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Tire vulcanization workshop energy consumption optimization scheduling method based on hybrid genetic algorithm

A hybrid genetic algorithm and tire vulcanization technology, which is applied in the field of optimal scheduling of tire vulcanization workshop energy consumption based on hybrid genetic algorithm, can solve problems such as unfavorable industrial production, complex process, and many parameters of genetic algorithm

Active Publication Date: 2015-02-25
GUANGDONG UNIV OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the genetic algorithm needs to set many parameters, the process is complicated, and the solution efficiency is slow. The solution efficiency is related to the selection of the initial solution.
[0004] Both Chinese patent 201410093206.3 and Chinese pa

Method used

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  • Tire vulcanization workshop energy consumption optimization scheduling method based on hybrid genetic algorithm
  • Tire vulcanization workshop energy consumption optimization scheduling method based on hybrid genetic algorithm
  • Tire vulcanization workshop energy consumption optimization scheduling method based on hybrid genetic algorithm

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Effect test

Embodiment 1

[0075] See attached figure 1 , a step-by-step flow chart of a hybrid genetic algorithm-based method for optimal scheduling of energy consumption in a tire vulcanization workshop, which specifically includes the following steps:

[0076] Step S1: Construct the optimal scheduling model of energy consumption in the tire vulcanization workshop, and determine the minimum production cost E of machined tires min , the E min It consists of two parts, including workpiece delay penalty cost and machine energy consumption cost. The objective function is shown in formula (1.1):

[0077] E min = Σ i = 1 n β i · ...

Embodiment 2

[0136] In order to verify the effectiveness of a hybrid genetic algorithm-based energy optimization scheduling method for tire vulcanization workshops proposed by the present invention, the present embodiment uses Matlab7.1 simulation software, and the CPU is Intel Core22.16GHz, and the memory is 2G on a computer. Simulation test.

[0137] The main factors that affect the performance of the algorithm are: the arrival time of the workpiece, the number of workpieces n, the coefficient of the delivery time of the workpiece, the ratio of unit energy consumption (the ratio of the machine warm-up energy consumption per unit time to the machine waiting energy consumption per unit time) and the number of machines, among which Assuming a normal distribution of workpiece arrival times: Poisson distribution: λ i = Σ j = 1 ...

Embodiment 3

[0140] Further, in order to verify the effectiveness and practicability of the technical solution of the present invention, the technical solution proposed by the present invention is used in a rubber tire enterprise. There are currently 100 workpieces to be processed, and the production plan for 100 workpieces to be processed is arranged (see Table 1 for data). There are 12 vulcanizing machines in total. Table 2 shows the energy consumption cost rate of each machine in three states, and Table 3 Indicates the processing time of each workpiece on the machine, arrival time, delivery date and late penalty rate; Table 4 is the workpiece processing sequence table based on the LPP-GA algorithm; Table 5 is the LPP-GA genetic algorithm and random-GA (Ordinary Genetic Algorithm) Results Comparison Table.

[0141] Table 1 Production plan for workpieces to be processed

[0142]

[0143]

[0144]

[0145]

[0146] Table 2 Energy consumption cost rates in three operating state...

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Abstract

The invention discloses a tire vulcanization workshop energy consumption optimization scheduling method based on the hybrid genetic algorithm, and belongs to the technical field of tire vulcanization workshop scheduling and production energy conservation. The method includes the procedure steps of conducting mathematical modeling, conducting matrix type coding on machines and machined workpieces, conducting population initialization on the basis of the LPP rules, determining the fitness function F(i), conducting selective operation on individuals in a roulette mode, selecting the individuals meeting the conditions and conducting interlace operation according to the probability Pc, selecting the individuals meeting the conditions and conducting mutation operation according to the probability Pm, conducting adaptive value evaluation, and judging whether the conditions are met or not. The method is simple in procedure, the speed for obtaining the optimal scheduling scheme is increased by 5 times, the production cost of each machine is reduced by 8.7%, energy can be saved for enterprises, the production cost can be reduced for enterprises, and timely delivery can be ensured for enterprises.

Description

technical field [0001] The invention belongs to the technical field of tire vulcanization workshop scheduling and production energy saving, and in particular relates to a hybrid genetic algorithm-based energy consumption optimization scheduling method for tire vulcanization workshops. Background technique [0002] The tire industry is a traditional labor-intensive and technology-intensive high-energy manufacturing industry. Although my country's tire manufacturing industry started late, it has developed rapidly. Since 2004, my country's tire production and export volume have leapt to the first place in the world. However, since 2011, the increase in the price of energy and raw materials has raised the production cost of tire manufacturers, which has put my country's tire industry in a difficult situation. According to the January 2011 report of the Tire Branch of the China Rubber Industry Association, its 45 member companies had a deficit of 37.2%, and their profits fell by...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/04G06N3/12
CPCY02P90/30G06Q10/04G06N3/12G06Q50/04
Inventor 杨海东唐万和张沙清杨波黎展滔
Owner GUANGDONG UNIV OF TECH
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