CN117934049B - Multi-level cost calculation optimization method and device, electronic equipment and storage medium - Google Patents
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Abstract
The invention relates to a multi-level cost calculation optimization method, a device, electronic equipment and a storage medium, wherein the method comprises the following steps: and obtaining a cost calculation formula, decomposing the cost calculation formula into a plurality of layers, and constructing an inverse Polish expression corresponding to each layer based on each layer of the cost calculation formula. And sequentially reading the operands and operators in the reverse Polish expression from one side of the reverse Polish expression, and calculating the reverse Polish expression according to the priority of the operators to obtain a single-layer level calculation result. The different levels of reverse polish expressions are combined to obtain a multi-level reverse polish expression, and a multi-level calculation result of the multi-level reverse polish expression is obtained based on a single-level calculation result of each reverse polish expression. The method relies on the algorithm of the reverse Polish expression, so that the calculated amount of multi-level cost calculation is greatly reduced, and the calculation efficiency under the multi-level cost structure is further improved.
Description
Technical Field
The present invention relates to the field of computer science and software engineering technology, and in particular, to a method and apparatus for optimizing multi-level cost calculation, an electronic device, and a storage medium.
Background
Cost calculation is an important concept in computer science and software engineering. Cost calculations typically involve a number of factors, such as time, manpower, resources, etc. In general, cost computation requires consideration of multiple levels, such as levels of project level, task level, and resource level.
At present, the traditional cost calculation method mainly uses a tree structure to represent the levels, but the representation mode of the tree structure increases the calculation pressure to a certain extent due to more and more branches in the complex cost calculation problem of multi-level cost calculation, so that the cost calculation efficiency is reduced, and even the accuracy of the cost calculation is reduced.
Disclosure of Invention
In view of the foregoing, it is desirable to provide a multi-level cost calculation optimization method, apparatus, electronic device, and storage medium capable of ensuring the efficiency and accuracy of cost calculation in multi-level cost calculation.
The invention provides a multi-level cost calculation optimization method, which comprises the following steps:
Acquiring a cost calculation formula, decomposing the cost calculation formula into a plurality of layers, and constructing an inverse Polish expression corresponding to each layer based on each layer of the cost calculation formula;
Sequentially reading operands and operators in the reverse Polish expression from one side of the reverse Polish expression, and calculating the reverse Polish expression according to the priority of the operators to obtain a single-level calculation result;
Combining the reverse polish expressions of different levels to obtain a multi-level reverse polish expression, and obtaining a multi-level calculation result of the multi-level reverse polish expression based on a single-level calculation result of each reverse polish expression;
wherein each hierarchy contains a plurality of cost terms, each cost term having a unique identifier and cost value, the reverse polish expression is composed of operands and operators, the operands are located on one side of the reverse polish expression, the operators are located on the other side of the reverse polish expression, and the priorities of the operators are arranged in a set arrangement order.
In one embodiment, the obtaining the cost calculation formula and decomposing the cost calculation formula into a plurality of levels, and constructing the inverse polish expression corresponding to each level based on each level of the cost calculation formula includes:
Setting the operand on a calculation start side of the reverse Polish expression and setting the operator on a calculation end side of the reverse Polish expression when the reverse Polish expression is constructed; and
Acquiring the set arrangement order based on the priority of the operators, wherein the set arrangement order is from the calculation starting side to the calculation ending side;
the operand is composed of the identifier and the cost value, and the operator is the operator corresponding to the identifier and the cost value.
In one embodiment, the sequentially reading the operands and operators in the reverse polish expression from one side of the reverse polish expression, and calculating the reverse polish expression according to the priority of the operators to obtain a single-level calculation result, including:
Sequentially reading the operands and operators in the reverse Polish expression from a computation start side of the reverse Polish expression to pop the operands in the reverse Polish expression out of the stack;
calculating a first calculation result between a plurality of the operands based on priorities of operators among the operands;
The single-layer level calculation result of the reverse Polish expression is calculated by a plurality of first calculation results according to the priority of the operators.
In one embodiment, the combining the reverse polish expressions of different levels to obtain a multi-level reverse polish expression, and based on a single-level calculation result of each of the reverse polish expressions, obtaining a multi-level calculation result of the multi-level reverse polish expression includes:
Combining the single-layer-level computing results corresponding to the inverse Poland expressions of different levels, and reading operators among the single-layer-level computing results of different levels;
And calculating the single-level calculation results of the different levels as operands based on the priorities of the operators to obtain the multi-level calculation results.
In one embodiment, the combining the reverse polish expressions of different levels to obtain a multi-level reverse polish expression, and based on a single-level calculation result of each reverse polish expression, obtaining a multi-level calculation result of the multi-level reverse polish expression, further includes:
Decomposing the cost calculation formula into a plurality of levels, and dequeuing the levels in sequence according to the level data in the calculation queue so as to push the dequeued level data;
If the operators exist in the dequeue of the hierarchical data, two operands are popped out of a stack to be used as the operands on two sides of the operators for calculation, and a second calculation result is obtained;
and stacking the second calculation result, and continuously dequeuing the second calculation result in sequence according to the level data in the calculation queue so as to calculate each single-level reverse Polish expression in the multi-level reverse Polish expressions, thereby obtaining the multi-level calculation result.
