follows:
in the method, in the process of the invention,representing the specified unit carrying capacity of oil products o from a resource point r to a demand point d in a mode j, and carrying out ton/batch; />Is an integer variable representing the number of unit shipments of oil o transported from resource point r to demand point d by means of j.
S3, based on logistics cost and pipeline utilization rate information generated by the shipper by utilizing each transportation mode, the finished oil logistics plan evaluation module obtains common benefits of the shipper and the carrier through calculating the cost change of the shipper and the income change condition of the pipeline carrier, further judges whether the common benefits are maximized, and if not, adjusts pricing parameters according to a price data model, updates new pipeline prices into a finished oil primary logistics optimization model, and solves the logistics plan again; if yes, entering a common profit distribution module of both parties;
s4, the common benefits of the shipper and the carrier are the combined value of the cost reduction of the shipper and the income increase of the pipeline carrier. When the solved logistics plan can maximize the common benefits of the finished oil shippers and the pipeline shippers, on one hand, the cost-saving amplitude of the shippers and the indirect benefits brought by adopting a pipeline transportation mode (such as avoiding market risks) need to be considered; on the other hand, the carrying cost and the increasing income of the pipeline party caused by the improvement of the utilization rate of the pipeline are required to be considered. Based on the above, the profit distribution ratio of the supporting party and the supporting party is determined. Therefore, the common income distribution module can improve the pipeline utilization rate while reducing the logistics cost of shippers, thereby promoting the income increase of the pipeline shippers and creating a win-win situation.
The specific application is as follows:
and taking a certain finished oil shipper as a research object, dividing the service range of the shipper into 4 areas (A-D), and carrying out integral finished oil logistics collaborative optimization.
The shipper resource supply and demand plan is shown in fig. 2 and 3, and totally involves 28 resource points and 271 demand points (80 demand points are taken as an example in fig. 3), three major types of oil products (diesel, gasoline and kerosene), and four transportation modes (pipelines, railways, waterways and highways). Wherein, the total diesel oil supply is 435.82 ten thousand tons, the total gasoline supply is 509.55 ten thousand tons, and the total kerosene supply is 13.52 ten thousand tons, corresponding to the total demand.
The pricing parameters of the basic scheme are shown in Table 1, and all four service areas adopt a basic price of 1 to 0 yuan/ton and a basic price of 2 to 0.196 yuan/ton.km. After the solution of the primary logistics optimization model of the finished oil is adopted, the overall logistics cost of the consignor is 8.1 hundred million yuan, the overall income of the pipeline is 4.0 hundred million yuan, and the total pipeline conveying capacity and the total turnover capacity are 467 ten thousand tons and 205 ten million tons and kilometers respectively.
Table 1 current pricing parameters for pipeline carriers
By utilizing the multi-party cooperation-based finished oil logistics optimization method and system provided by the invention, the optimized pipe transportation price parameters are shown in table 2 according to the cooperative optimization flow shown in fig. 1. The basic price 1 of the four service areas is still the same and is 30 yuan/ton, but the basic price 2 is determined according to the characteristics of each service area and is different between 0.082 and 0.152 yuan/ton and metric lining. On this basis, as shown in table 3, the results indicate that: the logistics cost of the shipper is reduced by 516 ten thousand yuan, the income of the pipe party is increased by 886 ten thousand yuan, and the total maximum income is 1402 ten thousand yuan. From the aspect of pipeline conveying capacity and turnover, the conveying capacity is increased by 11 ten thousand tons, the turnover is increased by 2.36 percent, the turnover is increased by 8 ten million tons per kilometer, and the turnover is increased by 3.90 percent.
