CN114091994A - Data processing method and device for goods - Google Patents
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Abstract
The invention discloses a data processing method and device for goods. Wherein, the method comprises the following steps: determining a plurality of constants and a plurality of variables in the data of the cargo; according to the constraint relation of goods circulation and the constraint expressions of a plurality of constants and a plurality of variables, wherein the constraint relation is the constraint relation between the constants and the variables; determining an optimization expression of a final optimization target according to a plurality of optimization conditions of cargo circulation, wherein the optimization conditions are the optimization conditions of cargo circulation; and solving according to the variables, the constants, the constraint expressions and the optimization expressions to determine the circulation plan of the goods. The invention solves the technical problems of low efficiency and high cost in the related technology by manually making the cargo circulation plan.
Description
Technical Field
The invention relates to the field of logistics planning, in particular to a data processing method and device for goods.
Background
Factory delivery in the garden needs to be communicated in place before reporting plans of various factories in cooperation, but the various factories cannot make delivery plans on the whole and comprehensively, so that delivery of the factories cannot be influenced, delivery of other factories can be considered, delivery points are reduced on the whole, delivery of dates is centralized, and delivery cost is reduced.
Before the production, each factory needs to distribute the products to corresponding industry and trade according to the order requirement in a specified date, the industry and trade warehouses are distributed nationwide, and factors such as inventory, production plan, vehicle resources and the like are comprehensively considered to make a delivery plan which accords with the park. The process of manual planning includes data export (order data, inventory data, production plan, vehicle resources and the like), planning and result uploading, wherein the planning is carried out in 3 flows, fig. 1 is a schematic diagram of the manual planning flow of the circulation plan of the goods in the prior art, as shown in fig. 1, the planning is the most tedious, dimensions such as customer types, destinations, products, delivery volumes, delivery dates and the like are sorted in thousands of orders, the inventory and the production plan are matched, the single-worker trade delivery time is concentrated as much as possible, the delivery points are few as possible, the single-vehicle load capacity is the largest and the like, and finally only a feasible delivery plan which meets a single factory can be made.
In view of the above problems, no effective solution has been proposed.
Disclosure of Invention
The embodiment of the invention provides a data processing method and device for goods, which are used for at least solving the technical problems of low efficiency and high cost caused by the fact that a goods circulation plan is made manually in the related technology.
According to an aspect of an embodiment of the present invention, there is provided a data processing method for goods, including: determining a plurality of constants and a plurality of variables in the data of the cargo; according to the constraint relation of goods circulation and the constraint expressions of a plurality of constants and a plurality of variables, wherein the constraint relation is the constraint relation between the constants and the variables; determining an optimization expression of a final optimization target according to a plurality of optimization conditions of cargo circulation, wherein the optimization conditions are the optimization conditions of cargo circulation; and solving the constraint expression and the optimization expression according to the variables, the constants, the constraint expression and the optimization expression to determine the circulation plan of the goods.
Optionally, determining a plurality of constants and a plurality of variables in the data of the cargo comprises: and respectively determining constants and variables of different data contents according to the data contents of the goods, wherein the different data contents comprise goods production plan data, goods warehousing data and goods circulation equipment data.
Optionally, the constraint expressions according to the constraint relation of the goods circulation and the plurality of constants and the plurality of variables include; obtaining constants and variables related to the constraint relationship according to the constraint relationship; establishing a constraint expression corresponding to the constraint relation according to the constant and the variable; and determining a plurality of constraint expressions by traversing the constraint relation.
Optionally, determining an optimized expression of the final optimization target according to a plurality of optimization conditions of the cargo circulation includes: obtaining constants and variables related to the optimization conditions according to the optimization conditions; creating an expression of the optimized condition according to the constant and the variable; determining a plurality of expressions by traversing the optimization conditions; and determining the optimized expression of the final optimization target according to the physical quantity corresponding to the final optimization target and the weights corresponding to the expressions.
Optionally, before determining the optimized expression of the final optimization target according to the weight corresponding to the plurality of expressions and according to the physical quantity corresponding to the final optimization target, the method further includes: determining the weights of the expressions according to the extreme value of the physical quantity corresponding to the final optimization target; when the extreme value is a maximum value, the expression is positively correlated with the physical quantity, the weight of the expression is positive, the expression is negatively correlated with the physical quantity, and the weight of the expression is negative; and under the condition that the extreme value is a minimum value, the expression is positively correlated with the physical quantity, the weight of the expression is negative, the expression is negatively correlated with the physical quantity, and the weight of the expression is positive.
Optionally, solving the constraint expression and the optimized expression according to the variables, the constants, the constraint expression and the optimized expression, and determining the circulation plan of the goods includes: generating an input file of a solver according to the variables, the constants, the constraint expressions and the optimization expressions; inputting the input file into a mixed integer solver, and outputting an optimal solution of the variables of the optimized expression by the mixed integer solver; and determining the circulation plan of the goods according to the optimal solution of the variables.
Optionally, the determining the circulation plan of the cargo according to the optimal solution of the variables includes: determining a delivery plan of the goods according to the optimal solution of the variables of the goods production plan data of the goods; determining a transfer plan of the goods according to the optimal solution of the variables of the goods warehousing data of the goods; and determining a distribution plan of the cargo circulation equipment of the cargo according to the optimal solution of the variables of the cargo circulation equipment data of the cargo.
According to another aspect of the embodiments of the present invention, there is also provided a data processing apparatus for goods, including: the system comprises a first determination module, a second determination module and a control module, wherein the first determination module is used for determining a plurality of constants and a plurality of variables in data of cargoes; the second determining module is used for determining constraint relations of goods circulation and constraint expressions of a plurality of constants and a plurality of variables, wherein the constraint relations are constraint relations between the constants and the variables; the third determining module is used for determining an optimization expression of a final optimization target according to a plurality of optimization conditions of cargo circulation, wherein the optimization conditions are the optimization conditions of the cargo circulation; and the fourth determining module is used for solving according to the variables, the constants, the constraint expressions and the optimized expressions to determine the circulation plan of the goods.
