CN105808848A - Method for processing discrete standard optimization design variable - Google Patents

Method for processing discrete standard optimization design variable Download PDF

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Publication number
CN105808848A
CN105808848A CN201610131016.5A CN201610131016A CN105808848A CN 105808848 A CN105808848 A CN 105808848A CN 201610131016 A CN201610131016 A CN 201610131016A CN 105808848 A CN105808848 A CN 105808848A
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value
variable
subinterval
interval
optimization
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李金平
曹学鹏
顾海荣
叶敏
张军
徐信芯
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Changan University
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Changan University
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/10—Geometric CAD
    • G06F30/17—Mechanical parametric or variational design

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  • General Engineering & Computer Science (AREA)
  • Computational Mathematics (AREA)
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Abstract

The invention discloses a method for processing discrete standard optimization design variable for mechanical structure optimization design. The method comprises following steps of 1, assuming that there is a design variable x and an optimization variable y, wherein xi stands for the ith value of the design variable x, and xij stands for the jth value of the optimization variable y corresponding to the xi; 2, assuming that there is an interval [0,s]; equally dividing the interval [0,s] into s subintervals interval [0,1 ), [1,2 ), [2,3 ),..., [s-1,s], wherein each subinterval is equipped with a corresponding value of the optimization variable y; 3, generating a random number rand; determining the subinterval in which the random number falls, wherein if the rand falls in the subinterval [s-1,s], the xij value in the subinterval [s-1,s] is the value of the optimization variable y. According to the method, the verification processes in the prior art are reduced, the optimization efficiency is improved, and the relevance problem of the discrete standard design variable is solved.

Description

A kind of method processing discrete normalized optimization design variable
Technical field
The present invention relates to Optimal Structure Designing technical field, be specifically related to the discrete normalized design of a kind of process The method of variable, for Optimal Design of Mechanical Structure.
Background technology
The optimization problem of discrete variable usually can be run in Optimal Structure Designing, if not phase between design variable Closing, definition only need to input centrifugal pump when optimizing design variable；If it is relevant between design variable, then also Dependency between variable to be considered.Structural analysis at present, it is generally required to finite element analysis software, sets up parameter The real constant of input block is needed, as limited configurations meta software ANSYS is utilizing pipe unit when changing model When Pipe16 carries out stress and strain model, need two real constants of input pipe unit, the i.e. external diameter of pipe unit and Wall thickness；When carrying out dimensionally-optimised to structure, external diameter and wall thickness just become design variable, and the two Having relatedness between variable, its reason is that steel pipe sizes is all standardized, and same external diameter may be corresponding Different wall thickness.If do not consider the relatedness of external diameter and wall thickness when definition optimizes design variable, the most defeated Enter the centrifugal pump of external diameter and wall thickness, a lot of false solution will be produced.Such as, main chord external diameter have 57mm, 65mm, 76mm, 85mm and 95mm five kinds selection, wall thickness has 4mm, 5mm, 5.5mm and 6.5mm Four kinds of selections, after optimization, optimal solution is external diameter 85mm, wall thickness 5mm, and this optimum results and existing steel Pipe size is not mated, and does not has the steel pipe of correspondence, and this optimal solution does not has in the span of design variable, Therefore be false solution.It is clear that increasing along with outer diameter of steel pipes and wall thickness number, utilize this process side Formula optimization external diameter and wall thickness, and the probability that can meet corresponding relation can be substantially reduced, thus cause optimizing Inefficiency, Optimized Iterative time increase, in some instances it may even be possible to can not get optimal solution.
Treating method to this situation is that design variable is considered as continuous variable at present, and it is right to optimize after terminating Optimal solution carries out rounding process or to take the standardized value near optimal solution be optimum results, then checks this optimization Whether result meets constraints；But this treating method needs to increase extra proof procedure, if setting Meter variable is more, and the optimum results after rounding is unsatisfactory for constraints, then need re-optimization or again justify Whole, cause optimizing efficiency more low, can't ensure that optimum results is optimal solution simultaneously.
Summary of the invention
In order to overcome defect present in prior art, it is an object of the invention to provide a kind of process discrete The method of standardized designs variable, this approach reduces proof procedure of the prior art, improves excellent Change efficiency.
In order to achieve the above object, the present invention is solved by the following technical solutions.
A kind of method processing discrete normalized optimization design variable, it is characterised in that comprise the following steps:
, if there is a design variable x and an optimized variable y, x in step 1iRepresent the of described design variable x I value, xijRepresent corresponding described xiUnder the jth value of optimized variable y, i, j are respectively nature Number；
Step 2, is provided with one interval [0, s], and wherein, s is the value of design variable x correspondence optimized variable y Number, then interval [0, s] is divided into s subinterval [0,1), [1,2), [2,3) ..., [s-1, s], and Each subinterval has the value of an optimized variable y corresponding with this subinterval；
Step 3, produces a random number rand, determines the subinterval that random number rand falls into, if at random Number rand falls into subinterval [s-1, s], the then x in subinterval, place [s-1, s]ijValue is optimized variable y Value.
Described random number rand is uniformly distributed in described interval [0, s] upper obedience.
Compared with prior art, the invention has the beneficial effects as follows: the present invention processes discrete normalized design and becomes The method of amount determines by randomly choosing when each iteration optimization, it is not necessary to justify optimum results Whole or to take the standardized value near optimal solution be optimum results, then optimum results is tested, so locate Reason method decreases proof procedure, improves optimization efficiency, solves the pass of discrete normalized design variable Connection sex chromosome mosaicism.
Detailed description of the invention
Below in conjunction with specific embodiment, the present invention is described in further detail, but following example are not made For limiting the scope of the invention.
Table 1
Shown in reference table 1, table 1 is the discrete heat sources value list of the present embodiment, is main chord External diameter and wall thickness data, external diameter and wall thickness be all standardization steel pipe, external diameter x represents, wall thickness y Represent, xiRepresent the value of external diameter x, xijRepresenting the value of wall thickness y, wall thickness corresponding to each external diameter is not Just the same, there is monodrome also to have many-valued.
Being provided with one interval [0, s], s is the number of the value of wall thickness y corresponding for external diameter x；
Interval [0, s] is divided into s subinterval [0,1), [1,2), [2,3) ..., [s-1, s], wherein every height Interval has and value x of only value and wall thickness yijCorresponding；
Being provided with a random number rand, random number rand ∈ [0, s], from subinterval, random number rand place [s-1, s] chooses the value of wall thickness y.
When optimization method determines value x of the external diameter x of described main chordiAfter, if the wall thickness y's of its correspondence takes Value xijWhen being a value (s=1), then wall thickness y is this value；If value x of external diameter xiCorresponding wall thickness y Value xijWhen having multiple value (s ＞ 1), randomly located method can be used to determine each iteration optimization Time xijValue.
Concrete operation method is as follows:
(1) as i=1, value x of the external diameter x of main chordiFor 57mm, its corresponding wall thickness y Value xijHave and only one, i.e. s=1, then value x of wall thickness yijFor 4mm.
(2) as i=2, value x of the external diameter x of main chordiFor 65mm, its corresponding wall thickness y Value xijHave and only one, i.e. s=1, then value x of wall thickness yijFor 4mm.
(3) as i=3, value x of the external diameter x of main chordiFor 76mm, its corresponding wall thickness y Value xijThere are three, then value x of wall thickness yijFor can value be 4mm, 5.5mm, 6.5mm, i.e. S=3.
Now, be provided with one interval [0,3], then subinterval be [0,1), [1,2) and [2,3]；
If there being a random number rand, random number rand is uniformly distributed in interval [0, s] upper obedience, when with Machine number rand fall into interval [0,1) interior time, then value x of wall thickness yijFor 4mm；If random number rand falls into Interval [1,2) interior time, then value x of wall thickness yijFor 5.5mm, if random number rand falls in interval [2,3] Time, then value x of wall thickness yijFor 6.5mm；
Might as well set random number rand=1.234, then random number rand fall into interval [1,2) in, so secondary iteration xij Take 5.5mm to be optimized.
(4) as i=4, value x of the external diameter x of main chordiFor 85mm, its corresponding wall thickness y Value xijHave and only one, i.e. s=1, then wall thickness xijValue is 4mm.
(5) as i=5, value x of the external diameter x of main chordiFor 95mm, its corresponding wall thickness y Value xijThere are two, then value x of wall thickness yijFor can value be 4mm, 5mm, i.e. s=2.
Now, be provided with one interval [0,2], then subinterval be [0,1), [1,2]；
If there being a random number rand, random number rand is uniformly distributed in interval [0, s] upper obedience, when with Machine number rand fall into interval [0,1) interior time, then value x of wall thickness yijFor 4mm；If random number rand falls into When interval [1,2] is interior, then value x of wall thickness yijFor 5mm；
Random number rand=1.234 might as well be set, then in random number rand falls into interval [1,2], so secondary iteration xij Take 5mm to be optimized.
This processing method can guarantee that value x of wall thickness yijWithout departing from its span, it is ensured that steel pipe Corresponding relation between external diameter and wall thickness.
Obviously, those skilled in the art can carry out various change and modification without deviating from this to the present invention The spirit and scope of invention.So, if these amendments of the present invention and modification belong to right of the present invention and want Ask and within the scope of equivalent technologies, then the present invention is also intended to comprise these change and modification.