In one embodiment, the method further comprises:
performing visual rendering on the reverse Polish expression, the single-layer-level computing result, the multi-layer-level reverse Polish expression and the multi-layer-level computing result, and sending the visualized rendering to the front end so as to display cost computing results of different layers;
And displaying the cost calculation results of the different levels in a graphical mode, wherein the graphical mode at least comprises a line graph and a histogram.
In one embodiment, the method further comprises:
acquiring actual application requirements, wherein the actual application requirements are requests for users to increase or decrease the hierarchy in the cost calculation formula;
Increasing or decreasing the hierarchy in the costing formula based on the actual application demand to increase or decrease the cost terms in the costing formula and the computational relationship between the cost terms;
wherein the hierarchy includes at least a project level, a task level, and a resource level.
The invention also provides a multi-level cost calculation optimization device, which comprises:
The hierarchy decomposition module is used for acquiring a cost calculation formula, decomposing the cost calculation formula into a plurality of hierarchies, and constructing an inverse Polish expression corresponding to each hierarchy based on each hierarchy of the cost calculation formula;
The single-level computing module is used for sequentially reading the operands and operators in the reverse Polish expression from one side of the reverse Polish expression, and computing the reverse Polish expression according to the priority of the operators to obtain a single-level computing result;
The multi-level computing module is used for combining the reverse polish expressions of different levels to obtain multi-level reverse polish expressions, and obtaining multi-level computing results of the multi-level reverse polish expressions based on single-level computing results of each reverse polish expression;
wherein each hierarchy contains a plurality of cost terms, each cost term having a unique identifier and cost value, the reverse polish expression is composed of operands and operators, the operands are located on one side of the reverse polish expression, the operators are located on the other side of the reverse polish expression, and the priorities of the operators are arranged in a set arrangement order.
The invention also provides electronic equipment, which comprises a memory and a processor, wherein the memory stores a computer program, and the processor realizes the multi-level cost calculation optimization method according to any one of the above when executing the computer program.
The invention also provides a computer storage medium storing a computer program which when executed by a processor implements a multi-level cost calculation optimization method as described in any one of the above.
The multi-level cost calculation optimization method, the multi-level cost calculation optimization device, the electronic equipment and the storage medium are characterized in that cost calculation is divided into a plurality of levels, each level comprises a plurality of cost items, each cost item has a unique identifier and a cost value, and a corresponding reverse Polish expression is constructed based on each level. Then, sequentially reading the operands and operators in the reverse Polish expression from one side of the reverse Polish expression, and calculating the reverse Polish expression according to the priority of the operators to obtain a single-layer level calculation result. Finally, combining the reverse Polish expressions of different levels to obtain a multi-level reverse Polish expression, and obtaining a multi-level computing result of the multi-level reverse Polish expression based on a single-level computing result of each reverse Polish expression. The method relies on the algorithm of the reverse Polish expression, so that the calculated amount of multi-level cost calculation is greatly reduced, and the calculation efficiency under the multi-level cost structure is further improved.
Drawings
In order to more clearly illustrate the invention or the technical solutions of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are some embodiments of the invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of a multi-level cost calculation optimization method provided by the invention;
FIG. 2 is a schematic overall flow diagram of a multi-level cost calculation optimization method based on an inverse Polish expression according to a specific embodiment of the present invention;
FIG. 3 is a schematic diagram of a calculation process of a multi-level reverse Polish expression of a multi-level cost calculation optimization method according to an embodiment of the present invention;
FIG. 4 is a second schematic flow chart of the multi-level cost calculation optimization method according to the present invention;
FIG. 5 is a third schematic flow chart of the multi-level cost calculation optimization method according to the present invention;
FIG. 6 is a schematic diagram of a multi-level cost calculation optimization method according to the present invention;
FIG. 7 is a schematic flow chart of a multi-level cost calculation optimization method provided by the invention;
FIG. 8 is a flowchart illustrating a multi-level cost calculation optimization method according to the present invention;
FIG. 9 is a schematic diagram of a multi-level cost calculation optimization method according to the present invention;
FIG. 10 is a schematic diagram of a multi-level cost calculation optimizing device according to the present invention;
Fig. 11 is an internal structural diagram of a computer device provided by the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The multi-level cost calculation optimization method, apparatus, electronic device and storage medium of the present invention are described below with reference to fig. 1 to 11.
As shown in fig. 1, in one embodiment, a multi-level cost calculation optimization method includes the steps of:
Step S110, a cost calculation formula is obtained, the cost calculation formula is decomposed into a plurality of layers, and an inverse Polish expression corresponding to each layer is constructed based on each layer of the cost calculation formula.
Specifically, the server obtains a cost calculation formula, decomposes the cost calculation formula into a plurality of levels, and constructs an inverse Polish expression corresponding to each level based on each level of the cost calculation formula.
