Hybrid gene operation method

An operation method and hybrid technology, applied in the field of calculation, can solve the problems of poor local search ability, low search efficiency, and time-consuming genetic algorithm of genetic algorithm, so as to improve the calculation efficiency and calculation results, and reduce the calculation time.

Pending Publication Date: 2019-08-23
PRECISION MACHINERY RES & DEV CENT
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Problems solved by technology

[0004] Although the genetic algorithm has a global search ability, it can search all the solutions in the solution space without falling into the problem of rapid decline of local solutions; however, the local search ability of the genetic algorithm is poor, which makes the simple gene...

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Embodiment Construction

[0030] In order to facilitate the description of the central idea of ​​the present invention expressed in the column of the above-mentioned summary of the invention, it is now expressed with specific embodiments. Various objects in the embodiments are drawn in proportions, sizes, deformations or displacements suitable for description, rather than in proportions of actual components, which will be described first.

[0031] see Figure 1 to Figure 3 , the present invention provides a hybrid gene computing method, which comprises the following steps:

[0032] Random step S1 : receiving a pursuit target 10 , and randomly generating a plurality of solution paths 20 for the pursuit target 10 . To further illustrate, in the embodiment of the present invention, for the pursuit target 10 that needs to be solved, a feasible solution that may meet the pursuit target 10 is randomly generated, and each solution path 20 is each feasible solution.

[0033] The first conversion step S2 : co...

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Abstract

The invention provides a hybrid gene operation method. The hybrid gene operation method comprises the following steps: receiving a pursuit target to randomly generate a plurality of solution paths; converting each solution path into a first adaptive target; comparing the first adaptive target with the pursuing target, and when a non-feasible solution is generated, performing a gene operation on the first adaptive target to generate a plurality of second adaptive targets; performing a single-point search operation and a comparison operation on the second adaptive target to generate a pluralityof first evaluation paths and second evaluation paths; converting each first evaluation path and each second evaluation path into a mixed adaptation target; and when the hybrid adaptation target conforms to the pursuing target, regarding the hybrid adaptation target as an optimization solution, thereby achieving the purposes of rapid convergence and reduction of calculation time.

Description

technical field [0001] The invention relates to a calculation method, in particular to a hybrid gene calculation method. Background technique [0002] Genetic Algorithm (GA) is a search algorithm used to solve optimization in computational mathematics. Genetic algorithm retains better offspring through the process of evolution and iteration of the initial parent. [0003] Genetic algorithm process: randomly generate n chromosomes at the beginning; use the fitness function to calculate the fitness value of all chromosomes; repeat the above steps 2 to 4 times, the actions of performing the aforementioned steps 2 to 4 times are called 1 iteration until convergence, wherein the condition for convergence is that the number of iterations reaches a certain number of times or all chromosomes are very similar. [0004] Although the genetic algorithm has the ability of global search, it can search out all solutions in the solution space without falling into the problem of rapid decli...

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Application Information

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IPC IPC(8): G06N3/12
CPCG06N3/126
Inventor 李宛玲
Owner PRECISION MACHINERY RES & DEV CENT
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