Claims (2)

1. the method processing discrete normalized optimization design variable, it is characterised in that include following step Rapid:
, if there is a design variable x and an optimized variable y, x in step 1iRepresent the of described design variable x I value, xijRepresent corresponding described xiUnder the jth value of optimized variable y, i, j are respectively nature Number；
Step 2, is provided with one interval [0, s], and wherein, s is the value of design variable x correspondence optimized variable y Number, then interval [0, s] is divided into s subinterval [0,1), [1,2), [2,3) ..., [s-1, s], and Each subinterval has the value of an optimized variable y corresponding with this subinterval；
Step 3, produces a random number rand, determines the subinterval that random number rand falls into, if at random Number rand falls into subinterval [s-1, s], the then x in subinterval, place [s-1, s]ijValue is optimized variable y Value.
The method of process the most according to claim 1 discrete normalized optimization design variable, its feature Being, described random number rand is uniformly distributed in described interval [0, s] upper obedience.
CN201610131016.5A 2016-03-08 2016-03-08 Method for processing discrete standard optimization design variable Pending CN105808848A (en)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106777626A (en) * 2016-12-07 2017-05-31 西安科技大学 A kind of trusses with discrete variables Multidisciplinary systems Optimization Design
CN108647321A (en) * 2018-05-11 2018-10-12 长安大学 A kind of intelligence multi-source heterogeneous manufacture big data integrated model in workshop and semantic computation method

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106777626A (en) * 2016-12-07 2017-05-31 西安科技大学 A kind of trusses with discrete variables Multidisciplinary systems Optimization Design
CN106777626B (en) * 2016-12-07 2019-02-15 西安科技大学 A kind of trusses with discrete variables Multidisciplinary systems optimum design method
CN108647321A (en) * 2018-05-11 2018-10-12 长安大学 A kind of intelligence multi-source heterogeneous manufacture big data integrated model in workshop and semantic computation method
CN108647321B (en) * 2018-05-11 2021-10-01 长安大学 Tree-shaped intelligent workshop manufacturing big data integrated modeling and semantic calculation method

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