Product oil replenishment method based on three-layer logistics network

Abstract

The invention relates to the technical field of logistics transportation, and discloses a product oil replenishment method based on a three-layer logistics network, and the replenishment method comprises the steps: carrying out the primary dispatching from a refinery plant to an oil depot, and carrying out the secondary distribution from the oil depot to a gas station; determining a fixed oil depot subset and a candidate oil depot subset in the oil depot node set; constructing a primary dispatching model and a secondary distribution model according to the fixed oil depot subset and the candidate oil depot subset; in the primary dispatching model and the secondary distribution model, decision variables are introduced for the candidate oil depot subsets to express the loading and unloading conditions of the candidate oil depots; establishing an objective function according to the primary dispatching model and the secondary distribution model, calculating an optimal solution under a preset constraint condition, and confirming a replenishment object and a replenishment amount of each node; according to the method, the replenishment strategy is formulated in consideration of primary dispatching and secondary distribution, global optimization can be realized, the oil depot layout is changed through decision introduction of the candidate oil depots, and then the operation efficiency can be improved by optimizing the oil depot layout.

Description

Technical Field

[0001] The present invention relates to the field of logistics and transportation technology, and more specifically to a method for replenishing refined oil products based on a three-layer logistics network. Background Art

[0002] The logistics activities of the finished oil supply chain include the movement of finished oil from refineries to oil depots and the movement of finished oil from oil depots to gas stations. The resulting distribution activities are called primary distribution and secondary distribution respectively.

[0003] The replenishment of refined oil includes the replenishment of oil depots and gas stations. The replenishment of refined oil means that the enterprise determines the replenishment quantity for oil depots and gas stations according to the needs of each gas station and completes the corresponding distribution activities. In the past, the replenishment of refined oil was that the gas station submitted the replenishment demand to the dispatching command center of the refined oil sales company according to the demand, and the company distributed from the oil depot according to the type and quantity of oil ordered by the gas station, that is, the replenishment model implemented the order system; now, the replenishment of refined oil is that the gas station shares sales data and other relevant information with the dispatching command center of the refined oil sales company, and the company actively formulates the replenishment plan of refined oil and completes the distribution, that is, the replenishment model implements the replenishment system.

[0004] Existing replenishment strategies often only consider single-time delivery issues and fail to achieve global optimization, making it difficult to effectively improve network operating efficiency and reduce operating costs.

[0005] Therefore, how to achieve global optimization of the supply network and improve operational efficiency is an urgent problem that technical personnel in this field need to solve. Summary of the invention

[0006] In view of this, the present invention provides a method for replenishing finished oil products based on a three-layer logistics network, which takes into account primary transportation and secondary distribution to formulate a replenishment strategy, can achieve global optimization, and on the basis of global optimization, change the layout of oil depots by introducing decisions on candidate oil depots, and then improve the operating efficiency by optimizing the layout of oil depots.

[0007] In order to achieve the above object, the present invention adopts the following technical solution:

[0008] A method for replenishing finished oil based on a three-layer logistics network, the three-layer logistics network comprising: refinery-oil depot-gas station; the steps of the replenishment method comprising: primary distribution from the refinery to the oil depot and secondary distribution from the oil depot to the gas station;

[0009] Confirming a fixed oil depot subset and a candidate oil depot subset in the oil depot node set;

[0010] A primary transportation model and a secondary distribution model are constructed according to the fixed oil depot subset and the candidate oil depot subset; in the primary transportation model and the secondary distribution model, decision variables are introduced for the candidate oil depot subset to express the loading and unloading conditions of the candidate oil depots;

[0011] An objective function is established based on the primary distribution model and the secondary distribution model, an optimal solution is calculated under preset constraints, and the distribution target of each node and the corresponding replenishment quantity under the optimal oil depot layout are confirmed.

[0012] Preferably, a primary dispatch model and a secondary dispatch model are constructed according to the fixed oil depot subset and the candidate oil depot subset, specifically:

[0013] The objective function and decision variables of the one-time dispatch model are expressed as:

[0014]

[0015]

[0016]

[0017]

[0018]

[0019]

[0020]

[0021]

[0022]

[0023] The objective function and decision variables of the secondary distribution model are expressed as:

[0024]

[0025]

[0026]

[0027]

[0028]

[0029]

[0030]