Wherein each hierarchy contains a plurality of cost terms, each cost term has a unique identifier and cost value, the reverse Polish expression is composed of operands and operators, the operands are located on one side of the reverse Polish expression, the operators are located on the other side of the reverse Polish expression, and the priorities of the operators are arranged according to a set arrangement order.
In a specific embodiment, as shown in fig. 2, the multi-level cost calculation optimization method provided by the present invention first decomposes cost calculation into multiple levels, such as an item level, a task level, and a resource level, each of which contains multiple cost items, each of which has a unique identifier and a cost value. Next, a corresponding reverse polish expression is constructed for each hierarchy, the operands are placed on the left side of the reverse polish expression, the operators are placed on the right side of the reverse polish expression, and the priorities of the operators are arranged in order from left to right when the reverse polish expression is constructed.
In this embodiment, for each cost item, an inverse Polish expression is constructed with its identifier and cost value as operands and its corresponding operator as the operator. For example, for project-level cost calculations, if the total cost of project A and project B needs to be calculated, then the following inverse Polish expression can be constructed: ab+.
Where A and B are the costs of item A and item B, + is the addition operator.
Likewise, for task-level cost computation, if the total cost of task C and task D needs to be computed and added to the total cost of item A and item B, then the following inverse Polish expression can be constructed: c D + A B +.
Where C and D are the costs of task C and task D and +is the addition operator.
For resource level cost computation, if the cost of resource E and task D needs to be computed and added to the total cost of task C and task D, then the following inverse Polish expression can be constructed: e D + C D + A B +.
Where E is the cost of resource E and +is the addition operator.
In this way, each level of cost computation may be constructed as an inverse Polish expression, thereby facilitating subsequent computation and analysis.
And step S120, sequentially reading the operands and operators in the reverse Polish expression from one side of the reverse Polish expression, and calculating the reverse Polish expression according to the priority of the operators to obtain a single-layer calculation result.
Specifically, the server sequentially reads the operands and operators in the reverse polish expression from one side of the reverse polish expression constructed in step S110, and calculates the reverse polish expression according to the priority of the operators, so as to obtain a single-layer calculation result of the reverse polish expression corresponding to each layer.
In a specific embodiment, as shown in fig. 3, the multi-level cost calculation optimization method provided by the present invention may use the calculation method of the reverse polish expression to calculate the result of the constructed reverse polish expression. I.e. the operands and operators are read in sequence, starting from the left side of the expression, and calculated according to the priority of the operators.
For example, for the inverse Polish expression: e D + C D + A B +
(1): And sequentially dequeuing the data in the queue, then pushing the stack, sequentially reading the operand and the operator, and calculating.
(2): If operators are encountered in the dequeue process, two operands are popped from the stack and respectively used as a right operand and a left operand, operands E and D are read, and the sum of the operands E and D is calculated to obtain a result E+D.
(3): And then reading the operator+, pushing the operation result of the last step to be added with the operands C and D to obtain a result (E+D) +C+D.
(4): Jumping to (1), continuing dequeue operation, reading the operator "+", adding the result of (3) with the operands A and B, and obtaining the final result (E+D) +C+D+A+B.
In this way, the result of the inverse polish expression, i.e., the final result of the cost calculation, can be calculated.
Step S130, combining the reverse Polish expressions of different levels to obtain a multi-level reverse Polish expression, and obtaining a multi-level calculation result of the multi-level reverse Polish expression based on a single-level calculation result of each reverse Polish expression.
Specifically, the server combines the reverse polish expressions of different levels to obtain a multi-level reverse polish expression, and obtains a multi-level calculation result of the multi-level reverse polish expression based on a single-level calculation result of the reverse polish expression of each level.
In a specific embodiment, as shown in fig. 2, the multi-level cost calculation optimization method provided by the invention not only can realize single-level cost calculation, but also can realize multi-level cost calculation. In particular, different levels of inverse polish expressions may be combined to achieve multiple levels of cost computation.
For example, for project-level and task-level cost calculations, they may be combined into a multi-level inverse Polish expression: a B + C D +, where A and B are the costs of item A and item B, C and D are the costs of task C and task D, and "+" is the addition operator. For this multi-level reverse polish expression, the calculation method of the reverse polish expression may be used, sequentially reading the operands and operators from the left side, and performing the calculation according to the priorities of the operators. Specifically, the costs of item a and item B may be calculated first, and then the result may be added to the costs of task C and task D to obtain a final cost calculation result. In this way, multi-level cost calculation can be realized, so that the requirements of practical application are better met.
