Warehouse-out wave optimization method and system based on dynamic route selection

Abstract

The invention discloses a warehouse-out wave optimization method and system based on dynamic route selection, and the method comprises the steps: employing a package warehouse-VMI warehouse route selection model to focus one order in one VMI warehouse at a time to meet the route selection of all SKU demands, facing a continuously changing logistics environment, inputting the orders one by one according to a time sequence, and carrying out the optimization of the SKU demands. Dynamic route selection can be carried out in real time; on the basis, the optimal ex-warehouse wave of the package warehouse is obtained through the ex-warehouse wave optimization model based on dynamic route selection, the delivery mode of a traditional fixed line is changed through the ex-warehouse wave optimization strategy based on dynamic route selection, the ex-warehouse route and wave arrangement can be adjusted according to real-time data, and the optimal ex-warehouse wave of the package warehouse is obtained. It is ensured that each time of transportation is in butt joint with demand changes, and resource waste and time delay are avoided; as the model can flexibly deal with various emergencies and timely adjust the transportation strategy, the toughness and stability of the supply chain are further enhanced, and powerful guarantee is provided for enterprises to deal with future uncertainty.

Description

Technical Field

[0001] The present invention belongs to the technical field of logistics, and in particular, relates to a method and system for optimizing outbound waves based on dynamic route selection. Background Art

[0002] The cost of delivering raw materials for home appliances is complex and involves multiple links, of which the front-end transportation segment and the end-end warehouse distribution segment are the two main components. In the front-end transportation segment, the cost accounts for 60% of the total cost, which can be further divided into two types: bulk transportation and non-bulk transportation.

[0003] Bulk transportation mainly involves bulk raw materials required for home appliance manufacturing, such as steel, copper pipes, aluminum foil, pellets, presses, and motors. The transportation of these materials is usually carried out by direct point-to-point trunk lines, and the cost is mainly concentrated on transportation costs. Due to the large volume of bulk materials, price competitiveness has become a key factor in reducing costs. In this link, home appliance companies need to work closely with logistics suppliers to strive for more favorable transportation prices through bulk purchases, long-term contracts, etc.

[0004] Non-bulk transportation involves small materials such as standard parts, electrical components, and packaging auxiliary parts. The transportation of these materials is mainly LTL. The cost of LTL transportation includes freight collection fees, warehouse operation fees at both ends, trunk line transportation fees, and terminal delivery fees. Since the transportation of non-bulk materials is relatively scattered, how to effectively integrate resources, increase loading rates, and optimize transportation routes have become important issues in reducing costs.

[0005] At present, the main problem facing the delivery of raw materials for home appliances is the LTL delivery model. In the Yangtze River Delta region, for example, the number of suppliers exceeds 250, and the distribution is relatively concentrated. According to market research, there are at least 30 LTL special line companies transporting raw materials from different suppliers, and on average each company transports about 5-10 home appliance suppliers. This decentralized, small-scale, and disorderly competition situation has led to problems such as low delivery efficiency, high costs, and uneven service quality.

[0006] The current delivery mode is difficult to adapt to the flexible production of multiple varieties and small batches, with low competitiveness. As the trend of diversified and personalized market demand becomes increasingly prominent, the home appliance industry is gradually transforming towards a flexible production mode of multiple varieties and small batches. However, under the traditional logistics delivery mode, relying on fixed-route transportation plans, it is difficult to adapt to the demand fluctuations of this production mode. Therefore, due to the rigid characteristics of this delivery mode, when suppliers face the flexible production plans and rapidly changing demands of factories, it is difficult for them to make timely responses and adjustments, resulting in long delivery cycles and slow response speeds, further increasing the instability of the supply chain. The flexibility of the supply chain is closely related to its ability to adapt to market changes. An overly rigid delivery mode not only affects the agility of the supply chain but also restricts the competitive advantages of the entire logistics industry chain. Summary of the Invention

[0007] The present invention proposes an optimized method and system for outbound wave based on dynamic route selection. By determining the dynamic optimal path through the pick-up warehouse - VMI warehouse route selection model, and then determining the optimal outbound wave of the pick-up warehouse through the optimized model for outbound wave based on dynamic route selection, the delivery cycle is shortened, and the resilience and stability of the supply chain are enhanced.