[0031] Among them, m is the transportation mode from refinery to oil depot, which is divided into pipeline transportation, railway transportation and water transportation, M is the set of transportation modes from refinery to oil depot; o is the refinery node, O is the refinery set; i is the oil depot node, I is the oil depot set; n is the oil product type, N is the oil product set; is a 0-1 variable, indicating the use of transport mode m from refinery o to oil depot i; For oil The unit distance and unit volume transportation cost from refinery o to oil depot i; is the distance from refinery o to oil depot i, represents the transportation volume of oil product n from refinery o to oil depot i; is the average operating cost of oil depot i in one cycle, is the decision variable of the oil depot; is the fixed cost of shipment to refinery o, is a 0-1 variable representing the transportation of oil product n from refinery o to oil depot i, For oil depot Fixed costs of receiving goods; is the unit distance and unit volume transportation cost of oil product n from oil depot i to gas station j; is the distance from oil depot i to gas station j; is the distribution volume of oil product n from oil depot i to gas station j; The fixed cost of shipping to tank depot i, is a 0-1 variable representing the distribution of oil product n from oil depot i to gas station j, is the fixed cost of receiving goods for gas station j; The maximum transport volume from refinery to oil depot using transport mode m; The maximum transportation radius from refinery to oil depot using transportation mode m; Maximum delivery volume from oil depot to gas station using road transport; The maximum delivery radius from the oil depot to the gas station using road transport; is the candidate oil depot subset, It is a fixed oil depot subset; is a symbolic function whose specific meaning depends on the input variable. That is, when the transfer volume of oil product n from refinery o to oil depot i is 0, the sign function returns 0, indicating that there is no transfer of oil product n from refinery o to oil depot i; if the transfer volume is not 0, the sign function returns 1, indicating that there is a transfer of oil product n from refinery o to oil depot i. That is, when the distribution volume of oil product n from oil depot i to gas station j is 0, the sign function returns 0, indicating that no distribution of oil product n occurs from oil depot i to gas station j; if the distribution volume is not 0, the sign function returns 1, indicating that distribution of oil product n occurs from oil depot i to gas station j.

[0032] Specifically, the meanings of the objective functions of the one-time dispatch model are as follows: It represents the transportation cost of oil products from refinery to oil depot; represents the total operating cost of the oil depot; It represents the fixed shipping cost of the refinery, which is only related to whether the shipment is made and has nothing to do with the specific transportation volume; It represents the fixed receiving cost of the oil depot, which is only related to whether the goods are received, and has nothing to do with the specific transportation volume. The four costs together constitute the total cost of a transfer from the refinery to the oil depot. It means that the total amount of all oil products transferred from refinery o to oil depot i does not exceed the maximum transfer amount of the transportation method used; It means that the transportation distance of oil product n from refinery o to oil depot i does not exceed the maximum transportation radius of the transportation method used.

[0033] The meanings of the objective functions of the secondary distribution model are as follows: It represents the distribution cost of oil products from oil depots to gas stations; represents the total operating cost of the oil depot; It represents the fixed delivery cost of the oil depot, which is only related to whether the oil depot delivers the goods, and has nothing to do with the specific transportation volume; It represents the fixed receiving cost of the gas station, which is only related to whether the goods are received, and has nothing to do with the specific transportation volume. The four costs together constitute the total cost of secondary distribution from the oil depot to the gas station. It means that the total amount of oil delivered from oil depot i to gas station j does not exceed the maximum delivery amount of road transportation; It means that the transportation distance of oil product n from oil depot i to gas station j does not exceed the maximum distribution radius of road transportation.

[0034] Preferably, an objective function is established based on the primary transportation model and the secondary distribution model, specifically: cost parameters are respectively input into the primary transportation model and the secondary distribution model, the primary transportation cost and the secondary distribution cost are calculated, and a cost objective function is established.

[0035] Preferably, the cost parameters include one or more of the unit transportation cost of each route, refinery delivery cost, oil depot operating cost, oil depot delivery cost, oil depot receiving cost, and gas station receiving cost.

[0036] Preferably, the cost objective function is:

[0037]

[0038]

[0039]

[0041]

[0042]

[0043] in, is a 0-1 variable, indicating the use of transportation mode m from refinery o to oil depot i. is the unit distance and unit volume transportation cost of oil product n from refinery o to oil depot i, is the distance from refinery o to oil depot i, represents the transportation volume of oil product n from refinery o to oil depot i; is the unit distance and unit volume transportation cost of oil product n from oil depot i to gas station j, is the distance from oil depot i to gas station j, is the distribution volume of oil product n from oil depot i to gas station j; is the oil depot decision variable, The operating cost of oil depot i put into use is amortized within one cycle; is the fixed cost of shipment to refinery o, is a 0-1 variable representing the transportation of oil product n from refinery o to oil depot i, The fixed cost of shipping to tank depot i, is a 0-1 variable representing the distribution of oil product n from oil depot i to gas station j, is the fixed cost of receiving goods at depot i, is the fixed cost of receiving goods at gas station j. is a symbolic function whose specific meaning depends on the input variable. That is, when the transfer volume of oil product n from refinery o to oil depot i is 0, the sign function returns 0, indicating that there is no transfer of oil product n from refinery o to oil depot i; if the transfer volume is not 0, the sign function returns 1, indicating that there is a transfer of oil product n from refinery o to oil depot i. That is, when the distribution volume of oil product n from oil depot i to gas station j is 0, the sign function returns 0, indicating that oil product n is not distributed from oil depot i to gas station j; when the transportation volume is not 0, the sign function returns 1, indicating that oil product n is distributed from oil depot i to gas station j. The terms of the objective function correspond to the transportation cost of oil products from the refinery to the oil depot, the distribution cost of oil products from the oil depot to the gas station, the total operating cost of the oil depot, the fixed shipping cost of the refinery, the fixed shipping cost of the gas station, the fixed receiving cost of the oil depot, and the fixed receiving cost of the gas station.