According to another aspect of the embodiments of the present invention, there is further provided a processor, wherein the processor is configured to run a program, and when the program is run, the method for processing data of goods according to any one of the above-mentioned embodiments is performed.
According to another aspect of the embodiments of the present invention, there is also provided a computer storage medium, where the computer storage medium includes a stored program, and when the program runs, the apparatus on which the computer storage medium is located is controlled to execute the data processing method for goods described in any one of the above.
In an embodiment of the invention, a plurality of constants and a plurality of variables in the data for determining the cargo are adopted; according to the constraint relation of goods circulation and the constraint expressions of a plurality of constants and a plurality of variables, wherein the constraint relation is the constraint relation between the constants and the variables; determining an optimization expression of a final optimization target according to a plurality of optimization conditions of cargo circulation, wherein the optimization conditions are the optimization conditions of cargo circulation; the method comprises the steps of solving according to variables and constants, constraint expressions and optimization expressions, determining circulation plans of goods, determining the constants and the variables in goods data, determining a plurality of variables according to constraint relations and target conditions, and further generating the goods circulation plans according to the variables, so that the purpose of automatically generating the goods circulation plans according to the data of the goods is achieved, the generation efficiency of the goods circulation plans is improved, the generation cost of the goods circulation plans is reduced, the technical effect that the plan making efficiency is low manually is avoided, and the technical problems that the goods circulation plans are made manually in the related technology, the efficiency is low, and the cost is high are solved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the invention without limiting the invention. In the drawings:
FIG. 1 is a schematic illustration of a manual process for planning the circulation of goods according to the prior art;
fig. 2 is a flowchart of a data processing method of goods according to embodiment 1 of the present invention;
fig. 3 is a flowchart of another cargo data processing method according to embodiment 1 of the present invention;
FIG. 4 is a schematic diagram of a warehousing network of goods according to embodiment 2 of the present invention;
fig. 5 is a schematic diagram of a data processing device for goods according to embodiment 3 of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Example 1
In accordance with an embodiment of the present invention, there is provided a method embodiment of a data processing method for goods, it is noted that the steps illustrated in the flowchart of the drawings may be performed in a computer system such as a set of computer executable instructions, and that while a logical order is illustrated in the flowchart, in some cases the steps illustrated or described may be performed in an order different than here.
Fig. 2 is a flowchart of a data processing method for goods according to embodiment 1 of the present invention, as shown in fig. 2, the method includes the following steps:
step S202, determining a plurality of constants and a plurality of variables in the data of the goods;
step S204, according to the constraint relation of goods circulation and the constraint expressions of a plurality of constants and a plurality of variables, wherein the constraint relation is the constraint relation between the constants and the variables;
step S206, determining an optimization expression of a final optimization target according to a plurality of optimization conditions of cargo circulation, wherein the optimization conditions are the optimization conditions of the cargo circulation;
and S208, solving according to the variables, the constants, the constraint expressions and the optimized expressions to determine the circulation plan of the goods.
Through the steps, a plurality of constants and a plurality of variables in the data for determining the goods are adopted; determining the range of a plurality of variables according to the constraint relation of cargo circulation and a plurality of constants, wherein the constraint relation is the constraint relation between the constants and the variables; determining extreme values of a plurality of variables in the variable range according to target conditions of cargo circulation, wherein the target conditions are the target conditions of variable values; according to the extreme value of a plurality of variables, the mode of determining the circulation plan of the goods is determined, constant and variable in goods data are determined, a plurality of variables are determined according to the constraint relation and the target condition, then the goods circulation plan is generated according to the variables, and the purpose of automatically generating the goods circulation plan according to the data of the goods is achieved, so that the generation efficiency of the goods circulation plan is improved, the generation cost of the goods circulation plan is reduced, the technical effect that the plan is artificially made with low efficiency is avoided, and the technical problems that the goods circulation plan is manually made in the related technology, the efficiency is low, and the cost is high are solved.
The execution main body of the steps can be a computer terminal, a server terminal and other terminal equipment with computing capability, and the terminal equipment can be arranged in a goods dispatching center or a cloud end in remote communication with the goods dispatching center. And the cargo data are solved by carrying a solver. The solver may be a mixed integer solver MIP.
The data of the goods may be data of various aspects involved in the circulation of the goods, for example, may include production data of a manufacturer of the goods, including a factory code, a product code, a production quantity, etc., storage data of a storage warehouse of the goods, including a warehouse position, a warehouse storage quantity, a balance, etc., data of a circulation tool of the goods, including an available time of the circulation tool, an available quantity of the circulation tool, a loading capacity of the circulation tool, a code of the circulation tool, a circulation time of the circulation tool, etc., and data of a circulation destination of the goods, including a circulation order, an order code, etc.
The data of the goods are data which can be used in goods circulation, and in addition, some parameters can be coded conveniently for operation, such as coding of circulation tools, factory coding, warehouse coding and the like, so as to show differences, and convenience is brought to processing in the subsequent operation process. The quantities which are not controlled and changed by the dispatcher are constant, such as the codes, the models of the circulation tools, the capacity, the available quantity and the like, the production capacity of the factory, the position of the warehouse, the storage quantity, the balance quantity and the like, cannot be modified manually, and a specific goods circulation plan needs to be made according to the constant. Variables are variables for the quantities that can be changed, such as the number of distribution tools, the time of use of the distribution tools, the amount of allocation of the warehouse, etc.
