CN114239107A - Optimal pile machine number determination method based on matlab software genetic algorithm - Google Patents

Optimal pile machine number determination method based on matlab software genetic algorithm Download PDF

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CN114239107A
CN114239107A CN202111527494.5A CN202111527494A CN114239107A CN 114239107 A CN114239107 A CN 114239107A CN 202111527494 A CN202111527494 A CN 202111527494A CN 114239107 A CN114239107 A CN 114239107A
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pile
genetic algorithm
matlab software
construction
optimal
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叶钦繁
李光宁
郭凌勇
蒙锐
何宇
王峰
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Zhuhai Huafa Habitat Life Research Institute Co Ltd
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Zhuhai Huafa Habitat Life Research Institute Co Ltd
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Abstract

The invention discloses a method for determining the number of optimal pile machines based on matlab software genetic algorithm, which relates to the field of constructional engineering and has the technical key points that: firstly, solving by using nonlinear programming in the theory of operational research, obtaining an optimal solution by using a genetic algorithm (tool kit) based on MATLAB software, constructing a model of pile foundation construction, and solving the number of the optimal pile machines constructed on site according to the model of the foundation construction. The invention solves the problems by using the nonlinear programming in the theory of operational research, obtains the optimal solution by using the genetic algorithm (tool kit) based on MATLAB software, and can calculate the optimal pile driver number in site construction by the constraint conditions determined by the total construction period, the pile foundation number, the field area and the like.