[0044] Preferably, the objective function also includes a utilization objective function:

[0045]

[0046] in, is the important parameter of the oil depot’s oil delivery capacity utilization rate, is the maximum oil delivery amount of oil product n in oil depot i, is the maximum loading and unloading capacity of oil product n in oil depot i.

[0047] Preferably, the constraints include: flow balance constraints, loading and unloading volume and oil delivery volume constraints, carrying volume constraints, delivery radius constraints and decision variable value constraints;

[0048] The flow balance constraints include:

[0049]

[0050]

[0051]

[0052] in, is the beginning inventory of oil product n in gas station j, is the demand for oil product n at gas station j; is the beginning inventory of oil product n in oil depot i;

[0053] The loading and unloading volume and fuel delivery volume constraints include:

[0054]

[0055]

[0056] in, is the minimum unloading amount of oil product n in oil depot i, is the maximum unloading capacity of oil product n in oil depot i; is the minimum oil delivery quantity of oil product n in oil depot i, is the maximum oil delivery quantity of oil product n in oil depot i;

[0057] The carrying capacity constraints include:

[0058]

[0059]

[0060] in, is the maximum transport volume from refinery to oil depot using transport mode m, Maximum delivery volume from oil depot to gas station using road transport;

[0061] The delivery radius constraints include:

[0062]

[0063]

[0064] in, is the maximum transportation radius from refinery to oil depot using transportation mode m, The maximum delivery radius from the oil depot to the gas station using road transport;

[0065] The decision variable value constraints include:

[0066]

[0067]

[0068]

[0069]

[0070] in, represents the transportation volume of oil product n from refinery o to oil depot i, is the decision variable of the oil depot; is the distribution volume of oil product n from oil depot i to gas station j; is the candidate oil depot subset, It is a fixed oil depot subset.

[0071] Preferably, service mode constraints are also included, and the service mode constraints include:

[0072]

[0073]

[0074] The service mode constraint indicates that the oil depot that is not in use does not need to be replenished and does not participate in the replenishment service for the gas station.

[0075] Preferably, a genetic algorithm is used to calculate the optimal solution, and the steps include:

[0076] Initialize the oil depot site selection plan and the distribution volume allocation plan that meets the oil depot site selection plan, and obtain multiple populations and corresponding individuals in each population as initialization results; in the initialization results, each gene position corresponding to the fixed oil depot is a fixed parameter value, and the gene position corresponding to the candidate oil depot is a random value;

[0077] Perform crossover mutation based on the initialization results and update the population individuals;

[0078] Calculate the fitness of each individual, and select multiple individuals with the largest fitness to be retained and enter the next generation; where the individual fitness is the objective function value or the weighted sum of multiple objective function values;

[0079] Repeat S2 and S3 until the iteration is completed, and output the best individuals in each population for comparison to obtain the best individual in the best population, that is, the best replenishment plan under the optimal oil depot layout.

[0080] A refined oil replenishment system based on a three-layer logistics network includes a computer system, wherein the computer system is used to execute the refined oil replenishment method mentioned above.

[0081] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned method for replenishing refined oil is implemented.

[0082] It can be seen from the above technical solution that, compared with the prior art, the present invention discloses a method for replenishing finished oil products based on a three-layer logistics network, which takes into account primary transportation and secondary distribution to achieve global optimization, changes the layout of oil depots by introducing decisions on candidate oil depots, and thus can improve operating efficiency by optimizing the layout of oil depots. BRIEF DESCRIPTION OF THE DRAWINGS

[0083] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0084] Figure 1 A schematic diagram of a method for replenishing refined oil products based on a three-layer logistics network provided in an embodiment of the present invention;

[0085] Figure 2 This is a schematic diagram of the structure of a three-layer logistics network in an embodiment of the present invention;

[0086] Figure 3 Schematic diagram of a method for obtaining an optimal solution in an embodiment of the present invention. DETAILED DESCRIPTION

[0087] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0088] Example 1

[0089] like Figure 1 and Figure 2 The embodiment of the present invention discloses a method for replenishing refined oil based on a three-layer logistics network, wherein the three-layer logistics network includes: a refinery-an oil depot-a gas station.

[0090] The steps of the replenishment method include:

[0091] S1: Primary distribution from the refinery to the oil depot and secondary distribution from the oil depot to the gas station.

[0092] S2: Confirm the fixed oil depot subset and the candidate oil depot subset in the oil depot node set.