TABLE 2 collaborative optimization of pricing parameters for pipe inputs
TABLE 3 comparison of results before and after synergistic optimization
The common income of the supporting party and the supporting party reaches 1402 ten thousand yuan, and the common income distribution mechanism of the invention is based on consideration of the cost-saving amplitude of the consignor; secondly, the problem of transportation cost added to the pipeline side is solved by considering the improvement of the turnover quantity of the pipeline; thirdly, the problem of income change after the price parameters are adjusted by the pipeline carrier is considered; fourthly, the problem of indirect benefit brought by risk avoidance of shippers is considered to be the advantage of pipeline transportation. Thus, the revenue for the pipeline carrier should be properly increased, and the proposed distribution ratio of the present invention is 3:7 (shipper: pipe side). In this example, the invention saves 421 ten thousand yuan of logistics cost for the finished oil consignor, increases the output and the turnover of the lifting pipe by 3.9 percent, increases the income of the pipeline by 981 ten thousand yuan, and creates a win-win situation for both the consignor and the carrier.
Compared with the prior art, the invention solves the problem that the logistics cost is high caused by taking the shipper as a logistics segmentation node when the shipper optimizes the primary logistics of the finished oil, and provides a method for collaborative optimization of the finished oil logistics support and the carrier by considering the utilization rate of pipelines. By applying the method and the system, under the current pipe delivery pricing mechanism, the pipe delivery price parameters obtained through collaborative optimization can be improved in pipe utilization rate, so that the logistics pattern is optimized, the maximized common benefits are brought to both the supporting party and the supporting party, the purpose of reducing the cost of the finished oil commodity flow of the consignor is finally achieved, and theoretical guidance can be provided for the finished oil consignor.
The embodiment of the invention also provides a finished oil stream optimization system based on multiparty cooperation, which comprises the following steps:
the finished oil pipe price data module comprises a finished oil pipe price data model, wherein the finished oil pipe price data model is used for calculating the price of each pipe transportation path by using the mileage of the pipe transportation path and the parameters of the pipe transportation price;
the product oil primary logistics optimization module comprises a product oil primary logistics optimization model, wherein the product oil primary logistics optimization model is used for compiling a primary logistics plan to obtain logistics cost and pipeline utilization rate information generated by a shipper by utilizing each transportation mode based on the prices of each transportation path and other carrier path information, other carrier price information and shipper supply and demand information with the lowest logistics cost as targets;
the finished oil logistics plan evaluation module is used for obtaining common benefits of both shippers and carriers by calculating the cost change of the shippers and the income change condition of the pipeline carriers based on logistics cost and pipeline utilization rate information generated by the shippers by utilizing each transportation mode, further judging whether the common benefits are maximized or not, if not, adjusting pricing parameters according to a price data model, updating new pipeline prices into a finished oil primary logistics optimization model, and re-solving the logistics plan; if yes, entering a common profit distribution module of both parties;
and the two parties share a profit distribution module for determining the profit distribution ratio of the shipper and the carrier.
The embodiment of the invention also provides a computer readable storage medium, which stores computer instructions for realizing the multi-party cooperation-based product oil stream optimization method when being executed by a processor.