[0008] The present invention is implemented by adopting the following technical solutions:

[0009] Propose an optimized method for outbound wave based on dynamic route selection, including:

[0010] S1: Construct a pick-up warehouse - VMI warehouse route selection model:

[0011]

[0012] Among them, m (m = 1,..., M) is the pick-up warehouse code, n (n = 1,..., N) is the VMI warehouse code, i (i ∈ I) is the sku code, represents the unit distance cost of unit raw material i from the m-th pick-up warehouse to the n-th VMI warehouse, d m,n represents the distance from the m-th pick-up warehouse to the n-th VMI warehouse, D i is the demand of the i-th sku, is the inventory of the i-th sku in the current m-th pick-up warehouse, represents the transportation volume of the i-th sku from the m-th pick-up warehouse to the n-th VMI warehouse;

[0013] S2: Construct an optimized model for outbound wave based on dynamic route selection:

[0014] Max: ∑ 1≤i≤n ∑ 1≤j≤n S i,j X i,j ;

[0015]

[0016] X i,j = X j,i , for i ∈ I, for j ∈ I;

[0017] X i,i = 1, for i ∈ I;

[0018] X i,j = 1, if X i,m + X j,m = 2, for i ∈ I, for j ∈ I, for m ∈ I;

[0019] Wherein, i, j (i, j = 1, …, n) are the sku numbers of the orders dispatched from the VMI warehouse, S i,j The number of overlapping paths of the i, j-th sku, v i Is the volume of the i-th sku, V is the upper limit of the volume of a single transportation, X i,j Indicates whether the i, j-th sku enters the same wave;

[0020] S3: Based on the pick-up warehouse - VMI warehouse route selection model, obtain the optimal route from the pick-up warehouse to the VMI warehouse, and adopt the outbound wave optimization model based on dynamic route selection for different SKUs to obtain the optimal outbound wave plan.

[0021] In some embodiments of the present invention, the pick-up warehouse - VMI warehouse route selection model calculates the route selection that meets the requirements of all SKUs in one order in one VIM warehouse at a time, and n is a fixed value.

[0022] In some embodiments of the present invention, when solving, the pick-up warehouse - VMI warehouse route selection model selects the pick-up warehouses that can not only meet the current order requirements but also have room in the inventory capacity according to the inventory status of each pick-up warehouse and adds them to the optimal path planning.

[0023] In some embodiments of the present invention, the outbound wave optimization model based on dynamic route selection obtains the optimal routes from the pick-up warehouse to multiple VMIs based on the pick-up warehouse - VMI warehouse route selection model, and optimizes the waves for different SKU deliveries.

[0024] In some embodiments of the present invention, the outbound wave optimization model based on dynamic route selection optimizes the outbound waves of one pick-up warehouse at a time, and multiple pick-up warehouses optimize the waves simultaneously according to the time of detecting the order volume and the threshold of the cumulative orders.

[0025] Propose an outbound wave optimization system based on dynamic route selection, including:

[0026] The route selection unit for the cargo collection warehouse - VMI warehouse is used to obtain the optimal route from the cargo collection warehouse to the VMI warehouse based on the route selection model for the cargo collection warehouse - VMI warehouse; the route selection model for the cargo collection warehouse - VMI warehouse is as follows:

[0027]

[0028] where m (m = 1, …, M) is the code of the cargo collection warehouse, n (n = 1, …, N) is the code of the VMI warehouse, and i (i ∈ I) is the sku code. represents the unit distance cost of unit raw material i from the m-th cargo collection warehouse to the n-th VMI warehouse, d m,n represents the distance from the m-th cargo collection warehouse to the n-th VMI warehouse, D i is the demand of the i-th sku, is the inventory of the i-th sku in the current m-th cargo collection warehouse, represents the transportation volume of the i-th sku from the m-th cargo collection warehouse to the n-th VMI warehouse;