[0093] S3: A primary distribution model and a secondary distribution model are constructed based on the fixed oil depot subset and the candidate oil depot subset; in the primary distribution model and the secondary distribution model, decision variables are introduced for the candidate oil depot subset to express the loading and unloading conditions of the candidate oil depots.

[0094] S4: Establish the objective function based on the primary transportation model and the secondary distribution model, calculate the optimal solution under the preset constraints, and confirm the replenishment plan, where the replenishment plan includes the input of candidate oil depots, that is, the oil depot layout, as well as the distribution targets of each node and the corresponding replenishment quantity.

[0095] In this embodiment, the present invention inputs corresponding cost parameters into the primary transportation model and the secondary model respectively, and combines the demand of each gas station, the initial inventory of the oil depot, the replenishment quantity of the oil depot, etc. as known conditions to construct the total cost under the total transportation model, and finally combines various constraints to obtain the optimal solution.

[0096] The present invention comprehensively considers the primary transportation and secondary distribution to formulate a replenishment strategy, and can achieve global optimization. At the same time, under the concept of global optimization, the present invention changes the layout of the oil depot by introducing the decision of the candidate oil depot, and then can improve the operation efficiency by optimizing the layout of the oil depot.

[0097] In order to further implement the above technical solution, the primary distribution model and secondary distribution model in S3 are:

[0098] One-time transport model:

[0099]

[0100]

[0101]

[0102]

[0103] Secondary transportation model:

[0104]

[0105]

[0106]

[0107]

[0108] Among them, o is the refinery node, O is the refinery set; i is the oil depot node, I is the oil depot set; n is the oil type, N is the oil type set is the unit distance and unit volume transportation cost of oil product n from refinery o to oil depot i; is the distance from refinery o to oil depot i, represents the transportation volume of oil product n from refinery o to oil depot i; is the average operating cost of oil depot i in one cycle, is the decision variable of the oil depot;

[0109] is the unit distance and unit volume transportation cost of oil product n from oil depot i to gas station j; is the distance from oil depot i to gas station j; is the distribution volume of oil product n from oil depot i to gas station j; is the candidate oil depot subset, It is a fixed oil depot subset.

[0110] in, ; ; sgn(x) represents the sign function of x, where is a 0-1 variable representing the transportation of oil product n from refinery o to oil depot i; when the input variable is That is, when the amount of oil product n is transferred from refinery o to oil depot i, if the amount is 0, the sign function returns 0, indicating that there is no transfer of oil product n from refinery o to oil depot i; if the amount is not 0, the sign function returns 1, indicating that there is a transfer of oil product n from refinery o to oil depot i; is the distribution volume of oil product n from oil depot i to gas station j. When the input variable is That is, when the distribution volume of oil product n from oil depot i to gas station j is 0, the sign function returns 0, indicating that no distribution of oil product n occurs from oil depot i to gas station j; if the distribution volume is not 0, the sign function returns 1, indicating that distribution of oil product n occurs from oil depot i to gas station j.

[0111] In this embodiment, the primary transportation model and the secondary distribution model can respectively represent the primary transportation situation and the secondary distribution situation. In the primary transportation model, each path from the refinery to the oil depot and the unit cost and distribution volume of the corresponding path can be obtained; in the secondary distribution model, each path from the oil depot to the gas station and the unit cost and distribution volume of the corresponding path can be obtained; in addition, the primary transportation model and the secondary transportation model can reflect the unified introduction of candidate oil depots.

[0112] In order to further implement the above technical solution, the primary transport model and the secondary distribution model can also represent different transportation methods to further reflect the transport or delivery situation. Take the primary transport as an example:

[0113] The one-time transportation model can be further expressed as:

[0114]

[0115] in, It is a 0-1 variable, indicating the use of transportation mode m from refinery o to oil depot i, where m is the transportation mode from refinery to oil depot, such as pipeline transportation, railway transportation and water transportation, and M is the set of transportation modes from refinery to oil depot.

[0116] Furthermore, the primary distribution model and the secondary distribution model can also describe the delivery and harvesting situations.

[0117] The one-time transportation model can be further expressed as:

[0118]

[0119]

[0120] in, is the fixed cost of shipment to refinery o, is the fixed cost of receiving goods at tank depot i.

[0121] The secondary distribution model can be further expressed as:

[0122]

[0123] in, The fixed cost of shipping to tank depot i, is the fixed cost of receiving goods at gas station j.

[0124] In this embodiment, the meanings of the objective functions of a dispatch model are as follows: It represents the transportation cost of oil products from refinery to oil depot; represents the total operating cost of the oil depot; It represents the fixed shipping cost of the refinery, which is only related to whether the shipment is made and has nothing to do with the specific transportation volume; It represents the fixed receiving cost of the oil depot, which is only related to whether the goods are received, and has nothing to do with the specific transportation volume. The four costs together constitute the total cost of a transfer from the refinery to the oil depot. The meanings of the objective function of the secondary distribution model are as follows: It represents the distribution cost of oil products from oil depots to gas stations; represents the total operating cost of the oil depot; It represents the fixed delivery cost of the oil depot, which is only related to whether the oil depot delivers the goods, and has nothing to do with the specific transportation volume; It represents the fixed receiving cost of the gas station, which is only related to whether the goods are received, and has nothing to do with the specific transportation volume. The four costs together constitute the total cost of secondary distribution from the oil depot to the gas station.