In one embodiment, for a delivery plan for the circulation of goods, the following constants are set: factory code F ∈ [0, 1, … ]](ii) a Calendar code T e [0, 1, …, Delay ∈](ii) a Warehouse code W e [0, 1, …](ii) a Product code Z epsilon [0, 1, …](ii) a Order code I e [0, 1, … ]](ii) a Industry and trade code G e [0, 1, … ∈](ii) a Model V is the [0, 1, … ]](ii) a Order detail Nf，i，z，gWherein F belongs to F, I belongs to I, and Z belongs to Z, which represents the number of the I orders of the F factory as the Z models sent to the g industry and trade; warehouse balance inventory amount Mf，t，z，wIndicating the amount of production until day t-1; yield of Napsf，t，zDenotes f plant t day z modelThe number of the line-in T banks; vehicle bearing capacity AvWherein V belongs to V and represents the effective bearing volume and load of the V vehicle type; number of vehicles NVv，tRepresenting the available number of v vehicle types at t aim; vehicle code Vidv，t∈[0，1，…，NVv，t]. And the following variables: order status Sf，i，t，z，w∈[0，1]Wherein F belongs to F, I belongs to I, T belongs to T, Z belongs to Z, W belongs to W, and I orders are delivered from warehouse W in T days; adjusting amount Ndf，t，z，wThe z-type dial quantity of the w warehouse is represented, wherein the dial-out is a negative value, and the dial-in is a positive value; vehicle use state Sv，t，k∈[0，1]Where k ∈ Vid _ (v, t); warehouse goods picking state Ss for industry and tradeg，w∈[0，1]Whether the order sent to the g trade is delivered in a w warehouse or not; goods picking state St of industry and trade on a certain dayg，t∈[0，1]I.e. whether the order sent to g trade is to pick up goods on day t.
For the constraint relation between the variable and the constant, a constraint expression is determined, and the constraint relation can be understood as the relation between the variable and the constant under the objective condition that the goods circulation must meet, for example, the daily available goods amount of the factory does not exceed the actual available goods amount. For the factory warehouse, the available amount is the sum of the number of products scheduled for production on the day, the inventory and the allocation amount, wherein the allocation amount comprises the allocation amount of other warehouses and the balance allocation amount allocated to other warehouses; for the external warehouse, the available amount is the sum of the inventory and the allocation amount on the same day. Its constraint expression can be represented by:
for another example, an order for a particular industry trade may not have its total pick-up on a single vehicle exceeding its maximum capacity, assuming that the single vehicle is only for the single industry trade. The bearing capacity refers to the effective bearing volume and load of the vehicle type. The goods lifting amount can be converted from the product quantity, the size and the weight. Its constraint expression can be represented by: sigmat(Sf，i，t，z，w×Nf，i，z，g)≤Av，t×Sv，t，k. Restraint switchThe method comprises the following steps: factory products may only be dialed to a specified portion of the warehouse. Suppose there is f factory will not dial to w warehouse. Its constraint expression can be represented by: sigmaz Ndf，t，z，w0. The constraint relationship is as follows: the total number of the cars in a single day does not exceed the number of the cars available in a single day. Its constraint expression can be represented by: sigmak Sv，t，k×Vidv，t≤NVv，t. The constraint relationship is as follows: a single order can only be shipped in a single-day order warehouse. Its constraint relationship can be represented by the following equation: sigmai(Sf，i，t，z，w)＝＝1。
The above-mentioned optimization condition can be understood as a condition under which the variable is more optimized in value. For example, the optimization condition may be: the order is shipped as early as possible. Obtaining delta t according to the difference between the planning date t and the latest delivery date of the order, wherein delta t is more than or equal to 0 and represents delivery in advance, K0Less than 0; deltat < 0 denotes delivery late, K1Is greater than 0; when t is Delay, K denotes an order extension2＞＞K1. The expression can be represented by the following formula:
the optimization conditions can also be as follows: the total dialing amount is as small as possible. Due to the fact that corresponding cost can be generated by dialing, the maximum dialing amount can be added in the constraint relation, and the target can be weighted, so that flexible and controllable dialing can be guaranteed. Can be represented by the following formula: cost02 ═ Σf，t，z，wNdf，t，z，w×K3. The optimization conditions may be: the total number of vehicles per day is as small as possible. The expression can be represented by the following formula: cost03 ═ Σv，t，kSv，t，k×Vidv，t×K4. The optimization conditions may be: the total number of picking points of single-industry trade is as small as possible. Wherein Ssg，wBy Sf，i，t，z，wObtained by combining with the constraint of the large M method, which is not described herein in detail; the expression can be represented by the following formula: cost04 ═ Σg，w Ssg，w×K5. The optimization conditions may be: the total number of the shipments of a single worker is as small as possible. Wherein Stg，tBy Sf，i，t，z，wCombination is bigThe M method is obtained through constraint and is not described herein; the expression can be represented by the following formula: cost05 ═ Σg，t Stg，t×K6。
The optimization expression of the final optimization target may be determined by expressions corresponding to the optimization conditions, for example, in this embodiment, the final optimization target may be the minimum overall cost, and the final optimization expression may be referred to by the following formula: costallThe cost01+ cost02+ cost03+ cost04+ cost05, and cost01-05 are expressions of the above-described optimization conditions, respectively. In an embodiment, the expression corresponding to the optimization condition may be weighted according to the influence degree of different optimization conditions on the final optimization target. In addition, to achieve the target final optimization goal, other quantities of operations may be added to the expression of the optimization condition, such as the expression is the total number of vehicles per day, which corresponds to the cost, and the expression may be multiplied by the transportation cost of each vehicle.
Obtaining the constants and variables of the data of the goods, the constraint relation between the constants and the variables and the optimization conditions of the variables, inputting the constants and the variables into a solver to solve, obtaining the final optimal solution of the variables, namely the values of the variables, and generating a specific goods circulation plan according to the values of the variables.