Description

Optimal pile machine number determination method based on matlab software genetic algorithm
Technical Field
The invention relates to the field of constructional engineering, in particular to a method for determining the number of optimal pile machines based on matlab software genetic algorithm.
Background
The method is limited by factors such as construction site area, cost and the like, the pile machines cannot be infinitely arranged in the pile foundation construction, and the number of the pile machines in the traditional pile foundation construction approach is often determined according to engineering experience 'brain shooting bags'.
At present, how to combine engineering experience and accurate calculation to achieve reasonable pile machines, not only can meet construction requirements, but also can save total cost to the minimum. Therefore, it is necessary to invent an optimal pile driver number determination method based on matlab software genetic algorithm to solve the above problems.
Disclosure of Invention
The invention aims to provide a method for determining the number of optimal pile machines based on matlab software genetic algorithm, so as to solve the problems in the background technology.
In order to achieve the purpose, the invention provides the following technical scheme: the optimal pile machine quantity determination method based on MATLAB software genetic algorithm comprises the steps of firstly solving by using nonlinear programming in the operational research principle, and obtaining an optimal solution by using genetic algorithm (tool box) based on MATLAB software;
constructing a model of pile foundation construction, and solving the number of the optimal pile machines for site construction according to the model of the foundation construction;
the concrete model for building the pile foundation construction is as follows:
setting the requirement of a construction period as A, the number of tubular piles as B, the number of drilling and pouring pile foundations as C, and the floor area of a cell as D;
meanwhile, the daily cost of each static pile machine (construction pipe pile) is set as a, the daily construction quantity is set as b, and the working surface is set as c;
setting the daily cost of each bored pile driver (construction bored piles) as d, the daily construction quantity as e, and the working surface as f;
obtaining a formula according to a nonlinear programming in the operational research theory:
minZ＝aX1Y1+dX2Y2；
cX1+fX2＜D/2；
bX1eY1≥B；
X2Y2≥C；
X1≤g；X2≤h；
Y1≤A；Y2≤A；
wherein Z is the total cost, minZ is the lowest total cost, and X is the total cost1Number (integer) of static pile press, Y1Static pile machine construction days (integer), X2Number (integer) of bored pile-pouring machines, Y2The construction days (integer) of the drilling and pouring pile machine, and g and h are empirical values taken by constructors;
finally, X is calculated through matlab software genetic algorithm (tool box)1、Y1、X2、Y2And minZ results.
In the method for determining the number of the optimal pile machines based on the matlab software genetic algorithm, X is finally calculated each time through the matlab software genetic algorithm (tool box)1、Y1、X2And Y2The results are different, but the lowest value of the total cost of the objective function minZ is the same.
In the above method for determining the number of optimal pile machines based on matlab software genetic algorithm, the objective function in the matlab software genetic algorithm (tool box) is as follows: z is aX1Y1+dX2Y2。
In the above method for determining the number of optimal pile machines based on matlab software genetic algorithm, the nonlinear constraint conditions in the matlab software genetic algorithm (tool box) are as follows: cX1+fX2＜D/2、bX1eY1Not less than B and X2Y2≥C。
In the above method for determining the number of optimal pile machines based on matlab software genetic algorithm, the linear constraint conditions in the matlab software genetic algorithm (tool box) are as follows: x1≤g，X2≤h，Y1A and Y are not more than2≤A。
The invention has the technical effects and advantages that:
1. the invention solves the problem by applying the nonlinear programming in the operational research theory and obtains the optimal solution by applying the genetic algorithm (tool kit) based on MATLAB software;
2. the invention can calculate the optimal pile machine number in site construction through the constraint conditions determined by the total construction period, the pile foundation number, the field area and the like.
Drawings
FIG. 1 is a schematic diagram of the calculation of the objective function of the present invention.
FIG. 2 is a schematic diagram of the calculation of the nonlinear constraints of the present invention.
FIG. 3 is a schematic diagram of a first linear constraint of the present invention.
FIG. 4 is a schematic diagram of a second linear constraint of the present invention.
FIG. 5 is a schematic diagram of the algorithm calculation of the present invention.
Detailed Description
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.
Example 1
The invention discloses a method for determining the number of optimal piling machines based on MATLAB software genetic algorithm, which is shown in fig. 1-5, and comprises the steps of firstly solving by using nonlinear programming in the theory of operation and research, and obtaining an optimal solution by using genetic algorithm (tool kit) based on MATLAB software;
constructing a model of pile foundation construction, and solving the number of the optimal pile machines for site construction according to the model of the foundation construction;
the concrete model for building the pile foundation construction is as follows:
setting the requirement of a construction period as A, the number of tubular piles as B, the number of drilling and pouring pile foundations as C, and the floor area of a cell as D;
meanwhile, the daily cost of each static pile machine (construction pipe pile) is set as a, the daily construction quantity is set as b, and the working surface is set as c;
setting the daily cost of each bored pile driver (construction bored piles) as d, the daily construction quantity as e, and the working surface as f;
obtaining a formula according to a nonlinear programming in the operational research theory:
minZ＝aX1Y1+dX2Y2；
cX1+fX2＜D/2；
bX1eY1≥B；
X2Y2≥C；
X1≤g；X2≤h；
Y1≤A；Y2≤A；
wherein Z is the total cost, minZ is the lowest total cost, and X is the total cost1Number (integer) of static pile press, Y1Static pile machine construction days (integer), X2Number (integer) of bored pile-pouring machines, Y2The construction days (integer) of the drilling and pouring pile machine, and g and h are empirical values taken by constructors;
finally, X is calculated through matlab software genetic algorithm (tool box)1、Y1、X2、Y2And minZ result, and finally calculating X through matlab software genetic algorithm (tool box) each time1、Y1、X2And Y2The results are different, but the lowest value of the total cost of the objective function minZ is the same.
Wherein the objective function is: z is aX1Y1+dX2Y2The nonlinear constraint is: cX1+fX2＜D/2、bX1eY1Not less than BAnd X2Y2C is larger than or equal to C, and the linear constraint condition is as follows: x1≤g，X2≤h，Y1A and Y are not more than2≤A。
Example 2
The construction of a pile foundation in a certain community requires 60 days for a construction period, the number of pipe piles is 900, the number of drilling and pouring pile foundations is 600, and the floor area of the community is 40000m2Assuming that the cost of each static pile machine (construction pipe pile) is 1 ten thousand yuan per day, 10 static pile machines are constructed per day, and the working surface is 10 x 10 to 100m2(ii) a The cost of each bored pile machine (construction bored pile) is 0.4 ten thousand yuan per day, and the working surface is 6 × 6 ═ 36m2Construction was performed 1 per day.
Obtaining a formula according to a nonlinear programming in the operational research theory:
minZ＝X1Y1+0.4X2Y2；
100X1+36X2＜40000/2；
10X1Y1≥900；
X2Y2≥600；
X1less than or equal to 5 (empirical value); x2Less than or equal to 20 (empirical value);
Y1less than or equal to 60 (construction period constraint); y is2Less than or equal to 60 (construction period constraint);
wherein Z is the total cost, minZ is the lowest total cost, and X is the total cost1Number (integer) of static pile press, Y1Static pile machine construction days (integer), X2Number (integer) of bored pile-pouring machines, Y2The construction days (integer) of the drilling and pouring pile machine, and g and h are empirical values taken by constructors;
finally, the genetic algorithm (tool box) is calculated by matlab software:
X1＝3X2＝12Y1＝30Y250minZ 330 (ten thousand yuan)
Of course, the result of each genetic algorithm is not unique, and the second calculation yields:
X1＝2X2＝15Y1＝45Y240minZ 330 (ten thousand yuan)
But the lowest value of the total cost of the objective function minZ is the same.
Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that modifications may be made to the embodiments or portions thereof without departing from the spirit and scope of the invention.