[0125] In this embodiment, the primary dispatch refers to the delivery from the refinery to the oil depot node. When the oil depot is a candidate oil depot, the specific oil depot decision variable is used to determine whether to enable the candidate oil depot to complete the delivery. When the oil depot is a fixed oil depot, the decision variable is fixed to 1, which means that the delivery route is fixed. Similarly, the secondary delivery refers to the delivery from the oil depot node to the gas station. For the candidate node, the delivery from the candidate oil depot node to the gas station can only be realized when the candidate node is enabled and the delivery is executed.

[0126] Further, S4 is: inputting cost parameters into the primary transportation model and the secondary distribution model respectively, calculating the primary transportation cost and the secondary distribution cost, and establishing a cost objective function. The cost parameters include one or more of the unit transportation cost of each route, the refinery delivery cost, the oil depot operation cost, the oil depot delivery cost, the oil depot receiving cost, and the gas station receiving cost.

[0127] Specifically, the cost objective function represents the desire to optimize the problem by minimizing the total cost, including the transportation cost of oil products from the refinery to the oil depot, the transportation cost of oil products from the oil depot to the gas station, the total operating cost of the oil depot, the fixed shipping cost of the refinery, the fixed shipping cost of the oil depot, the fixed receiving cost of the oil depot, and the fixed receiving cost of the gas station. The cost objective function is:

[0128]

[0129]

[0130]

[0131]

[0132]

[0133] in, is a 0-1 variable, indicating the use of transportation mode m from refinery o to oil depot i. is the unit distance and unit volume transportation cost of oil product n from refinery o to oil depot i, is the distance from refinery o to oil depot i, represents the transportation volume of oil product n from refinery o to oil depot i; is the unit distance and unit volume transportation cost of oil product n from oil depot i to gas station j, is the distance from oil depot i to gas station j, For oil depot The delivery volume of oil product n to gas station j; is the oil depot decision variable, For oil depot The operating costs of the project are amortized over a period of time; is the fixed cost of shipment to refinery o, is a 0-1 variable representing the transportation of oil product n from refinery o to oil depot i, For oil depot Fixed costs of shipping, is a 0-1 variable representing the distribution of oil product n from oil depot i to gas station j, For oil depot Fixed costs of receiving goods, is the fixed cost of receiving goods at gas station j. is a symbolic function whose specific meaning depends on the input variable. That is, when the transfer volume of oil product n from refinery o to oil depot i is 0, the sign function returns 0, indicating that there is no transfer of oil product n from refinery o to oil depot i; if the transfer volume is not 0, the sign function returns 1, indicating that there is a transfer of oil product n from refinery o to oil depot i. That is, when the distribution volume of oil product n from oil depot i to gas station j is 0, the sign function returns 0, indicating that oil product n is not distributed from oil depot i to gas station j; when the transportation volume is not 0, the sign function returns 1, indicating that oil product n is distributed from oil depot i to gas station j. The terms of the objective function correspond to the transportation cost of oil products from the refinery to the oil depot, the distribution cost of oil products from the oil depot to the gas station, the total operating cost of the oil depot, the fixed shipping cost of the refinery, the fixed shipping cost of the gas station, the fixed receiving cost of the oil depot, and the fixed receiving cost of the gas station.

[0134] In this embodiment, is a known condition, which represents the set of all fixed oil depots and candidate oil depots; the cost incurred by the oil depot to receive oil products from the refinery and the unit cost incurred by the gas station to receive oil products from the oil depot include transportation cost, loading and unloading cost, etc. This cost is related to the type of oil, route and transportation volume.

[0135] Furthermore, the objective function also includes a utilization objective function, which means that the problem is optimized by maximizing the utilization of the oil depot in use, including the utilization of the oil depot's loading and unloading capacity and the utilization of the oil delivery capacity. The utilization objective function is:

[0136]

[0137] in, is the important parameter of the oil depot’s oil delivery capacity utilization rate, is the maximum oil delivery amount of oil product n in oil depot i, is the maximum loading and unloading capacity of oil product n at oil depot i.

[0138] In order to further implement the above technical solutions, the constraints include: flow balance constraints, loading and unloading volume and fuel delivery volume constraints, carrying volume constraints, distribution radius constraints, decision variable value constraints and service mode constraints;

[0139] Traffic balancing constraints include:

[0140] Constraint 1:

[0141] Constraint 2:

[0142] Constraint 3:

[0143] in, is the beginning inventory of oil product n in gas station j, is the demand for oil product n at gas station j; is the initial inventory of oil product n at oil depot i. Constraint 1 means that the sum of the initial inventory and replenishment of the gas station must meet the demand of the gas station; Constraint 2 means that the sum of the initial inventory and replenishment of the oil depot is equal to the sum of the total replenishment of each gas station; Constraint 3 means the total flow balance constraint of each oil product, that is, for each oil product, the sum of the total replenishment of the oil depot and the initial total inventory of the oil depot in use and the initial total inventory of the gas station must meet the demand of the gas station.