In a specific embodiment, in order to better explain the multi-level cost calculation optimization method provided by the invention, pseudo-coding expression is carried out on the multi-level reverse Polish expression calculation principle, and specific code segments are as follows:
-procedure start } -
Defining a class named PolandFunction
Method for defining a name main
A string variable named PLExpression is defined, the value of which is "specific Polish expression string"
Calling the calculation method, inputting PLExpression as a parameter, and storing the result in an integer variable named as calculation
Printing the value of calculation
Method for ending main
Defining a method named getPLExpressionList, accepting a string parameter
Storing the result in an array of strings named s using space-separation string parameters
Creating an empty list named list
Traversing each element in s
Adding elements to list
Printing list
Returning list
Ending getPLExpressionList method
Defining a method named isOper, accepting a character parameter
If the character parameter is any one of +, -, or/and then true is returned
Otherwise, return false
Ending isOper method
Defining a method called calculation, accepting a string parameter
Calling getPLExpressionList method, inputting character string parameters, and storing the result in list named list
Creating an empty stack named numStack
Traversing each element in list
If the element is not a number
The top element of numStack pops up, storing its value in an integer variable named num1
The top element of numStack is popped again, storing its value in an integer variable named num2
Calling the cal method, importing num1, num2 and elements, storing the result in integer variable named cal
Pressing the value of cal into numStack
Otherwise
Pressing elements into numStack
The top element of numStack is popped up, its value converted to an integer and returned
Method for ending calculation
Defining a method named cal, accepting three integer parameters
Creating an integer variable named result, initializing to 0
Performing the corresponding calculations based on third parameters (operators)
If the operator is +, add the first parameter to the second parameter, store the result in result
If the operator is-, subtracting the first parameter from the second parameter, storing the result in result
If the operator is x, multiplying the first parameter by the second parameter, storing the result in result
If the operator is/, dividing the second parameter by the first parameter, storing the result in result
Return result
Ending cal method
Ending PolandFunction class
-Procedure ending- (I)
In the multi-level cost calculation optimization method, cost calculation is decomposed into a plurality of levels, each level comprises a plurality of cost items, each cost item has a unique identifier and a cost value, and a corresponding reverse Polish expression is constructed based on each level. Then, sequentially reading the operands and operators in the reverse Polish expression from one side of the reverse Polish expression, and calculating the reverse Polish expression according to the priority of the operators to obtain a single-layer level calculation result. Finally, combining the reverse Polish expressions of different levels to obtain a multi-level reverse Polish expression, and obtaining a multi-level computing result of the multi-level reverse Polish expression based on a single-level computing result of each reverse Polish expression. The method relies on the algorithm of the reverse Polish expression, so that the calculated amount of multi-level cost calculation is greatly reduced, and the calculation efficiency under the multi-level cost structure is further improved.
As shown in fig. 4, in one embodiment, the multi-level cost calculation optimization method provided by the present invention obtains a cost calculation formula, decomposes the cost calculation formula into a plurality of levels, and constructs an inverse polish expression corresponding to each level based on each level of the cost calculation formula, and specifically includes the following steps:
in step S112, when the reverse polish expression is constructed, the operand is set on the calculation start side of the reverse polish expression, and the operator is set on the calculation end side of the reverse polish expression.
Specifically, in constructing the inverse polish expression, the operand is first set on the calculation start side of the inverse polish expression, and the operator is set on the calculation end side of the inverse polish expression.
Step S114, the set ranking order, which is the ranking order from the calculation start side to the calculation end side, is acquired based on the priorities of the operators.
Specifically, the server acquires a set arrangement order from the calculation start side to the calculation end side based on the priority of the operators.
As shown in fig. 5, in one embodiment, the multi-level cost calculation optimization method provided by the present invention sequentially reads operands and operators in an inverse polish expression from one side of the inverse polish expression, and calculates the inverse polish expression according to the priority of the operators to obtain a single-level calculation result, which specifically includes the following steps:
step S122, sequentially reads the operands and operators in the reverse polish expression from the calculation start side of the reverse polish expression to pop the operands in the reverse polish expression out of the stack.
Specifically, in calculating the single-level calculation result, the operands and operators in the reverse polish expression are first read sequentially from the calculation start side of the reverse polish expression to pop the operands in the reverse polish expression out of the stack.
Step S124, a first calculation result among the plurality of operands is calculated based on the priorities of operators among the operands.
Specifically, the server calculates a calculation result between the plurality of operands, that is, a first calculation result, based on the priorities of operators between the operands.
As shown in fig. 6, in one embodiment, the multi-level cost calculation optimization method provided by the present invention combines the reverse polish expressions of different levels to obtain multi-level reverse polish expressions, and obtains a multi-level calculation result of the multi-level reverse polish expressions based on a single-level calculation result of each reverse polish expression, specifically including the following steps:
Step S131, combining single-layer-level computing results corresponding to the reverse Poland expressions of different levels, and reading operators among the single-layer-level computing results of different levels.
Specifically, in the process of calculating the multi-level calculation results, the server combines single-level calculation results corresponding to the reverse Polish expressions of different levels, and reads operators among the single-level calculation results of different levels.
Step S133, calculating single-layer level calculation results of different levels as operands based on the priority of the operators to obtain a multi-level calculation result.
Specifically, the server calculates single-layer calculation results of different layers as operands based on the priority of the operators, and obtains multi-layer calculation results.