[0029] The outbound wave optimization unit based on dynamic route selection is used to obtain the optimal outbound wave plan for different SKUs by using the outbound wave optimization model based on dynamic route selection; the outbound wave optimization model based on dynamic route selection is as follows:

[0030] Max: ∑ 1≤i≤n ∑ 1≤j≤n S i,j X i,j ;

[0031]

[0032] X i,j = X j,i , for i ∈ I, for j ∈ I;

[0033] X i,i = 1, for i ∈ I;

[0034] X i,j = 1, if X i,m + X j,m = 2, for i ∈ I, for j ∈ I, for m ∈ I;

[0035] where i, j (i, j = 1, …, n) are the sku numbers of the orders dispatched by the VMI warehouse, S i,j is the number of overlapping paths of the i, j-th sku, v i is the volume of the i-th sku, V is the upper limit of the volume of a single transportation, and X i,j indicates whether the i, j-th sku enters the same wave.

[0036] In some embodiments of the present invention, the route selection model for the pick-up warehouse - VMI warehouse calculates the route selection that meets the requirements of all SKUs in one order in one VMI warehouse each time, and n is a fixed value.

[0037] In some embodiments of the present invention, when solving, the route selection model for the pick-up warehouse - VMI warehouse selects pick-up warehouses that can not only meet the current order requirements but also have some margin in inventory capacity according to the inventory status of each pick-up warehouse and adds them to the optimal route planning.

[0038] In some embodiments of the present invention, the outbound wave optimization model based on dynamic route selection obtains the optimal routes from the pick-up warehouse to multiple VMIs based on the route selection model for the pick-up warehouse - VMI warehouse, and performs wave optimization for different SKU deliveries.

[0039] In some embodiments of the present invention, the outbound wave optimization model based on dynamic route selection optimizes the outbound wave of one pick-up warehouse each time, and multiple pick-up warehouses perform wave optimization simultaneously according to the time of detecting the order volume and the threshold of the cumulative order.

[0040] Compared with the prior art, the advantages and positive effects of the present invention are as follows: The outbound wave optimization method and system based on dynamic route selection proposed by the present invention adopt the route selection model for the pick-up warehouse - VMI warehouse to focus on the route selection that meets the requirements of all SKUs in one order in one VMI warehouse each time. Facing the constantly changing logistics environment, by inputting orders one by one in chronological order, it can perform dynamic route selection in real time; on this basis, the optimal outbound wave of the pick-up warehouse is obtained through the outbound wave optimization model based on dynamic route selection. This outbound wave optimization strategy based on dynamic route selection changes the traditional fixed-line delivery mode. The model can adjust the outbound route and wave arrangement according to real-time data, ensuring that each transportation adapts to the changing demand, effectively avoiding waste of resources and delay of time. At the same time, since the model can flexibly respond to various emergencies and adjust the transportation strategy in a timely manner, it further enhances the resilience and stability of the supply chain, providing a strong guarantee for enterprises to cope with future uncertainties.

[0041] After reading the detailed description of the embodiments of the present invention in conjunction with the accompanying drawings, other features and advantages of the present invention will become clearer. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0043] Figure 1 It is a schematic diagram of the entire supply chain from the supplier - goods collection warehouse - VMI warehouse - production engineering in the present invention;

[0044] Figure 2 It is a schematic diagram of the outbound wave optimization method based on dynamic route selection proposed by the present invention;

[0045] Figure 3 It is a schematic diagram of the system architecture of the outbound wave optimization based on dynamic route selection proposed by the present invention. Detailed implementation manners

[0046] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0047] As Figure 1 shown, the goods collection warehouse in the logistics supply chain is a warehouse for centrally collecting goods; it gathers the goods scattered in different locations to facilitate subsequent unified transportation and processing; the VMI warehouse is a temporary storage material warehouse jointly established and managed by the enterprise and the supplier to achieve the lowest cost goal; based on the entire supply chain of the supplier - goods collection warehouse - VMI warehouse - production factory, it can accurately coordinate demand and supply, reduce inventory overstock or shortage, improve the overall inventory turnover rate, and at the same time promote the timely transmission of demand information from the production factory to the supplier. The enterprise can make more accurate inventory preparation, production, and transportation decisions, avoid the demand amplification effect caused by information lag, and reduce the fluctuations in the supply chain.