[0144] The restrictions on the loading and unloading volume and the oil delivery volume include:

[0145] Constraint 4:

[0146] Constraint 5:

[0147] in, is the minimum unloading amount of oil product n in oil depot i, is the maximum unloading capacity of oil product n in oil depot i; is the minimum oil delivery quantity of oil product n in oil depot i, is the maximum oil delivery quantity of oil product n in oil depot i; constraint 4 represents the loading and unloading quantity limit of each oil product in each oil depot, and the loading and unloading quantity of oil depots not in use is 0; constraint 5 represents the oil delivery quantity limit of each oil product in each oil depot, and the oil delivery quantity of oil depots not in use is 0.

[0148] Capacity constraints include:

[0149] Constraint 6:

[0150] Constraint 7:

[0151] in, is the maximum transport volume from refinery to oil depot using transport mode m, is the maximum delivery volume from the oil depot to the gas station using road transportation; constraint 6 represents the transportation volume limit for each path from the refinery to the oil depot, and the sum of the transportation volume of each oil product on the path cannot exceed the maximum transportation volume of the path; constraint 7 represents the delivery volume limit for each path from the oil depot to the gas station, and the sum of the delivery volume of each oil product on the path cannot exceed the maximum delivery volume of the path.

[0152] The delivery radius constraints include:

[0153] Constraint 8:

[0154] Constraint 9:

[0155] in, is the maximum transportation radius from refinery to oil depot using transportation mode m, It is the maximum delivery radius of road transportation from oil depot to gas station; Constraint 8 indicates that the transportation distance from refinery to oil depot cannot exceed the set maximum transportation radius; Constraint 9 indicates that the distribution distance from refinery to oil depot cannot exceed the set distribution radius.

[0156] The decision variable value constraints include:

[0157] Constraint 10:

[0158] Constraint 11:

[0159] Constraint 12:

[0160] Constraint 13:

[0161] in, represents the transportation volume of oil product n from refinery o to oil depot i, is the decision variable of the oil depot; is the distribution volume of oil product n from oil depot i to gas station j; is the candidate oil depot subset, It is a fixed oil depot subset.

[0162] Service model constraints include:

[0163] Constraint 14:

[0164] Constraint 15:

[0165] In the service mode constraints, constraint 14 indicates that the oil depot that is not in use does not need to be replenished; constraint 15 indicates that the oil depot that is not in use does not participate in the replenishment service for the gas station.

[0166] The present invention studies the replenishment optimization problem of the refined oil supply chain network, and establishes a replenishment model based on actual business scenarios with the goal of minimizing the total replenishment cost.

[0167] In addition to optimizing replenishment strategies, optimizing oil depot layout is also the key to reducing total costs and improving supply chain efficiency. Reasonable oil depot layout can reduce transportation distance and transportation costs, improve the service capacity of oil depots to surrounding gas stations, and thus reduce overall logistics costs.

[0168] like Figure 3 , using genetic algorithm to find the optimal solution. Based on the mathematical model, chromosomes are constructed by combining 0-1 binary coding with real number coding. 0-1 binary coding is used to indicate whether the candidate oil depot is put into use, and real number coding is used to indicate the distribution volume of each oil product from refinery to oil depot and from oil depot to gas station. Parameters such as population size, crossover probability, and mutation probability are set. The specific solution steps are described as follows:

[0169] S41: Initialize the oil depot site selection plan and the distribution volume allocation plan that meets the oil depot site selection plan, and obtain multiple populations and the corresponding individuals in each population as the initialization result; In the initialization result, each gene bit corresponding to the fixed oil depot is a fixed parameter value, and the gene bit corresponding to the candidate oil depot is a random value. Specifically, first, randomly generate the initial oil depot site selection plan. The fixed oil depot set and the candidate oil depot set are known conditions. When generating the oil depot site selection plan, all fixed oil depots must be put into use, and the corresponding gene bit value is fixed to 1; whether the candidate oil depot is put into use is determined according to a random number, and the corresponding gene bit value of 0 indicates that the candidate oil depot is not put into use, and the value of 1 indicates that the candidate oil depot is put into use. Secondly, according to the initial oil depot site selection plan and the demand of each oil product at the gas station, randomly generate as many oil product distribution volume allocation plans as possible. When the candidate oil depot is put into use, the corresponding oil product distribution volume is not 0. In order to ensure that the distribution volume can meet the needs of each gas station, the corresponding gene bit represents the demand percentage allocation plan borne by the corresponding path. Different oil distribution plans under the same oil depot site selection plan are regarded as different individuals under the same population; the individual site selection plans of different populations are different.