As shown in fig. 7, in one embodiment, the multi-level cost calculation optimization method provided by the present invention combines the reverse polish expressions of different levels to obtain a multi-level reverse polish expression, and obtains a multi-level calculation result of the multi-level reverse polish expression based on a single-level calculation result of each reverse polish expression, and specifically further includes the following steps:
and S132, decomposing the cost calculation formula into a plurality of layers, and dequeuing the dequeued layer data in sequence according to the layer data in the calculation queue so as to push the dequeued layer data.
Specifically, in the process of calculating the multi-level calculation result, the server decomposes cost calculation into a plurality of levels, and dequeues the level data in the calculation queue in turn, so as to push the dequeued level data.
In step S134, if there is an operator when the hierarchical data is dequeued, two operands are popped from the stack as the operands on both sides of the operator for calculation, and a second calculation result is obtained.
Specifically, if an operator exists in the dequeue of the hierarchical data, two operands are popped out of the stack to serve as operands on two sides of the operator for calculation, and a corresponding calculation result, namely a second calculation result, is obtained.
Step S136, stacking the second calculation result, and continuing dequeuing in sequence according to the level data in the calculation queue so as to calculate each single-level reverse Polish expression in the multi-level reverse Polish expressions, thereby obtaining the multi-level calculation result.
Specifically, the server performs a stacking process on the second calculation result obtained in the step S134, and continues dequeuing according to the level data in the calculation queue, so as to calculate each single-level reverse polish expression in the multi-level reverse polish expressions, thereby obtaining a multi-level calculation result.
In particular embodiments, as shown in connection with fig. 3, for the reverse polish expression: e D + C D + A B +.
(1): And sequentially dequeuing the data in the queue, then pushing the stack, sequentially reading the operand and the operator, and calculating.
(2): If operators are encountered in the dequeue process, two operands are popped from the stack and respectively used as a right operand and a left operand, operands E and D are read, and the sum of the operands E and D is calculated to obtain a result E+D.
(3): And then reading the operator+, pushing the operation result of the last step to be added with the operands C and D to obtain a result (E+D) +C+D.
(4): Jumping to (1), continuing dequeue operation, reading the operator "+", adding the result of (3) with the operands A and B, and obtaining the final result (E+D) +C+D+A+B.
As shown in fig. 8, in one embodiment, the multi-level cost calculation optimization method provided by the present invention further includes the following steps:
and step S810, performing visual rendering on the reverse Polish expression, the single-layer-level computing result, the multi-layer-level reverse Polish expression and the multi-layer-level computing result, and sending the visualized rendering to the front end so as to display the cost computing results of different layers.
Specifically, the server performs visual rendering on the corresponding inverse Polish expression of each level, the single-level computing result, the multi-level inverse Polish expression and the multi-level computing result, and sends the visualized rendering to the front end so as to display the cost computing results of different levels.
In step S820, the cost calculation results of different levels are displayed in a graphical manner, wherein the graphical manner at least comprises a line graph and a bar graph.
Specifically, the server displays the cost calculation results of different levels in a graphical mode, wherein the graphical mode at least comprises a line graph and a histogram.
In a specific embodiment, the multi-level cost calculation optimization method provided by the invention can display the reverse Polish expression and the calculation result in a graphical mode, thereby facilitating the analysis and decision of a user. For example, the cost calculation results of different levels may be presented using a line graph, a bar graph, or the like, and the different cost items and the relationship between the cost items may be represented using a color, a shape, or the like. In this way, visualization of the cost calculation may be achieved, thereby better supporting the user's decision making process. In addition, automation of cost calculation can be realized. In particular, the method of the present invention may be implemented using a programming language to automate cost calculations and analyses. For example, the method of the present invention may be implemented using a programming language such as Python, java, etc., and the cost data stored and managed using tools such as Excel, databases, etc. By the method, automation of cost calculation can be realized, so that workload of manual operation is reduced, and efficiency and accuracy of cost calculation are improved.
As shown in fig. 9, in one embodiment, the multi-level cost calculation optimization method provided by the present invention further includes the following steps:
In step S910, the actual application requirement is obtained, and the actual application requirement is a request for the user to increase or decrease the hierarchy in the cost calculation formula.
Specifically, the server obtains the actual application requirement of the user, and the actual application requirement is a request for the user to increase or decrease the hierarchy in the cost calculation formula.
In step S920, the hierarchy in the cost calculation formula is increased or decreased based on the actual application requirement, so as to increase or decrease the cost term in the cost calculation formula and the calculation relationship between the cost terms.
Specifically, the server increases or decreases the hierarchy in the cost calculation formula based on the actual application requirement, so as to increase or decrease the cost items in the cost calculation formula and the calculation relation between the cost items.
In a specific embodiment, the multi-level cost calculation optimization method provided by the invention can increase or decrease the level and detail of cost calculation according to the actual application requirements, so as to better adapt to different application scenes. For example, the item level, task level, resource level, etc. hierarchy in the cost calculation may be increased or decreased as needed, increasing or decreasing the relationship between the cost item and the cost item in the cost calculation. By the method, the expandability of cost calculation can be realized, so that the requirements of different application scenes can be better met.