The embodiment of the invention also provides computer equipment, which comprises a memory, a processor and a computer program stored on the memory and running on the processor, and is characterized in that the processor realizes the multi-party cooperation-based finished oil stream optimization method when executing the computer program.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; 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 (8)
1. A multi-party cooperation-based finished oil stream optimization method is characterized by comprising the following steps:
establishing a finished oil pipe price data model, wherein the finished oil pipe price data model calculates the price of each pipe transportation path by using the mileage of the pipe transportation path and the parameters of the pipe transportation price;
establishing a primary product oil logistics optimization model based on the prices of the transportation paths, the path information of other carriers, the price information of other carriers and the supply and demand information of the shippers;
utilizing the primary product oil logistics optimization model to aim at the lowest logistics cost, and creating a primary logistics plan to obtain logistics cost and pipeline utilization rate information generated by a shipper by utilizing each transportation mode;
based on the logistics cost and the pipeline utilization rate information generated by the shipper by utilizing each transportation mode, the finished oil logistics plan evaluation module obtains the common benefits of the shipper and the carrier by calculating the cost change of the shipper and the income change condition of the pipeline carrier, further judges whether the common benefits are maximized or not, and if not, adjusts the pricing parameters according to the price data model, updates the new pipeline price into the finished oil primary logistics optimization model, and solves the logistics plan again; if yes, entering a common profit distribution module of both parties;
the common profit distribution module of the two parties determines the profit distribution ratio of the shipper and the carrier;
the primary product oil logistics optimization model aims at the lowest logistics cost and is formed by R= {1,2,3 … and R max -represents a set of shipper resource point numbers r; in d= {1,2,3 …, D max -represents a set of shipper demand point numbers d; in the form of O= {1,2,3 …, O max -the collection of the consignor oil product type number o; in j= {1,2,3 …, J max And } represents a collection of transport means j, where f 1 Refers to the consignment fee, f generated by logistics plan 2 Penalty fee, f, generated by oil retention at resource point 3 The punishment fee generated by the lack of oil products at the demand point is shown in the following formulas (2) to (5):
minf＝f 1 +f 2 +f 3 (2)
in the method, in the process of the invention,representing unit cost, yuan/ton of oil product o transported from resource point r to demand point d through mode j; />Representing the quantity of oil products o transported from a resource point r to a demand point d in a mode j, and carrying out ton; />The unit punishment fee of the oil o retention of the resource point r is expressed, and the unit punishment fee is yuan/ton; />Unit punishment fee of the oil o shortage at the demand point d is expressed, and yuan/ton; />Representing the retention amount of oil o at a resource point r and ton; />Indicating the amount of oil o out of stock at the point of demand d, ton.
2. The multi-party cooperation-based finished oil stream optimization method according to claim 1, wherein the finished oil pipeline price data model is shown in formula (1):
wherein P is m Representing the price of the pipe conveying path m, yuan/ton; C1C 1 w,m Basic price 1, yuan/ton of the regional w pipe transportation path m is represented; C2C 2 w,m The basic price 2 of the regional w pipe transmission path m is represented, and yuan/ton kilometer is represented; l (L) m The mileage of the pipe transmission path m is represented.
3. The multi-party collaboration-based finished product oil stream optimization method as claimed in claim 1, wherein the constraint condition of the finished product oil primary stream optimization model comprises a shipper resource point related constraint comprising:
the resource points have oil supply quantity ranges, and the planned supply quantity of the primary logistics optimization model of the finished oil meets the upper and lower limit requirements;
and considering the transport capacity of each carrier, the resource amount of the resource point is not necessarily completely supplied to the demand point, and the hold-up amount is equal to the difference between the planned supply amount and the actual supply amount;
the planned supply amount of the primary logistics optimization model of the finished oil meets the upper and lower limit requirements, and the planned supply amount is specifically shown as formulas (6) and (7):
in the method, in the process of the invention,representing the planned supply quantity of oil products o of resource points r and tons; />Representing the lower limit/upper limit of the supply quantity of oil products o of resource points r and tons;
the difference between the planned supply amount and the actual supply amount is specifically represented by formula (8):
4. the multi-party collaboration-based finished product oil stream optimization method as claimed in claim 1, wherein the constraints of the finished product oil primary stream optimization model further comprise shipper demand point related constraints, the shipper demand point related constraints comprising:
the oil product demand range exists at the demand point, and the planned receiving amount of the primary logistics optimization model of the finished oil product meets the upper limit and the lower limit;
the demand of the demand point is not necessarily fully satisfied, so that a shortage is introduced, which is equal to the difference between the planned received amount and the actual received amount;
the planned receiving amount of the primary logistics optimization model of the finished oil meets the upper and lower limit requirements, and the method is specifically shown in formulas (9) - (10):
in the method, in the process of the invention,representing the planned receiving quantity of the oil product o at the demand point d and ton; />The lower limit/upper limit of the demand of the oil product o at the demand point d is represented, and ton is represented;
the shortage amount satisfies that the shortage amount is equal to the difference between the planned received amount and the actual received amount, specifically as shown in formula (11):
5. the multi-party collaboration-based finished product stream optimization method as claimed in claim 1, wherein the constraints of the finished product primary stream optimization model further comprise carrier path-related constraints comprising:
ensuring a minimum shipping volume specified by the benefit, as shown in formula (12); or the maximum shipping capacity due to vehicle speed, capacity, as shown in equation (13):
in the method, in the process of the invention,representing the lower limit/upper limit of the consignment amount of the oil product o transported from the resource point r to the demand point d in a mode j, and carrying out ton;
the carrier's conveyance is required to satisfy the relationship (14) between the shipping volume of the transportation path and the unit shipping volume and integer variable,
in the method, in the process of the invention,representing the specified unit carrying capacity of oil products o from a resource point r to a demand point d in a mode j, and carrying out ton/batch;is an integer variable representing the number of unit shipments of oil o transported from resource point r to demand point d by means of j.