[0048] The present invention aims to propose an outbound wave optimization method to reduce the goods transportation time by optimizing the goods transportation route and outbound method, improve the goods turnover speed, and achieve the technical effects of reducing both human and resource consumption and reducing the invisible costs of logistics.

[0049] S1: Build a route selection model for the goods collection warehouse - VMI warehouse.

[0050] The emergence of the goods collection warehouse under the three - level link model solves the current situation of the less - than - truckload delivery mode in the two - pole model (from the supplier to the production factory). After the location of the goods collection warehouse is determined, a satisfactory optimal route for the cost of the supplier - goods collection warehouse - VMI warehouse can be obtained, and the main burden of the entire supply chain transportation cost is in the section from the goods collection warehouse to the VMI warehouse. The present invention first selects the path with the minimum cost from the goods collection warehouse to the VMI warehouse through the VMI warehouse - goods collection warehouse route selection model to reduce the transportation cost of the entire supply chain.

[0051] Model assumptions: (1) The transportation cost is borne by the VMI warehouse, and the inventory cost is borne by the cargo collection warehouse. Therefore, when the VMI warehouse selects the route of the cargo collection warehouse, it only needs to consider the transportation cost and does not need to consider the inventory cost of the cargo collection warehouse; (2) The transportation cost has a functional relationship with the transportation quantity and transportation distance, that is, C t = f(s, d). Since the distance from the cargo collection warehouse to the VMI is an input parameter and the transportation quantity is a decision variable, taking a linear functional relationship to simplify the model calculation, the total transportation cost C t = cds, where c is the cost per unit distance of a unit of raw material; (3) Under the information sharing mode of full-link connection, the VMI warehouse can obtain the current inventory level of each sku of each cargo collection warehouse in real time; (4) This model only considers the route selection problem from newly built cargo collection warehouses to the VMI. For VMI warehouses that are expanded to realize the functions of cargo collection warehouses, it is considered that they do not need to make route selections; (5) This optimization model calculates the route selection that meets the requirements of all skus in one order in one VMI warehouse at a time. That is, n is a fixed value each time it is calculated.

[0052] Construct the objective function with the minimum transportation cost (the total cost of transporting raw material supplies from the cargo collection warehouse to the VMI warehouse):

[0053]

[0054] The constraint conditions include:

[0055] 1) Meet the order demand: The total transportation volume of all raw materials should meet the demand of this order, which is expressed as:

[0056]

[0057] 2) Meet the inventory constraint of the cargo collection warehouse: The various raw materials allocated to a single cargo collection warehouse should be less than or equal to the current inventory of this type of raw material in this cargo collection warehouse, which is expressed as:

[0058]

[0059] In summary, the following objective function and constraint conditions can be constructed:

[0060]

[0061]

[0062]

[0063] Among them, m (m = 1, …, M) is the code of the cargo collection warehouse, n (n = 1, …, N) is the code of the VMI warehouse, i (i ∈ I) is the code of the sku, represents the cost per unit distance of unit raw material i from the m-th cargo collection warehouse to the n-th VMI warehouse, dm,n Denote the distance from the m-th cargo collection warehouse to the n-th VMI warehouse as D i is the demand quantity of the i-th sku, is the inventory of the i-th sku in the current m-th cargo collection warehouse, Denote the transportation volume of the i-th sku from the m-th cargo collection warehouse to the n-th VMI warehouse.

[0064] Solvers such as Lingo can be called to solve this objective function.

[0065] Considering that the model specifically incorporates the inventory capacity constraint of the cargo collection warehouse as a key factor, this design greatly enhances its practicality and accuracy. During the solution process, the system will evaluate the inventory status of each cargo collection warehouse, and preferentially select those cargo collection warehouses that can not only meet the current order requirements but also have room in inventory capacity to be added to the optimal delivery route plan. Such a selection mechanism not only ensures the timely fulfillment of orders but also effectively avoids delays or cancellations caused by insufficient inventory, improving the overall efficiency of logistics operations.