The multi-level cost calculation optimizing device provided by the invention is described below, and the multi-level cost calculation optimizing device described below and the multi-level cost calculation optimizing method described above can be referred to correspondingly.
As shown in FIG. 10, in one embodiment, a multi-level cost computation optimization apparatus includes a hierarchy decomposition module 1010, a single-level computation module 1020, and a multi-level computation module 1030.
The hierarchy decomposition module 1010 is configured to obtain a cost calculation formula, decompose the cost calculation formula into a plurality of hierarchies, and construct an inverse polish expression corresponding to each hierarchy based on each hierarchy of the cost calculation formula.
The single-level computing module 1020 is configured to sequentially read the operands and the operators in the reverse polish expression from one side of the reverse polish expression, and compute the reverse polish expression according to the priorities of the operators, so as to obtain a single-level computing result.
The multi-level computation module 1030 is configured to combine the reverse polish expressions of different levels to obtain a multi-level reverse polish expression, and obtain a multi-level computation result of the multi-level reverse polish expression based on a single-level computation result of each reverse polish expression.
Wherein each hierarchy contains a plurality of cost terms, each cost term has a unique identifier and cost value, the reverse Polish expression is composed of operands and operators, the operands are located on one side of the reverse Polish expression, the operators are located on the other side of the reverse Polish expression, and the priorities of the operators are arranged according to a set arrangement order.
In this embodiment, the multi-level cost calculation optimization device provided by the invention, the level decomposition module is specifically configured to:
In constructing an inverse Polish expression, operands are set on the calculation start side of the inverse Polish expression, and operators are set on the calculation end side of the inverse Polish expression. And
The set ranking order is obtained based on the priorities of the operators, the set ranking order being the ranking order from the calculation start side to the calculation end side.
Wherein the operand is composed of an identifier and a cost value, and the operator is an operator corresponding to the identifier and the cost value.
In this embodiment, the multi-level cost calculation optimization device provided by the invention, the single-level calculation module is specifically configured to:
The operands and operators in the reverse Polish expression are read sequentially from the computation start side of the reverse Polish expression to pop the operands in the reverse Polish expression out of the stack.
A first calculation result between the plurality of operands is calculated based on the priorities of the operators between the operands.
The single-layer level calculation result of the reverse Polish expression is calculated according to the priority of the operators by a plurality of first calculation results.
In this embodiment, the multi-level cost calculation optimization device provided by the present invention, the multi-level calculation module is specifically configured to:
And combining single-layer-level computing results corresponding to the reverse Poland expressions of different levels, and reading operators among the single-layer-level computing results of different levels.
And calculating single-layer-level calculation results of different levels as operands based on the priority of the operators to obtain a multi-level calculation result.
In this embodiment, the multi-level cost calculation optimization device provided by the present invention, the multi-level calculation module is specifically further configured to:
And decomposing the cost calculation formula into a plurality of layers, and dequeuing the dequeued layer data in sequence according to the layer data in the calculation queue so as to push the dequeued layer data.
If operators exist in the process of dequeuing the hierarchical data, two operands are popped from the stack to serve as operands on two sides of the operators to be calculated, and a second calculation result is obtained.
And stacking the second calculation result, and continuously dequeuing the second calculation result in sequence according to the level data in the calculation queue so as to calculate each single-level reverse Polish expression in the multi-level reverse Polish expressions, thereby obtaining the multi-level calculation result.
In this embodiment, the multi-level cost calculation optimizing apparatus provided by the present invention further includes a cost calculation visualizing module, configured to:
And visually rendering the reverse Polish expression, the single-layer-level computing result, the multi-layer-level reverse Polish expression and the multi-layer-level computing result and sending the visualized rendering to the front end so as to show cost computing results of different layers.
And displaying cost calculation results of different levels in a graphical mode, wherein the graphical mode at least comprises a line graph and a column graph.
In this embodiment, the multi-level cost calculation optimization apparatus provided by the present invention further includes a cost calculation adjustment module, configured to:
And acquiring the actual application requirement, wherein the actual application requirement is a request for increasing or decreasing the hierarchy in the cost calculation formula for the user.
The hierarchy in the cost calculation formula is increased or decreased based on actual application requirements to increase or decrease cost terms in the cost calculation formula and the calculation relationship between the cost terms.
Wherein the hierarchy includes at least a project level, a task level, and a resource level.
Fig. 11 illustrates a physical structure diagram of an electronic device, which may be an intelligent terminal, and an internal structure diagram thereof may be as shown in fig. 11. The electronic device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the electronic device is configured to provide computing and control capabilities. The memory of the electronic device includes a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface of the electronic device is used for communicating with an external terminal through a network connection. The computer program, when executed by a processor, implements a multi-level cost calculation optimization method, the method comprising:
Acquiring a cost calculation formula, decomposing the cost calculation formula into a plurality of layers, and constructing an inverse Polish expression corresponding to each layer based on each layer of the cost calculation formula;
Sequentially reading operands and operators in the reverse Polish expression from one side of the reverse Polish expression, and calculating the reverse Polish expression according to the priority of the operators to obtain a single-level calculation result;
combining the reverse Polish expressions of different levels to obtain a multi-level reverse Polish expression, and obtaining a multi-level calculation result of the multi-level reverse Polish expression based on a single-level calculation result of each reverse Polish expression;
Wherein each hierarchy contains a plurality of cost terms, each cost term has a unique identifier and cost value, the reverse Polish expression is composed of operands and operators, the operands are located on one side of the reverse Polish expression, the operators are located on the other side of the reverse Polish expression, and the priorities of the operators are arranged according to a set arrangement order.