[0170] S42: Perform crossover and mutation based on the initialization result, and update the individuals in the population. Perform crossover and mutation operations in the entire population according to a certain probability. Specifically, randomly select two individuals, generate a random number between 0 and 1, and if the random number is lower than the crossover probability, the two individuals cross; randomly select a population, generate a random number between 0 and 1, and if the random number is lower than the mutation probability, the population mutates. There are two types of crossover operations: one is performed between different individuals in the same population, and the two-point crossover operator is applied to the oil distribution codes of the two individuals; the other is performed between different individuals in different populations, and the oil distribution codes of the two individuals are exchanged. The mutation operation is performed on a single population, and a new oil depot site selection plan is randomly generated to replace the old oil depot site selection plan.

[0171] S43: Calculate the fitness of each individual, i.e., the fitness of the chromosome, and select multiple individuals with the largest fitness to be retained and enter the next generation; wherein the individual fitness is the weighted sum of the objective function value or multiple objective function values. For example, when the objective function includes the above-mentioned cost objective function and utilization objective function, the two objective functions are weightedly summed to eliminate the influence of different dimensions. Considering the cost objective function To minimize the objective, the utilization objective function In order to maximize the goal, the cost objective function is transformed into Transform to maximize the goal , and eliminate the influence of different dimensions of the objective function on the result by weighted summation to obtain the individual fitness value.

[0172]

[0173]

[0174] in To maximize the goal The importance parameter, To maximize the goal The importance parameter of . and The value of and The size gap is determined, which is a known condition in this case. The fitness value of the individual is calculated according to the objective function after weighted summation, and the individual with the largest fitness is selected as the preferred individual to enter the next generation.

[0175] S44: Repeat S42 and S43 until the iteration is completed, and output the best individuals in each population for comparison, and obtain the best individuals in the best population, that is, the best replenishment plan under the optimal oil depot layout. Among them, the replenishment plan includes the primary transportation route and the secondary distribution route, as well as the corresponding replenishment quantity and corresponding cost of each route; it can also include the transportation type and oil type of each route, as well as the total cost of the primary transportation and secondary distribution. Through sensitivity analysis, the impact of the change of the minimum oil payment on the total cost is studied. The results show that the total cost increases monotonically with the increase of the minimum oil payment. The smaller the minimum oil payment is set, the lower the total cost. When the minimum oil payment is set large enough, the total cost no longer changes with the change of the minimum oil payment.

[0176] Choose any unused oil depot in the solution and calculate the total cost of putting it into use. Compare the total cost of putting the oil depot into use with the total cost of not putting it into use, and find that the total cost of putting it into use is higher than the total cost of not putting it into use.

[0177] The experimental results show that the optimal replenishment plan can help supply chain managers make better replenishment decisions to ensure that each gas station can obtain the required oil products in a timely manner and maintain the normal operation of the supply chain under the premise of controlling the replenishment cost. The optimal oil depot layout plan balances the operating cost and transportation cost of the oil depot, and minimizes the total cost in the finished oil logistics network.

[0178] Example 2

[0179] Based on the same inventive concept, an embodiment of the present invention discloses a refined oil replenishment system based on a three-layer logistics network, including a computer system, which is used to execute the refined oil replenishment method in Example 1.

[0180] Example 3

[0181] Based on the same inventive concept, an embodiment of the present invention discloses a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the refined oil replenishment method in Embodiment 1 is implemented.

[0182] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0183] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for replenishing refined oil products based on a three-layer logistics network, characterized in that: The three-layer logistics network includes: refinery-oil depot-gas station; the replenishment method includes: primary distribution from the refinery to the oil depot and secondary distribution from the oil depot to the gas station; Confirming a fixed oil depot subset and a candidate oil depot subset in the oil depot node set; A primary dispatch model and a secondary distribution model are constructed based on the fixed oil depot subset and the candidate oil depot subset; in the primary dispatch model and the secondary distribution model, decision variables are introduced for the candidate oil depot subset to express the decision situation of the candidate oil depot being put into use; An objective function is established based on the primary distribution model and the secondary distribution model, and the optimal solution is calculated under preset constraints to confirm the distribution target and corresponding replenishment quantity of each node under the optimal oil depot layout.

2. A method for replenishing refined oil products based on a three-layer logistics network according to claim 1, characterized in that: A primary dispatch model and a secondary distribution model are constructed based on the fixed oil depot subset and the candidate oil depot subset, specifically: The one-time transportation model is: ； ； ； ； The secondary distribution model is: ； ； ； ； Where o is a refinery node, O is a refinery set; i is a tank depot node, I is a tank depot set; n is a fuel type, N is a fuel type set; is the unit distance and unit volume transportation cost of oil product n from refinery o to oil depot i; is the distance from refinery o to oil depot i, represents the volume of oil product n transferred from refinery o to oil depot i; is the average operating cost of oil depot i in one cycle, is the decision variable of the oil depot; is the unit distance and unit volume transportation cost of oil product n from oil depot i to gas station j; is the distance from oil depot i to gas station j; is the delivery volume of oil product n from oil depot i to gas station j; is the candidate oil depot subset, It is a fixed oil depot subset.