[0066] In addition, a major highlight of this model lies in its flexibility and dynamics. It does not solve the route selection problems for all orders or all VMI (Vendor Managed Inventory) warehouses at once, but focuses on solving the path planning for a single VMI warehouse for a single order at a time. This design enables the model to easily cope with the ever-changing logistics environment. By inputting orders one by one in chronological order, the system can perform dynamic route selection in real time.

[0067] S2: Construct an outbound wave optimization model based on the dynamic route selection model.

[0068] In the context of the entire logistics chain, based on the cargo collection warehouse - VM warehouse route selection model, the optimal route from the cargo collection warehouse to the VMI warehouse can be determined. In the specific shipping scenario of the cargo collection warehouse, a single cargo collection warehouse needs to transport goods to multiple VMI warehouses. The outbound wave optimization model of the cargo collection warehouse aims to solve the problem of combining the skus of different orders to reduce the actual transportation cost.

[0069] Model assumptions: (1) Based on the optimal routes from the cargo collection warehouse to multiple VMI obtained from the dynamic route selection model of the cargo collection warehouse - VMI warehouse, perform wave optimization for different sku delivery problems; (2) There is an upper limit on the single - time transportation capacity, and the transportation capacity is measured by the volume of goods; (3) Regularly detect the order volume of the VMI warehouse, and perform wave optimization for the outbound of the cargo collection warehouse only when the order volume assigned to a single cargo collection warehouse accumulates to a certain value; (4) This model only considers the outbound wave optimization of a single cargo collection warehouse at a time. In the actual situation, multiple cargo collection warehouses determine the time to detect the order volume and the threshold for accumulating orders according to specific circumstances and perform wave optimization simultaneously.

[0070] Based on the route selection model from the cargo collection warehouse to the VMI warehouse, the path from the cargo collection warehouse to the VMI warehouse obtained is used as the basis for the minimum cost. When the number of repeated paths for a single transportation is larger, the distance that needs to be transshipped is less, thereby reducing the transportation cost. Therefore, the objective function is established with the maximum number of overlapping paths:

[0071] Max:∑ 1≤i≤n ∑ 1≤j≤n S i,j X i,j ;

[0072] The constraint conditions include:

[0073] (1) Upper limit of transportation capacity: There is an upper limit to the total volume of a single delivery. The selected SKUs need to meet this volume constraint, which can be expressed as follows:

[0074]

[0075] 2) Logical constraints:

[0076] X i,j =X j,i ,for i∈I、for j∈I;

[0077] X i,i =1,for i∈I;

[0078] X i,j =1,if X i,m +X j,m =2,for i∈I、for j∈I、for m∈I;

[0079] In summary, the following objective function and constraint conditions can be constructed:

[0080] Max:∑ 1≤i≤n ∑ 1≤j≤n S i,j X i,j ;

[0081]

[0082] X i,j =X j,i ,for i∈I、for j∈I;

[0083] X i,i =1,for i∈I;

[0084] X i,j =1,if X i,m +X j,m =2,for i∈I、for j∈I、for m∈I。

[0085] Among them, i, j (i, j = 1, …, n) are the sku numbers of the orders dispatched from the VMI warehouse, S i,j is the number of overlapping paths of the i, j-th sku, v i is the volume of the i-th sku, V is the upper limit of the volume of a single shipment, X i,j indicates whether the i, j-th sku enters the same wave.

[0086] The Lingo solver can be called to input the corresponding parameters for quick solution. The core innovation of this model lies in its outbound wave optimization strategy based on the dynamic route selection mechanism. This strategy changes the traditional fixed-route delivery mode and endows the transportation link with flexibility and adaptability. Facing the ever-changing market demands, the model can adjust the outbound routes and wave arrangements according to real-time data to ensure that each shipment can meet the demand changes, effectively avoiding resource waste and time delays.