It will be appreciated by those skilled in the art that the structure shown in fig. 11 is merely a block diagram of a portion of the structure associated with the present inventive arrangements and is not limiting of the electronic device to which the present inventive arrangements are applied, and that a particular electronic device may include more or fewer components than shown, or may combine certain components, or have a different arrangement of components.
In another aspect, the present invention also provides a computer storage medium storing a computer program which when executed by a processor implements a multi-level cost calculation optimization method, the method comprising:
Acquiring a cost calculation formula, decomposing the cost calculation formula into a plurality of layers, and constructing an inverse Polish expression corresponding to each layer based on each layer of the cost calculation formula;
Sequentially reading operands and operators in the reverse Polish expression from one side of the reverse Polish expression, and calculating the reverse Polish expression according to the priority of the operators to obtain a single-level calculation result;
combining the reverse Polish expressions of different levels to obtain a multi-level reverse Polish expression, and obtaining a multi-level calculation result of the multi-level reverse Polish expression based on a single-level calculation result of each reverse Polish expression;
Wherein each hierarchy contains a plurality of cost terms, each cost term has a unique identifier and cost value, the reverse Polish expression is composed of operands and operators, the operands are located on one side of the reverse Polish expression, the operators are located on the other side of the reverse Polish expression, and the priorities of the operators are arranged according to a set arrangement order.
In yet another aspect, a computer program product or computer program is provided, the computer program product or computer program comprising computer instructions stored in a computer readable storage medium. A processor of an electronic device reads the computer instructions from a computer readable storage medium, the processor executing the computer instructions to implement a multi-level cost calculation optimization method, the method comprising:
Acquiring a cost calculation formula, decomposing the cost calculation formula into a plurality of layers, and constructing an inverse Polish expression corresponding to each layer based on each layer of the cost calculation formula;
Sequentially reading operands and operators in the reverse Polish expression from one side of the reverse Polish expression, and calculating the reverse Polish expression according to the priority of the operators to obtain a single-level calculation result;
combining the reverse Polish expressions of different levels to obtain a multi-level reverse Polish expression, and obtaining a multi-level calculation result of the multi-level reverse Polish expression based on a single-level calculation result of each reverse Polish expression;
Wherein each hierarchy contains a plurality of cost terms, each cost term has a unique identifier and cost value, the reverse Polish expression is composed of operands and operators, the operands are located on one side of the reverse Polish expression, the operators are located on the other side of the reverse Polish expression, and the priorities of the operators are arranged according to a set arrangement order.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory.
By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (SYNCHLINK) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The foregoing examples illustrate only a few embodiments of the invention and are described in detail herein without thereby limiting the scope of the invention. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the invention, which are all within the scope of the invention. Accordingly, the scope of protection of the present invention is to be determined by the appended claims.
Claims (10)
1. A multi-level cost computation optimization method, the method comprising:
Acquiring a cost calculation formula, decomposing the cost calculation formula into a plurality of layers, and constructing an inverse Polish expression corresponding to each layer based on each layer of the cost calculation formula;
Sequentially reading operands and operators in the reverse Polish expression from one side of the reverse Polish expression, and calculating the reverse Polish expression according to the priority of the operators to obtain a single-level calculation result;
Combining the reverse polish expressions of different levels to obtain a multi-level reverse polish expression, and obtaining a multi-level calculation result of the multi-level reverse polish expression based on a single-level calculation result of each reverse polish expression;
wherein each hierarchy contains a plurality of cost terms, each cost term having a unique identifier and cost value, the reverse polish expression is composed of operands and operators, the operands are located on one side of the reverse polish expression, the operators are located on the other side of the reverse polish expression, and the priorities of the operators are arranged in a set arrangement order.
2. The multi-level costing optimization method of claim 1 wherein the obtaining the costing formula and decomposing the costing formula into a plurality of levels and constructing an inverse polish expression for each level based on each level of the costing formula includes:
Setting the operand on a calculation start side of the reverse Polish expression and setting the operator on a calculation end side of the reverse Polish expression when the reverse Polish expression is constructed; and
Acquiring the set arrangement order based on the priority of the operators, wherein the set arrangement order is from the calculation starting side to the calculation ending side;
the operand is composed of the identifier and the cost value, and the operator is the operator corresponding to the identifier and the cost value.