Fig. 3 is a flowchart of another cargo data processing method according to embodiment 1 of the present invention, and as shown in fig. 3, optionally, step S202, where determining a plurality of constants and a plurality of variables in the cargo data includes: step S2022 determines constants and variables of different data contents according to the data contents of the goods, where the different data contents include goods production plan data, goods warehousing data, and goods circulation device data.
The data of the goods may be data of multiple dimensions, such as production data of the manufacturer, storage data of a storage warehouse of the goods, data of a distribution tool of the goods, and data of a distribution destination of the goods. For data of different dimensions, its constants and variables can be determined separately. It should be noted that, when the constants and the variables are determined, the determination may be performed according to requirements, and not all the data items involved are set as the constants or the variables, and of course, the more the constants and the variables are set, the more accurate and reasonable the obtained logistics plan is, but the slower the solving speed is. Conversely, the fewer the constants and variables are set, the lower the accuracy of the obtained logistics plan is, but the faster the solving speed is, the constants and variables related to the constraints can be set according to requirements when in use. Therefore, different data providers can set the constants and the variables by themselves, the set constants and the set variables are transmitted to a terminal for operation and execution, people of all parties do not need to be gathered and determined, people with knowledge about data of all parties do not need to be arranged, cost for defining the data variables and the constants is effectively reduced, and efficiency is improved.
Optionally, step S204 includes, according to the constraint relationship of the goods circulation and the constraint expressions of the plurality of constants and the plurality of variables; step S2042, obtaining constants and variables related to the constraint relationship according to the constraint relationship; step S2044, establishing a constraint expression corresponding to the constraint relation according to the constant and the variable; step S2046, a plurality of constraint expressions are determined by traversing the constraint relationship.
The constraint relation can be set artificially, and in the process of cargo transportation, certain irreparable objective rules exist, so that the normal operation of a cargo circulation plan can be ensured under the condition of meeting the rules. The constraint condition may be set manually, and specifically, before the step S204, according to the constraint relationship of the circulation of the goods and the constraint expressions of the plurality of constants and the plurality of variables, the method further includes: and receiving the input constraint relation, and storing the constraint relation. The method can also be used for directly calling, and can store the previously written constraint conditions so as to directly call in the following.
Optionally, in step S206, determining an optimized expression of a final optimization target according to a plurality of optimization conditions of cargo circulation includes: step S2062, obtaining constants and variables related to the optimization conditions according to the optimization conditions; step S2064, establishing an expression of the optimization condition according to the constant and the variable; step S2066, determining a plurality of expressions through traversing optimization conditions; step S2068, determining the optimized expression of the final optimization target according to the physical quantity corresponding to the final optimization target and the weights corresponding to the expressions.
The optimization conditions are similar to the constraint conditions, the optimization conditions are used for setting the value direction of the variables which tend to be more according to the requirements, and the values are taken according to the optimization conditions during solving, so that various requirements of various orders can be met, including the lowest cost, the fastest speed, the most reliable and the like. The optimization conditions can also be set manually, or the previously written optimization conditions can be directly called.
Optionally, in step S2068, before determining the optimized expression of the final optimization target according to the weight corresponding to the multiple expressions and the physical quantity corresponding to the final optimization target, the method further includes: step S2060, determining the weights of a plurality of expressions according to the extreme value of the physical quantity corresponding to the final optimization target; under the condition that the extreme value is the maximum value, the expression is positively correlated with the physical quantity, the weight of the expression is positive and negatively correlated with the physical quantity, and the weight of the expression is negative; when the extreme value is a minimum value, the expression is positively correlated with the physical quantity, the weight of the expression is negative, the expression is negatively correlated with the physical quantity, and the weight of the expression is positive.
When setting the weight, determining the weight of a plurality of expressions according to the extreme value of the physical quantity corresponding to the final optimization target; under the condition that the extreme value is maximum, if the expression of the optimization condition is positively correlated with the physical quantity, the weight of the expression is positive, and if the expression of the optimization condition is negatively correlated with the physical quantity, the weight of the expression is negative; under the condition that the extreme value is the minimum value, if the expression of the optimization condition is positively correlated with the physical quantity, the weight of the expression is negative, and if the expression of the optimization condition is negatively correlated with the physical quantity, the weight of the expression is positive so as to reflect the influence mode of the expression on the physical quantity of the final optimization target.
Optionally, in step S208, solving according to the variable and the constant, the constraint expression and the optimized expression, and determining the circulation plan of the goods includes: step S2082, generating an input file of the solver according to the variable, the constant, the constraint expression and the optimization expression, where the input file may be a file in a predetermined format input by the hybrid solver. Step S2084, inputting the input file into a mixed integer solver, and outputting an optimal solution of variables of the optimized expression by the mixed integer solver; step S2086, determining a circulation plan of the cargo according to the optimal solution of the variables.
Specifically, the physical quantity corresponding to the final optimization target is the overall cost, the extreme value is the minimum value of the overall cost, and step S2086, according to the optimal solution of the variables, determining the circulation plan of the cargo includes: step S20862, determining a delivery plan of the goods according to the optimal solution of the variables of the goods production plan data of the goods; step S20864, determining a transfer plan of the goods according to the optimal solution of the variables of the goods warehousing data of the goods; step S20866, determining a distribution plan of the cargo distribution device of the cargo according to the optimal solution of the variables of the cargo distribution device data of the cargo.
In the process of goods circulation, cooperation of multiple parties is needed, management of the multiple parties is different, so that plan determination of different dimensions is needed according to data of different dimensions, and the Yibaozhen goods circulation plan can operate according to the plan. The accuracy and the stability of the cargo circulation plan are further ensured.