3. The method for replenishing refined oil products based on a three-layer logistics network according to claim 1, characterized in that: An objective function is established according to the primary transport model and the secondary distribution model, specifically: cost parameters are input into the primary transport model and the secondary distribution model respectively, the primary transport cost and the secondary distribution cost are calculated, and a cost objective function is established.

4. A method for replenishing refined oil products based on a three-layer logistics network according to claim 3, characterized in that: The cost parameters include one or more of the unit transportation cost of each route, refinery delivery cost, oil depot operating cost, oil depot delivery cost, oil depot receiving cost, and gas station receiving cost.

5. The method for replenishing refined oil products based on a three-layer logistics network according to claim 3, characterized in that: The cost objective function is: ； ； ； in, It represents the usage of transport mode m from refinery o to oil depot i. is the unit distance and unit volume transportation cost of oil product n from refinery o to oil depot i, is the distance from refinery o to oil depot i, represents the volume of oil product n transferred from refinery o to oil depot i; is the unit distance and unit volume transportation cost of oil product n from oil depot i to gas station j, is the distance from oil depot i to gas station j, is the delivery volume of oil product n from oil depot i to gas station j; is the oil depot decision variable, The operating cost of oil depot i put into use is amortized over one cycle; is the fixed cost of shipment to refinery o, is a 0-1 variable representing the transportation of oil product n from refinery o to oil depot i, is the fixed cost of shipping from depot i, is a 0-1 variable representing the distribution of oil product n from oil depot i to gas station j, is the fixed cost of receiving goods at oil depot i, is the fixed cost of receiving goods at gas station j.

6. The method for replenishing refined oil products based on a three-layer logistics network according to claim 3, characterized in that: The objective function also includes a utilization objective function: ； in, is the important parameter of the oil depot’s oil delivery capacity utilization rate, is the maximum oil delivery quantity of oil product n in oil depot i, The maximum loading and unloading capacity of oil product n in oil depot i.

7. A method for replenishing refined oil products based on a three-layer logistics network according to claim 5 or 6, characterized in that: The constraints include one or more of flow balance constraints, loading and unloading and fuel delivery constraints, carrying capacity constraints, delivery radius constraints, decision variable value constraints, and service mode constraints; The flow balance constraints include: ； ； ； in, is the beginning inventory of oil product n at gas station j, is the demand for oil product n at gas station j; is the beginning inventory of oil product n in oil depot i; The loading and unloading volume and fuel delivery volume constraints include: ； ； in, is the minimum unloading quantity of oil product n in oil depot i, is the maximum loading and unloading capacity of oil product n in oil depot i; is the minimum oil delivery quantity of oil product n in oil depot i, is the maximum oil delivery quantity of oil product n in oil depot i; The carrying capacity constraints include: ； ； in, is the maximum transport volume from refinery to oil depot using transport mode m, The maximum delivery volume from the oil depot to the gas station using road transport; The delivery radius constraints include: ； ； in, The maximum transport radius from refinery to oil depot using transport mode m, The maximum delivery radius from the oil depot to the gas station using road transport; The decision variable value constraints include: ； ； ； ； in, represents the amount of oil product n transported from refinery o to oil depot i, is the decision variable of the oil depot; is the delivery volume of oil product n from oil depot i to gas station j; is the candidate oil depot subset, It is a fixed oil depot subset; The service mode constraints include: ； ； The service mode constraint indicates that the oil depot that is not in use does not need to be replenished and does not participate in the replenishment service for the gas station.

8. The method for replenishing refined oil products based on a three-layer logistics network according to claim 1, characterized in that: The optimal solution is calculated using a genetic algorithm, and the steps include: Initializing the oil depot site selection plan and the distribution volume allocation plan that conforms to the oil depot site selection plan, and obtaining multiple populations and corresponding individuals in each population as initialization results; in the initialization results, each gene bit corresponding to the fixed oil depot is a fixed parameter value, and each gene bit corresponding to the candidate oil depot is a random value; Perform crossover mutation based on the initialization results and update the population individuals; Calculate the fitness of each individual and select the individuals with the largest fitness to be retained and enter the next generation; the individual fitness is the objective function value or the weighted sum of multiple objective function values; Repeat S2 and S3 until the iteration is completed, and output the best individuals in each population for comparison to obtain the best individual in the best population, that is, the best replenishment plan under the optimal oil depot layout.

9. A refined oil replenishment system based on a three-layer logistics network, characterized in that: The method comprises a computer system for executing the method for replenishing refined oil products according to any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for replenishing refined oil according to any one of claims 1 to 8 is implemented.

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