3. The multi-level cost calculation optimization method according to claim 2, wherein the sequentially reading the operands and operators in the reverse polish expression from one side of the reverse polish expression, and calculating the reverse polish expression according to the priority of the operators, to obtain a single-level calculation result, comprises:
Sequentially reading the operands and operators in the reverse Polish expression from a computation start side of the reverse Polish expression to pop the operands in the reverse Polish expression out of the stack;
calculating a first calculation result between a plurality of the operands based on priorities of operators among the operands;
The single-layer level calculation result of the reverse Polish expression is calculated by a plurality of first calculation results according to the priority of the operators.
4. The multi-level cost computation optimization method of claim 1, wherein said combining the reverse polish expressions of different levels to obtain a multi-level reverse polish expression and based on a single-level computation result of each of the reverse polish expressions, obtaining a multi-level computation result of the multi-level reverse polish expression comprises:
Combining the single-layer-level computing results corresponding to the inverse Poland expressions of different levels, and reading operators among the single-layer-level computing results of different levels;
And calculating the single-level calculation results of the different levels as operands based on the priorities of the operators to obtain the multi-level calculation results.
5. The multi-level cost computation optimization method of claim 4, wherein said combining said inverse polish expressions of different levels to obtain a multi-level inverse polish expression and based on single-level computation results of each said inverse polish expression, obtaining multi-level computation results of said multi-level inverse polish expression further comprises:
Decomposing the cost calculation formula into a plurality of levels, and dequeuing the levels in sequence according to the level data in the calculation queue so as to push the dequeued level data;
If the operators exist in the dequeue of the hierarchical data, two operands are popped out of a stack to be used as the operands on two sides of the operators for calculation, and a second calculation result is obtained;
and stacking the second calculation result, and continuously dequeuing the second calculation result in sequence according to the level data in the calculation queue so as to calculate each single-level reverse Polish expression in the multi-level reverse Polish expressions, thereby obtaining the multi-level calculation result.
6. The multi-level cost computation optimization method of claim 1, further comprising:
performing visual rendering on the reverse Polish expression, the single-layer-level computing result, the multi-layer-level reverse Polish expression and the multi-layer-level computing result, and sending the visualized rendering to the front end so as to display cost computing results of different layers;
And displaying the cost calculation results of the different levels in a graphical mode, wherein the graphical mode at least comprises a line graph and a histogram.
7. The multi-level cost computation optimization method of any one of claims 1 to 6, further comprising:
acquiring actual application requirements, wherein the actual application requirements are requests for users to increase or decrease the hierarchy in the cost calculation formula;
Increasing or decreasing the hierarchy in the costing formula based on the actual application demand to increase or decrease the cost terms in the costing formula and the computational relationship between the cost terms;
wherein the hierarchy includes at least a project level, a task level, and a resource level.
8. A multi-level costing optimization apparatus, the apparatus comprising:
The hierarchy decomposition module is used for acquiring a cost calculation formula, decomposing the cost calculation formula into a plurality of hierarchies, and constructing an inverse Polish expression corresponding to each hierarchy based on each hierarchy of the cost calculation formula;
The single-level computing module is used for sequentially reading the operands and operators in the reverse Polish expression from one side of the reverse Polish expression, and computing the reverse Polish expression according to the priority of the operators to obtain a single-level computing result;
The multi-level computing module is used for combining the reverse polish expressions of different levels to obtain multi-level reverse polish expressions, and obtaining multi-level computing results of the multi-level reverse polish expressions based on single-level computing results of each reverse polish expression;
wherein each hierarchy contains a plurality of cost terms, each cost term having a unique identifier and cost value, the reverse polish expression is composed of operands and operators, the operands are located on one side of the reverse polish expression, the operators are located on the other side of the reverse polish expression, and the priorities of the operators are arranged in a set arrangement order.
9. An electronic device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any one of claims 1 to 7 when the computer program is executed.
10. A computer storage medium storing a computer program, characterized in that the computer program when executed by a processor implements the steps of the method of any one of claims 1 to 7.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106648753A (en) * | 2016-11-23 | 2017-05-10 | 北京航天自动控制研究所 | Automatic criterion analysis method based on reverse Polish notation algorithm |
| CN109542406A (en) * | 2018-11-05 | 2019-03-29 | 清华大学 | Parallel implementation method and system for mode development |
| CN116150209A (en) * | 2023-02-20 | 2023-05-23 | 广州快决测信息科技有限公司 | Report computing system, method, electronic equipment and storage medium |
| CN117539868A (en) * | 2023-12-07 | 2024-02-09 | 中国平安人寿保险股份有限公司 | Binary tree-based financial service scenario generation method, device, system and medium |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106648753A (en) * | 2016-11-23 | 2017-05-10 | 北京航天自动控制研究所 | Automatic criterion analysis method based on reverse Polish notation algorithm |
| CN109542406A (en) * | 2018-11-05 | 2019-03-29 | 清华大学 | Parallel implementation method and system for mode development |
| CN116150209A (en) * | 2023-02-20 | 2023-05-23 | 广州快决测信息科技有限公司 | Report computing system, method, electronic equipment and storage medium |
| CN117539868A (en) * | 2023-12-07 | 2024-02-09 | 中国平安人寿保险股份有限公司 | Binary tree-based financial service scenario generation method, device, system and medium |
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