6. A multi-party collaboration-based product oil stream optimization system, comprising:
the finished oil pipe price data module comprises a finished oil pipe price data model, wherein the finished oil pipe price data model is used for calculating the price of each pipe transportation path by using the mileage of the pipe transportation path and the parameters of the pipe transportation price;
the product oil primary logistics optimization module comprises a product oil primary logistics optimization model, wherein the product oil primary logistics optimization model is used for compiling a primary logistics plan to obtain logistics cost and pipeline utilization rate information generated by a shipper by utilizing each transportation mode based on the prices of each transportation path and other carrier path information, other carrier price information and shipper supply and demand information with the lowest logistics cost as targets;
the finished oil logistics plan evaluation module is used for obtaining common benefits of both shippers and carriers by calculating the cost change of the shippers and the income change condition of the pipeline carriers based on logistics cost and pipeline utilization rate information generated by the shippers by utilizing each transportation mode, further judging whether the common benefits are maximized or not, if not, adjusting pricing parameters according to a price data model, updating new pipeline prices into a finished oil primary logistics optimization model, and re-solving the logistics plan; if yes, entering a common profit distribution module of both parties;
the two parties share a profit distribution module for determining the profit distribution ratio of the shipper and the carrier;
the primary product oil logistics optimization model aims at the lowest logistics cost and is formed by R= {1,2,3 … and R max -represents a set of shipper resource point numbers r; in d= {1,2,3 …, D max -represents a set of shipper demand point numbers d; in the form of O= {1,2,3 …, O max -the collection of the consignor oil product type number o; in j= {1,2,3 …, J max And } represents a collection of transport means j, where f 1 Refers to the consignment fee, f generated by logistics plan 2 Penalty fee, f, generated by oil retention at resource point 3 The punishment fee generated by the lack of oil products at the demand point is shown in the following formulas (2) to (5):
minf＝f 1 +f 2 +f 3 (2)
in the method, in the process of the invention,representing unit cost, yuan/ton of oil product o transported from resource point r to demand point d through mode j; />Representing the quantity of oil products o transported from a resource point r to a demand point d in a mode j, and carrying out ton; />The unit punishment fee of the oil o retention of the resource point r is expressed, and the unit punishment fee is yuan/ton; />Unit punishment fee of the oil o shortage at the demand point d is expressed, and yuan/ton; />Representing the retention amount of oil o at a resource point r and ton; />Indicating the amount of oil o out of stock at the point of demand d, ton.
7. A computer readable storage medium, characterized in that computer instructions are stored for implementing the multiparty collaboration based product oil stream optimization method according to any one of claims 1-5 when executed by a processor.
8. A computer device comprising a memory, a processor and a computer program stored on the memory and running on the processor, wherein the processor implements the multiparty collaboration-based product oil stream optimization method according to any one of claims 1-5 when executing the computer program.
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