[0087] In addition, the model also fully considers the capacity constraint of a single shipment. The incorporation of this key factor makes the optimization results closer to the actual operation scenario, ensuring the feasibility and economy of the transportation plan. Through refined capacity management, the model can maximize the utilization of transportation resources, reduce the empty load rate, and improve the overall transportation efficiency.

[0088] The most significant effect is that the application of this model shortens the delivery cycle, reducing the time from order receipt to the goods reaching the customer. This rapid response ability not only improves customer satisfaction but also enhances the enterprise's competitiveness in the market. At the same time, since the model can flexibly respond to various emergencies and adjust the transportation strategy in a timely manner, it further enhances the resilience and stability of the supply chain, providing a strong guarantee for the enterprise to cope with future uncertainties.

[0089] S3: Based on the pick-up warehouse - VMI warehouse route selection model, obtain the optimal route from the pick-up warehouse to the VMI warehouse, and for different SKUs, adopt the outbound wave optimization model to obtain the optimal outbound wave plan.

[0090] The optimal path with the minimum cost from each cargo collection warehouse to the VMI warehouse obtained through the cargo collection warehouse - VMI warehouse route selection model constructed by S1 is used to reduce the transportation cost of the entire link. And the cargo collection warehouse that can not only meet the current order demand but also has room in inventory capacity will be preferentially selected to join the optimal distribution route planning; focusing on solving the path planning design for a single VMI warehouse for a single order at a time can easily cope with the changing logistics environment. By inputting orders one by one in chronological order, the system can perform dynamic route selection in real time; for a single cargo collection warehouse that needs to transport goods to multiple VMI warehouses, after obtaining the optimal routes from the cargo collection warehouse to multiple VMI warehouses based on the cargo collection warehouse - VMI warehouse route selection model, for the problem of different SKU deliveries, the outbound wave optimization model constructed by S2 is used to combine the SKUs of different orders to obtain the optimal outbound wave strategy, which endows the transportation link with flexibility and adaptability. The model can adjust the outbound route and wave arrangement according to real - time data to ensure that each transportation docks with the demand changes, effectively avoiding resource waste and time delays, and shortening the time from order reception to the delivery of goods to customers.

[0091] Based on the above - mentioned outbound wave optimization method based on dynamic route selection, the present invention also proposes an outbound wave optimization system based on dynamic route selection, including:

[0092] Propose an outbound wave optimization system based on dynamic route selection, including:

[0093] A cargo collection warehouse - VMI warehouse route selection unit, used to obtain the optimal route from the cargo collection warehouse to the VMI warehouse based on the cargo collection warehouse - VMI warehouse route selection model; the cargo collection warehouse - VMI warehouse route selection model is:

[0094]

[0095] Among them, m (m = 1, …, M) is the cargo collection warehouse code, n (n = 1, …, N) is the VMI warehouse code, i (i ∈ I) is the sku code, represents the unit distance cost of unit raw material i from the m - th cargo collection warehouse to the n - th VMI warehouse, d m,n represents the distance from the m - th cargo collection warehouse to the n - th VMI warehouse, D i is the demand for the i - th sku, is the inventory of the i - th sku in the current m - th cargo collection warehouse, represents the transportation volume of the i - th sku from the m - th cargo collection warehouse to the n - th VMI warehouse.

[0096] An outbound wave optimization unit based on dynamic route selection, used to obtain the optimal outbound wave plan for different SKUs by using the outbound wave optimization model based on dynamic route selection; the outbound wave optimization model based on dynamic route selection is:

[0097] Max: ∑ 1≤i≤n ∑ 1≤j≤n S i,j X i,j ;

[0098]

[0099] X i,j = X j,i , for i ∈ I, for j ∈ I;

[0100] X i,i = 1, for i ∈ I;

[0101] X i,j = 1, if X i,m + X j,m = 2, for i ∈ I, for j ∈ I, for m ∈ I;

[0102] wherein, i, j (i, j = 1, …, n) are the sku numbers of the orders dispatched from the VMI warehouse, S i,j is the number of overlapping paths of the i, j-th sku, v i is the volume of the i-th sku, V is the upper limit of the volume of a single transportation, X i,j indicates whether the i, j-th sku enters the same wave.