Example 2
This embodiment 2 provides a collaborative calculation method for campus delivery based on MIP. Under the prerequisite of guaranteeing each factory delivery period, can also accomplish in coordination with the shipment of other factories, the point of delivery is concentrated on the whole, concentrated shipment date and then reduce the logistics cost. In the related technology, under the conditions of large data scale and many influence factors of goods, the NP-hard problem is easy to occur in the derivation of the fruit relation, so that optimization cannot be performed or modeling difficulty is extremely high, and solution cannot be performed. According to the invention, an operation optimization theory is adopted, a constraint relation and an optimization target are combed for the existing problems, and then the problems are solved, so that the modeling difficulty is greatly reduced, the configuration is flexible, and the global optimal solution can be obtained.
Fig. 4 is a schematic diagram of a warehouse network of goods according to embodiment 2 of the present invention, as shown in fig. 4, a campus includes a plurality of factories, offline products of the factories are stored in warehouses, and the warehouses are divided into 2 types of factory warehouses and 2 types of external warehouses, wherein the factory warehouses only store products of the factory, and the external warehouses can store products of a plurality of factories. In order to effectively improve the garden vehicle allocation and delivery efficiency, the inventory, production plan, orders and garden vehicle resource effective cooperation of various factories are considered, the order sent to the same trade needs to be picked up in a single warehouse as much as possible, the whole vehicle is packed in the single warehouse as much as possible, the goods must be picked up in a plurality of warehouses, the delivery date is concentrated, and the purposes of improving the delivery efficiency, reducing the vehicle resource input and the vehicle waiting time are achieved.
The collaborative campus delivery plan is optimized based on the MIP (mixed integer solution) algorithm principle, so that the system can be 'in consideration of the whole bureau', not only the delivery plan of each factory is met, but also the delivery efficiency of the whole campus is improved. The main process comprises constant and variable factors of campus delivery collaboration, constraint relation, optimization target combing and optimization solving of 4 parts.
1. The key influencing factors are as follows:
1.1 Key constants are as follows:
the factory code F ∈ [0, 1, … ];
calendar code T is from [0, 1, …, Delay ];
the warehouse code W is equal to [0, 1, … ];
the product code Z belongs to [0, 1, … ];
order code I belongs to [0, 1, … ];
the trade code G belongs to [0, 1, … ];
the vehicle type V belongs to [0, 1, … ];
order detail Nf，i，z，gWherein F belongs to F, I belongs to I, and Z belongs to Z, which represents the number of the I orders of the F factory as the Z models sent to the g industry and trade;
warehouse balance inventory amount Mf，t，z，wIndicating the amount of production until day t-1;
yield of Napsf，t，zThe number of the model z of f factory t days which is offline into the factory warehouse is represented;
vehicle bearing capacity AvWherein V belongs to V and represents the effective bearing volume and load of the V vehicle type;
number of vehicles NVv，tRepresenting the available number of the v vehicle types on the t day;
vehicle code Vidv，t∈[0，1，…，NVv，t]；
1.2 Key variables are as follows:
order status Sf，i，t，z，w∈[0，1]Wherein F belongs to F, I belongs to I, T belongs to T, Z belongs to Z, W belongs to W, and I orders are delivered from warehouse W in T days;
adjusting amount Ndf，t，z，wThe z-type dial quantity of the w warehouse is represented, wherein the dial-out is a negative value, and the dial-in is a positive value;
vehicle use state Sv，t，k∈[0，1]Where k ∈ Vid _ (v, t);
warehouse goods picking state Ss for industry and tradeg，w∈[0，1]Whether the order sent to the g trade is delivered in a w warehouse or not;
goods picking state St of industry and trade on a certain dayg，t∈[0，1]Whether the order sent to the g trade is to pick up goods on t days or not;
2. the constraint relationship refers to the established shipping criteria and objective limiting factors in the collaborative shipping process, and the key (and not limited) constraint relationship is as follows:
2.1 the daily availability of the plant does not exceed the actual availability. For the factory warehouse, the available amount is the sum of the number of products scheduled for production on the day, the inventory and the allocation amount, wherein the allocation amount comprises the allocation amount of other warehouses and the balance allocation amount allocated to other warehouses; for the external warehouse, the available amount is the sum of the inventory and the allocation amount on the same day.
2.2 the total delivery of orders to a particular trade does not exceed its maximum capacity on a single vehicle, assuming that the single vehicle is only to the single trade. The bearing capacity refers to the effective bearing volume and load of the vehicle type. The goods lifting amount can be converted from the number, the size and the weight of the products.
2.3 factory products can only be dialed to a specified portion of the warehouse. Suppose there is f factory will not dial to w warehouse.
2.4 Total number of cycles per day does not exceed the number of available cycles per day.
2.5 Individual orders can only be shipped in a single daily warehouse.
3. The optimization target is an expression designed on the premise of meeting constraint conditions, and an extreme value is taken on the expression.
The expressions are designed based on business objectives, and key (and not limited) expressions are as follows:
3.1 order delivery as early as possible. Obtaining delta t according to the difference between the planning date t and the latest delivery date of the order, wherein delta t is more than or equal to 0 and represents delivery in advance, K0Less than 0; deltat < 0 denotes delivery late, K1Is greater than 0; when t is Delay, K denotes an order extension2＞＞K1。
3.2 the total transfer amount is as small as possible. Due to the fact that corresponding cost can be generated by dialing, the maximum dialing amount can be added in the constraint relation, and the target can be weighted, so that flexible and controllable dialing can be guaranteed.
3.3 Total number of vehicles per day is as small as possible.
3.4 the total number of picking points of single-job trade is as small as possible. Wherein Ssg，wBy Sf，i，t，z，wObtained by combining with the constraint of the large M method, which is not described herein in detail;
3.5 Single industry trade may have as few total dates to send out as possible. Wherein Stg，tBy Sf，i，t，z，wObtained by combining with the constraint of the large M method, which is not described herein in detail;
4. optimizing and solving, summarizing each optimization target into an overall cost, and taking costallThe minimum value is just required. In addition, each single optimization target can be normalized, and the weight can also be designed into an expression according to the dependent variable, which is not described herein.
costall＝cost01+cost02+cost03+cost04+cost05
After optimization calculation, a delivery plan, a transfer plan and a vehicle distribution plan of each factory can be directly obtained, and are respectively shown in tables 1 to 3.