Claims (5)

1. The optimal pile machine quantity determination method based on the MATLAB software genetic algorithm is characterized in that firstly, nonlinear programming in the operational research principle is used for solving, and a genetic algorithm (tool box) based on the MATLAB software is used for obtaining an optimal solution;
constructing a model of pile foundation construction, and solving the number of the optimal pile machines for site construction according to the model of the foundation construction;
the concrete model for building the pile foundation construction is as follows:
setting the requirement of a construction period as A, the number of tubular piles as B, the number of drilling and pouring pile foundations as C, and the floor area of a cell as D;
meanwhile, the daily cost of each static pile machine (construction pipe pile) is set as a, the daily construction quantity is set as b, and the working surface is set as c;
setting the daily cost of each bored pile driver (construction bored piles) as d, the daily construction quantity as e, and the working surface as f;
obtaining a formula according to a nonlinear programming in the operational research theory:
minZ＝aX1Y1+dX2Y2；
cX1+fX2＜D/2；
bX1eY1≥B；
X2Y2≥C；
X1≤g；X2≤h；
Y1≤A；Y2≤A；
wherein Z is the total cost, minZ is the lowest total cost, and X is the total cost1Number (integer) of static pile press, Y1Static pile machine construction days (integer), X2Number (integer) of bored pile-pouring machines, Y2The construction days (integer) of the drilling and pouring pile machine, and g and h are empirical values taken by constructors;
finally, X is calculated through matlab software genetic algorithm (tool box)1、Y1、X2、Y2And minZ results.
2. The method for determining the optimal number of pile machines based on matlab software genetic algorithm according to claim 1, wherein X is finally calculated each time through the matlab software genetic algorithm (tool box)1、Y1、X2And Y2The results are different, but the lowest value of the total cost of the objective function minZ is the same.
3. The method for determining the optimal number of pile machines based on matlab software genetic algorithm according to claim 1, wherein the objective function in the matlab software genetic algorithm (tool box) is as follows: z is aX1Y1+dX2Y2。
4. The method for determining the optimal number of pile machines based on matlab software genetic algorithm according to claim 1, wherein the nonlinear constraint conditions in the matlab software genetic algorithm (tool box) are as follows: cX1+fX2＜D/2、bX1eY1Not less than B and X2Y2≥C。
5. The method for determining the optimal number of pile machines based on matlab software genetic algorithm according to claim 1, wherein the linear constraint conditions in the matlab software genetic algorithm (tool box) are as follows: x1≤g，X2≤h，Y1A and Y are not more than2≤A。
CN202111527494.5A 2021-12-14 2021-12-14 Optimal pile machine number determination method based on matlab software genetic algorithm Pending CN114239107A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115033956A (en) * 2022-05-26 2022-09-09 珠海十字门中央商务区建设控股有限公司 Method for calculating budget engineering quantity of drainage plate based on drilling radiation drainage plate range diagram

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
王勇: "MATLAB中用遗传算法求解约束非线性规划问题", 哈尔滨商业大学学报(自然科学版), 31 August 2006 (2006-08-31) *
齐宝库 等: "多种配套作业机械优化配置方案求解方法研究", 沈阳建筑大学学报(自然科学版), 30 November 2007 (2007-11-30) *

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115033956A (en) * 2022-05-26 2022-09-09 珠海十字门中央商务区建设控股有限公司 Method for calculating budget engineering quantity of drainage plate based on drilling radiation drainage plate range diagram

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