[0103] In some embodiments of the present invention, the route selection model for the pick-up warehouse - VMI warehouse calculates the route selection that meets the requirements of all SKUs in one order in one VIM warehouse at a time, and n is a fixed value.

[0104] In some embodiments of the present invention, when solving, the route selection model for the pick-up warehouse - VMI warehouse selects the pick-up warehouses that can not only meet the current order requirements but also have room in the inventory capacity according to the inventory status of each pick-up warehouse and adds them to the optimal route planning.

[0105] In some embodiments of the present invention, the outbound wave optimization model based on dynamic route selection obtains the optimal routes from the pick-up warehouse to multiple VMI based on the route selection model for the pick-up warehouse - VMI warehouse, and performs wave optimization for different SKU deliveries.

[0106] In some embodiments of the present invention, the outbound wave optimization model based on dynamic route selection optimizes the outbound wave of one pick-up warehouse at a time, and multiple pick-up warehouses perform wave optimization simultaneously according to the time of detecting the order volume and the threshold of the cumulative orders.

[0107] The optimization method of the outbound wave optimization system based on dynamic route selection is described in detail in the method and will not be elaborated here.

[0108] It should be noted that, in the specific implementation process, the above control part can be implemented by a processor in hardware form executing computer-executable instructions in software form stored in a memory, which will not be elaborated here. And the programs corresponding to the actions executed by the above control circuit can all be stored in the computer-readable storage medium of the system in software form, so as to facilitate the processor to call and execute the operations corresponding to each of the above modules.

[0109] The computer-readable storage medium mentioned above may include volatile memory, such as random access memory; it may also include non-volatile memory, such as read-only memory, flash memory, hard disk or solid-state drive; it may also include a combination of the above types of memory.

[0110] The processor mentioned above can also be a general term for multiple processing elements. For example, the processor can be a central processing unit, or it can be other general-purpose processors, digital signal processors, application-specific integrated circuits, field-programmable gate arrays or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor, etc., and can also be a dedicated processor.

[0111] It should be pointed out that the above description is not a limitation of the present invention, and the present invention is not limited to the above examples. Changes, modifications, additions or substitutions made by those of ordinary skill in the art within the scope of the essence of the present invention should also fall within the protection scope of the present invention.

Claims

1. An outbound wave optimization method based on dynamic route selection, characterized in that Including: S1: Construct a route selection model for the pick-up warehouse - VMI warehouse: Among them, m (m = 1, …, M) is the cargo collection warehouse code, n (n = 1, …, N) is the VMI warehouse code, and i (i ∈ I) is the sku code. represents the unit distance cost of unit raw material i from the m-th cargo collection warehouse to the n-th VMI warehouse, d m,n represents the distance from the m-th cargo collection warehouse to the n-th VMI warehouse, D i is the demand of the i-th sku. is the inventory of the i-th sku in the current m-th cargo collection warehouse. represents the transportation volume of the i-th sku from the m-th cargo collection warehouse to the n-th VMI warehouse. S2: Construct an outbound wave optimization model based on dynamic route selection: Max: ∑ 1≤i≤n ∑ 1≤j≤n S i,j X i,j ; X i,j = X j,i , for i ∈ I, for j ∈ I; X i,i = 1 for i ∈ I; X i,j = 1, if X i,m + X j,m = 2, for i ∈ I, for j ∈ I, for m ∈ I; Among them, i, j (i, j = 1, …, n) are the sku numbers of the orders dispatched from the VMI warehouse, S i,j is the number of overlapping paths of the i, j-th sku, v i is the volume of the i-th sku, V is the upper limit of the volume for a single shipment, X i,j indicates whether the i, j-th sku enters the same wave; S3: Obtain the optimal route from the pick-up warehouse to the VMI warehouse based on the route selection model for the pick-up warehouse - VMI warehouse, and for different SKUs, obtain the optimal outbound wave plan using the outbound wave optimization model based on dynamic route selection.

2. The optimized outbound wave method based on dynamic route selection according to claim 1, wherein The route selection model for the pick-up warehouse - VMI warehouse calculates the route selection that meets the requirements of all SKUs in one order in one VIM warehouse at a time, and n is a fixed value.