TABLE 1 example factory shipment results
TABLE 2 factory Dial results example
TABLE 3 vehicle Allocation results example
The key point of the embodiment is that the MIP algorithm is utilized to synthesize production plans, stocks and vehicle resources of each factory in the park, the optimal combination of the resources is planned in a coordinated mode, the total vehicle-warehouse number and the trade-delivery date number are reduced, the transportation cost is effectively reduced, and the warehouse stock-keeping efficiency is improved. In addition, whether the coordination scene of the campus delivery of the constraint and optimization targets such as allocation is involved or not, the coordination scene can also be solved through the modeling method set forth by the invention, and therefore, the coordination scene is also within the protection scope of the invention.
The solution of the present embodiment has time benefits: the system replaces manpower, the complexity of offline communication and manual planning is effectively avoided, a delivery plan, a transfer plan and a vehicle allocation plan can be directly calculated through a modeling method, and the working efficiency is greatly improved; also has economic benefits: the problem of each factory shipper can only be absorbed in oneself, be difficult to macroscopic resources collaborative is solved, only whole consideration just can obtain best stock and join in marriage the car combination, improves the stock precision, reduces vehicle latency, greatly reduced logistics cost.
Example 3
Fig. 5 is a schematic diagram of a data processing device for goods according to embodiment 3 of the present invention, and as shown in fig. 5, according to another aspect of the embodiment of the present invention, there is further provided a data processing device for goods, including: a first determination module 52, a second determination module 54, a third determination module 56, and a fourth determination module 58, which are described in detail below.
A first determining module 52 for determining a plurality of constants and a plurality of variables in the data of the cargo; a second determining module 54, connected to the first determining module 52, for determining constraint relationships between the goods circulation and constraint expressions of a plurality of constants and a plurality of variables, where the constraint relationships are constraint relationships between the constants and the variables; a third determining module 56, connected to the second determining module 54, configured to determine an optimized expression of a final optimization target according to a plurality of optimization conditions of cargo distribution, where the optimization conditions are optimization conditions of cargo distribution; and a fourth determining module 58, connected to the third determining module 56, for solving the constraint expression and the optimized expression according to the variables and constants, and determining the distribution plan of the goods.
By the device, a plurality of constants and a plurality of variables in the data of the cargo are determined by the first determining module 52; the second determining module 54 determines constraint relationships between the constants and the variables according to the constraint relationships of the circulation of the goods and the constraint expressions of the constants and the variables; the third determining module 56 determines an optimized expression of the final optimization target according to a plurality of optimization conditions of the cargo circulation, wherein the optimization conditions are the optimization conditions of the cargo circulation; the fourth determining module 58 determines the circulation plan of the goods by determining the constants and variables in the data of the goods, determining a plurality of variables according to the constraint relation and the target condition, and then generating the circulation plan of the goods according to the variables, thereby achieving the purpose of automatically generating the circulation plan of the goods according to the data of the goods, thereby improving the generation efficiency of the circulation plan of the goods, reducing the generation cost of the circulation plan of the goods, avoiding the technical effect of low efficiency of manually making the circulation plan, and further solving the technical problems of low efficiency and high cost of manually making the circulation plan of the goods in the related art.
As an optional implementation, the first determining module includes: the first determining unit is used for respectively determining constants and variables of different data contents according to the data contents of the goods, wherein the different data contents comprise goods production plan data, goods warehousing data and goods circulation equipment data.
As an optional implementation, the method further includes: the receiving module is used for receiving the input constraint relation and storing the constraint relation; the second determination module comprises; the first obtaining unit is used for obtaining constants and variables related to the constraint relation according to the constraint relation; the establishing unit is used for establishing a constraint expression corresponding to the constraint relation according to the constant and the variable; and the first traversal unit is used for determining a plurality of constraint expressions by traversing the constraint relation.
As an optional implementation, the third determining module includes: the second acquisition unit is used for acquiring constants and variables related to the optimization conditions according to the optimization conditions; a creating unit configured to create an expression of the optimized condition based on the constant and the variable; the second traversal unit is used for determining a plurality of expressions through traversal optimization conditions; and the weighting unit is used for determining the optimized expression of the final optimization target according to the physical quantity corresponding to the final optimization target and the weights corresponding to the expressions.
As an optional implementation manner, the third determining module further includes: the weight unit is used for determining the weights of the expressions according to the extreme value of the physical quantity corresponding to the final optimization target; under the condition that the extreme value is the maximum value, the expression is positively correlated with the physical quantity, the weight of the expression is positive and negatively correlated with the physical quantity, and the weight of the expression is negative; when the extreme value is a minimum value, the expression is positively correlated with the physical quantity, the weight of the expression is negative, the expression is negatively correlated with the physical quantity, and the weight of the expression is positive.
As an optional implementation, the fourth determining module includes: the generating unit is used for generating an input file of the solver according to the variables, the constants, the constraint expressions and the optimized expressions; the input unit is used for inputting the input file into the mixed integer solver, and the mixed integer solver outputs the optimal solution of the variables of the optimized expression; and the determining unit is used for determining the circulation plan of the goods according to the optimal solution of the variables.
As an alternative implementation, the physical quantity corresponding to the final optimization target is an overall cost, the extreme value is a minimum value of the overall cost, and the determining unit includes: the first determining subunit is used for determining a delivery plan of the goods according to the optimal solution of the variables of the goods production plan data of the goods; the second determining subunit is used for determining a transfer plan of the goods according to the optimal solution of the variables of the goods warehousing data of the goods; and the third determining subunit is used for determining the distribution plan of the cargo circulation equipment of the cargo according to the optimal solution of the variables of the cargo circulation equipment data of the cargo.
