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An optimization method and optimization system for patrolling the shortest path

A technology of the shortest path and optimization method, which is applied in the directions of data processing application, prediction, calculation, etc., can solve problems such as stable production, product quality risks, failure to discover hidden dangers of production site accidents in time, and reduce production quality inspection problems, The effect of reducing inspection time and improving work efficiency

Active Publication Date: 2021-12-03
SHANGHAI MICRO VISION TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

On-site inspections have multiple points. If there is no effective and scientific on-site inspection and supervision mechanism at the management level, and hidden accidents and weak links in the production site are not discovered in time, it will bring risks to stable production and product quality.

Method used

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  • An optimization method and optimization system for patrolling the shortest path
  • An optimization method and optimization system for patrolling the shortest path
  • An optimization method and optimization system for patrolling the shortest path

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Experimental program
Comparison scheme
Effect test

Embodiment 1

[0075] In this embodiment, 10, 14, 20, 40, and 80 inspection points generated randomly, and two-dimensional or three-dimensional data are used as experimental objects.

[0076] Step 1. Mark the coordinates of the points where all inspection processes are located, in which a sequence E of 14 rows and 2 columns is randomly generated, as shown in Table 1; a sequence F of 32 rows and 3 columns is randomly generated, as shown in Table 2.

[0077] Table 1, Sequence E

[0078] serial number Abscissa Y-axis 1 99.21 72.97 2 10.78 80.04 3 39.56 5.61 4 20.24 77.73 5 85.14 61.45 6 44.82 16.18 7 53.45 70.79 8 86.75 4.74 9 53.35 0.09 10 82.47 25.07 11 54.84 84.40 12 25.20 86.52 13 17.21 65.55 14 0.15 30.25

[0079] Table 2, Sequence F

[0080]

[0081]

[0082] Step 2: Generate an initial path with an initial population of 100×32 and 100×14, that is, the inspection points are 32 and ...

Embodiment 2

[0101]On the computer, the simulated person randomly walks through 14 inspection points 300 times by feeling, and calculates the distances of all the inspection points each time to be h1, h2...h300, such as Figure 9 shown. Calculate the average of the distance traveled 300 times, the simulated walking path is as follows Figure 10 As shown, by comparing the average distance H2=59.55 traveled by human feeling with the distance H1=29.3405 optimized by genetic algorithm, the optimized distance is 51% lower than the distance traveled by human feeling.

Embodiment 3

[0103] Randomly generate data E10 with 10 rows and 2 columns on the computer, randomly generate data E20 with 20 rows and 2 columns, randomly generate data E40 with 40 rows and 2 columns, and randomly generate data E80 with 80 rows and 2 columns, and perform these 4 sets of data respectively Based on the path optimization of the genetic algorithm, and the average value of the total distance obtained by simulating 300 times of walking by feeling, the distances obtained respectively are compared and analyzed, as shown in Table 3.

[0104] Table 3. Comparative analysis table based on different numbers of inspection points in two-dimensional plane

[0105] serial number Inspection point go by feeling Genetic Algorithm Optimization absolute reduction Route descent after optimization 1 10 471.61 263.82 207.79 44.06％ 2 20 1011.90 396.50 615.40 60.82％ 3 40 1980.80 536.64 1444.16 72.91％ 4 80 4032.00 1722.57 2309.43 57.28％

[0...

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Abstract

The present invention provides an optimization method and an optimization system for the shortest path of inspection, including marking the coordinates of all inspection points in N-dimensional space; according to the number of inspection points, the initial path whose initial population is NIND is obtained based on a genetic algorithm; according to Generate the initial path, construct the objective function of each path; construct the fitness function of the initial path; calculate the sum of the paths of all the inspection subsets in the inspection set, and calculate the relative fitness of each inspection subset Based on the genetic algorithm, the initial population for selection, crossover, and mutation is determined according to the fitness function, so as to gradually obtain the shortest path. The optimization method and optimization system of the shortest inspection path of the present invention can find a path to traverse all the points among several inspection points, and the total distance is the smallest, thereby reducing the inspection time of the factory site, improving work efficiency, and maximizing Reduce the occurrence of production quality inspection problems.

Description

technical field [0001] The invention relates to a path optimization method and an optimization system, in particular to an optimization method and an optimization system for patrolling the shortest path. Background technique [0002] Since the establishment of the restructuring, the general physical processing factories have insisted on quality improvement and continuously optimized the management of the factory to ensure product quality. At present, various management measures of the factory have been relatively perfect, and reasonable norms and systems have been formed for quality control and inspection requirements. [0003] However, in the implementation process of various norms and systems, quality fluctuations caused by various reasons occur from time to time, which has brought considerable losses to the enterprise. Most of the reasons are the slack and incomplete implementation of existing norms, documents, and standards, which put forward higher requirements for on-...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q10/04
CPCG06Q10/047
Inventor 张军詹映薛庆逾石超
Owner SHANGHAI MICRO VISION TECH