3. The optimized method for outbound wave based on dynamic route selection according to claim 1, characterized in that When solving, the route selection model for the pick-up warehouse - VMI warehouse selects the pick-up warehouse that can not only meet the current order requirements but also has some margin in inventory capacity according to the inventory status of each pick-up warehouse and adds it to the optimal route planning.

4. The optimized method for outbound wave based on dynamic route selection according to claim 1, wherein The outbound wave optimization model based on dynamic route selection obtains the optimal routes from the pick-up warehouse to multiple VMI warehouses based on the route selection model for the pick-up warehouse - VMI warehouse, and optimizes the outbound waves for different SKU deliveries.

5. The optimized method for outbound wave based on dynamic route selection according to claim 1, characterized in that The outbound wave optimization model based on dynamic route selection optimizes the outbound waves of one pick-up warehouse at a time, and multiple pick-up warehouses optimize the waves simultaneously according to the time of detecting the order volume and the threshold of the cumulative orders.

6. An outbound wave optimization system based on dynamic route selection, characterized in that, Including: A route selection unit for the pick-up warehouse - VMI warehouse, which is used to obtain the optimal route from the pick-up warehouse to the VMI warehouse based on the route selection model for the pick-up warehouse - VMI warehouse; the route selection model for the pick-up warehouse - VMI warehouse is: Among them, m (m = 1, …, M) is the cargo collection warehouse code, n (n = 1, …, N) is the VMI warehouse code, and i (i ∈ I) is the sku code. represents the unit distance cost of unit raw material i from the m-th cargo collection warehouse to the n-th VMI warehouse, d m,n represents the distance from the m-th cargo collection warehouse to the n-th VMI warehouse, D i is the demand quantity of the i-th sku. is the inventory of the i-th sku in the current m-th cargo collection warehouse. represents the transportation volume of the i-th sku from the m-th cargo collection warehouse to the n-th VMI warehouse. An outbound wave optimization unit based on dynamic route selection, which is used to obtain the optimal outbound wave plan for different SKUs using the outbound wave optimization model based on dynamic route selection; the outbound wave optimization model based on dynamic route selection is: Max: ∑ 1≤i≤n ∑ 1≤j≤n S i,j X i,j ; X i,j = X j,i , for i ∈ I, for j ∈ I; X i,i = 1, for i ∈ I; X i,j = 1, if X i,m + X j,m = 2, for i ∈ I, for j ∈ I, for m ∈ I; Among them, i, j (i, j = 1, …, n) are the sku numbers of the orders dispatched from the VMI warehouse, S i,j is the number of overlapping paths of the i, j-th sku, v i is the volume of the i-th sku, V is the upper limit of the volume for a single transportation, X i,j indicates whether the i, j-th sku enters the same wave.

7. The optimized outbound wave system based on dynamic route selection according to claim 6, wherein The route selection model for the pick-up warehouse - VMI warehouse calculates the route selection that meets the requirements of all SKUs in one order in one VIM warehouse at a time, and n is a fixed value.

8. The optimized outbound wave system based on dynamic route selection according to claim 6, wherein When solving, the route selection model for the pick-up warehouse - VMI warehouse selects the pick-up warehouse that can not only meet the current order requirements but also has some margin in inventory capacity according to the inventory status of each pick-up warehouse and adds it to the optimal route planning.

9. The optimized outbound wave system based on dynamic route selection according to claim 6, characterized in that The outbound wave optimization model based on dynamic route selection obtains the optimal routes from the pick-up warehouse to multiple VMI warehouses based on the route selection model for the pick-up warehouse - VMI warehouse, and optimizes the outbound waves for different SKU deliveries.

10. The optimized outbound wave system based on dynamic route selection according to claim 6, characterized in that The outbound wave optimization model based on dynamic route selection optimizes the outbound waves of one pick-up warehouse at a time, and multiple pick-up warehouses optimize the waves simultaneously according to the time of detecting the order volume and the threshold of the cumulative orders.

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