Example 4
According to another aspect of the embodiments of the present invention, there is also provided a processor configured to execute a program, where the program executes the following steps.
Determining a plurality of constants and a plurality of variables in the data of the cargo; determining the range of a plurality of variables according to the constraint relation of cargo circulation and a plurality of constants, wherein the constraint relation is the constraint relation between the constants and the variables; determining extreme values of a plurality of variables in the variable range according to target conditions of cargo circulation, wherein the target conditions are the target conditions of variable values; and determining a circulation plan of the goods according to the extreme values of the plurality of variables.
As an alternative embodiment, determining a plurality of constants and a plurality of variables in the data for the good includes: and respectively determining constants and variables of different data contents according to the data contents of the goods, wherein the different data contents comprise goods production plan data, goods warehousing data and goods circulation equipment data.
As an optional implementation, before the constraint relation according to the circulation of the goods and the constraint expression of the plurality of constants and the plurality of variables, the method further includes: receiving an input constraint relation, and storing the constraint relation; constraint expressions which are based on the constraint relation of the goods circulation and a plurality of constants and a plurality of variables comprise; obtaining constants and variables related to the constraint relationship according to the constraint relationship; establishing a constraint expression corresponding to the constraint relation according to the constant and the variable; and determining a plurality of constraint expressions by traversing the constraint relation.
As an alternative embodiment, determining the optimization expression of the final optimization objective according to the plurality of optimization conditions of the goods circulation includes: obtaining constants and variables related to the optimization conditions according to the optimization conditions; creating an expression of an optimization condition according to the constant and the variable; determining a plurality of expressions through traversing optimization conditions; and determining the optimized expression of the final optimization target according to the physical quantity corresponding to the final optimization target and the weights corresponding to the expressions.
As an optional implementation manner, before determining the optimized expression of the final optimization target according to the weight corresponding to the multiple expressions and the physical quantity corresponding to the final optimization target, the method further includes: determining the weights of the expressions according to the extreme value of the physical quantity corresponding to the final optimization target; under the condition that the extreme value is the maximum value, the expression is positively correlated with the physical quantity, the weight of the expression is positive and negatively correlated with the physical quantity, and the weight of the expression is negative; when the extreme value is a minimum value, the expression is positively correlated with the physical quantity, the weight of the expression is negative, the expression is negatively correlated with the physical quantity, and the weight of the expression is positive.
As an alternative embodiment, solving the constraint expression and the optimization expression according to the variables and the constants, and determining the circulation plan of the goods includes: generating an input file of a solver according to the variables, the constants, the constraint expressions and the optimization expressions; inputting the input file into a mixed integer solver, and outputting an optimal solution of variables of the optimized expression by the mixed integer solver; and determining a circulation plan of the goods according to the optimal solution of the variables.
As an alternative implementation, the physical quantity corresponding to the final optimization goal is an overall cost, the extreme value is a minimum value of the overall cost, and determining the circulation plan of the goods according to the optimal solution of the variables includes: determining a delivery plan of the goods according to the optimal solution of the variables of the goods production plan data of the goods; determining a transfer plan of the goods according to the optimal solution of the variables of the goods warehousing data of the goods; determining a distribution plan of the cargo distribution equipment of the cargo according to the optimal solution of the variables of the cargo distribution equipment data of the cargo.
Example 5
According to another aspect of the embodiments of the present invention, there is also provided a computer storage medium including a stored program, wherein when the program is executed, an apparatus in which the computer storage medium is controlled performs the following steps.
Determining a plurality of constants and a plurality of variables in the data of the cargo; determining the range of a plurality of variables according to the constraint relation of cargo circulation and a plurality of constants, wherein the constraint relation is the constraint relation between the constants and the variables; determining extreme values of a plurality of variables in the variable range according to target conditions of cargo circulation, wherein the target conditions are the target conditions of variable values; and determining a circulation plan of the goods according to the extreme values of the plurality of variables.
As an alternative embodiment, determining a plurality of constants and a plurality of variables in the data for the good includes: and respectively determining constants and variables of different data contents according to the data contents of the goods, wherein the different data contents comprise goods production plan data, goods warehousing data and goods circulation equipment data.
As an optional implementation, before the constraint relation according to the circulation of the goods and the constraint expression of the plurality of constants and the plurality of variables, the method further includes: receiving an input constraint relation, and storing the constraint relation; constraint expressions which are based on the constraint relation of the goods circulation and a plurality of constants and a plurality of variables comprise; obtaining constants and variables related to the constraint relationship according to the constraint relationship; establishing a constraint expression corresponding to the constraint relation according to the constant and the variable; and determining a plurality of constraint expressions by traversing the constraint relation.
As an alternative embodiment, determining the optimization expression of the final optimization objective according to the plurality of optimization conditions of the goods circulation includes: obtaining constants and variables related to the optimization conditions according to the optimization conditions; creating an expression of an optimization condition according to the constant and the variable; determining a plurality of expressions through traversing optimization conditions; and determining the optimized expression of the final optimization target according to the physical quantity corresponding to the final optimization target and the weights corresponding to the expressions.
As an optional implementation manner, before determining the optimized expression of the final optimization target according to the weight corresponding to the multiple expressions and the physical quantity corresponding to the final optimization target, the method further includes: determining the weights of the expressions according to the extreme value of the physical quantity corresponding to the final optimization target; under the condition that the extreme value is the maximum value, the expression is positively correlated with the physical quantity, the weight of the expression is positive and negatively correlated with the physical quantity, and the weight of the expression is negative; when the extreme value is a minimum value, the expression is positively correlated with the physical quantity, the weight of the expression is negative, the expression is negatively correlated with the physical quantity, and the weight of the expression is positive.
As an alternative embodiment, solving the constraint expression and the optimization expression according to the variables and the constants, and determining the circulation plan of the goods includes: generating an input file of a solver according to the variables, the constants, the constraint expressions and the optimization expressions; inputting the input file into a mixed integer solver, and outputting an optimal solution of variables of the optimized expression by the mixed integer solver; and determining a circulation plan of the goods according to the optimal solution of the variables.
As an alternative implementation, the physical quantity corresponding to the final optimization goal is an overall cost, the extreme value is a minimum value of the overall cost, and determining the circulation plan of the goods according to the optimal solution of the variables includes: determining a delivery plan of the goods according to the optimal solution of the variables of the goods production plan data of the goods; determining a transfer plan of the goods according to the optimal solution of the variables of the goods warehousing data of the goods; determining a distribution plan of the cargo distribution equipment of the cargo according to the optimal solution of the variables of the cargo distribution equipment data of the cargo.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
In the above embodiments of the present invention, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed technology can be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units may be a logical division, and in actual implementation, there may be another division, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, units or modules, and may be in an electrical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the principle of the present invention, and these modifications and decorations should also be regarded as the protection scope of the present invention.
Claims (10)
1. A data processing method for goods, comprising:
determining a plurality of constants and a plurality of variables in the data of the cargo;
according to the constraint relation of goods circulation and the constraint expressions of a plurality of constants and a plurality of variables, wherein the constraint relation is the constraint relation between the constants and the variables;
determining an optimization expression of a final optimization target according to a plurality of optimization conditions of cargo circulation, wherein the optimization conditions are the optimization conditions of cargo circulation;
and solving the constraint expression and the optimization expression according to the variables, the constants, the constraint expression and the optimization expression to determine the circulation plan of the goods.
2. The method of claim 1, wherein determining a plurality of constants and a plurality of variables in the data for the good comprises:
and respectively determining constants and variables of different data contents according to the data contents of the goods, wherein the different data contents comprise goods production plan data, goods warehousing data and goods circulation equipment data.
3. The method of claim 1, wherein the constraint expressions based on the constraint relationship of the circulation of the goods and the plurality of constants and the plurality of variables comprise;
obtaining constants and variables related to the constraint relationship according to the constraint relationship;
establishing a constraint expression corresponding to the constraint relation according to the constant and the variable;
and determining a plurality of constraint expressions by traversing the constraint relation.
4. The method of claim 3, wherein determining the optimized expression for the final optimization objective based on the plurality of optimization conditions for the circulation of the good comprises:
obtaining constants and variables related to the optimization conditions according to the optimization conditions;
creating an expression of the optimized condition according to the constant and the variable;
determining a plurality of expressions by traversing the optimization conditions;
and determining the optimized expression of the final optimization target according to the physical quantity corresponding to the final optimization target and the weights corresponding to the expressions.
5. The method according to claim 4, wherein before determining the optimized expression of the final optimization goal according to the weight corresponding to the plurality of expressions and the physical quantity corresponding to the final optimization goal, the method further comprises:
determining the weights of the expressions according to the extreme value of the physical quantity corresponding to the final optimization target;
when the extreme value is a maximum value, the expression is positively correlated with the physical quantity, the weight of the expression is positive, the expression is negatively correlated with the physical quantity, and the weight of the expression is negative;
and under the condition that the extreme value is a minimum value, the expression is positively correlated with the physical quantity, the weight of the expression is negative, the expression is negatively correlated with the physical quantity, and the weight of the expression is positive.
6. The method of claim 5, wherein solving the constraint expression and the optimization expression based on the variables and the constants comprises:
generating an input file of a solver according to the variables, the constants, the constraint expressions and the optimization expressions;
inputting the input file into a mixed integer solver, and outputting an optimal solution of the variables of the optimized expression by the mixed integer solver;
and determining the circulation plan of the goods according to the optimal solution of the variables.
7. The method according to claim 6, wherein the physical quantity corresponding to the final optimization objective is an overall cost, the extreme value is a minimum value of the overall cost,
determining the circulation plan of the cargo according to the optimal solution of the variables comprises:
determining a delivery plan of the goods according to the optimal solution of the variables of the goods production plan data of the goods;
determining a transfer plan of the goods according to the optimal solution of the variables of the goods warehousing data of the goods;
and determining a distribution plan of the cargo circulation equipment of the cargo according to the optimal solution of the variables of the cargo circulation equipment data of the cargo.
8. A data processing device for cargo, comprising:
the system comprises a first determination module, a second determination module and a control module, wherein the first determination module is used for determining a plurality of constants and a plurality of variables in data of cargoes;
the second determining module is used for determining constraint relations of goods circulation and constraint expressions of a plurality of constants and a plurality of variables, wherein the constraint relations are constraint relations between the constants and the variables;
the third determining module is used for determining an optimization expression of a final optimization target according to a plurality of optimization conditions of cargo circulation, wherein the optimization conditions are the optimization conditions of the cargo circulation;
and the fourth determining module is used for solving according to the variables, the constants, the constraint expressions and the optimized expressions to determine the circulation plan of the goods.
9. A processor, characterized in that the processor is configured to run a program, wherein the program is configured to execute a data processing method of an item according to any one of claims 1 to 7 when running.
10. A computer storage medium, comprising a stored program, wherein the program, when executed, controls an apparatus in which the computer storage medium is located to perform the data processing method for goods according to any one of claims 1 to 7.
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| CN113592146B (en) * | 2021-06-30 | 2023-07-25 | 青岛海尔科技有限公司 | Target product delivery method, target product delivery system and electronic equipment |
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| CN110111004A (en) * | 2019-05-09 | 2019-08-09 | 上汽安吉物流股份有限公司 | Complete vehicle logistics dispatching method and device, computer-readable medium and logistics system |
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