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Multi-objective optimization method and device, equipment and medium

A multi-objective optimization and objective technology, applied in multi-objective optimization, neural learning methods, design optimization/simulation, etc., can solve problems such as optimization problems that do not consider the multi-objective of the hybrid control system, and achieve reasonable control effects

Pending Publication Date: 2022-04-29
SOUTH UNIVERSITY OF SCIENCE AND TECHNOLOGY OF CHINA
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  • Application Information

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Problems solved by technology

Existing methods often only consider the design of the hybrid control system with fuel consumption as a single objective, and do not consider the multi-objective optimization problem of the hybrid control system

Method used

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  • Multi-objective optimization method and device, equipment and medium
  • Multi-objective optimization method and device, equipment and medium
  • Multi-objective optimization method and device, equipment and medium

Examples

Experimental program
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Effect test

example 1

[0096] Example 1, specifically, the design of the power control system of a hybrid electric vehicle usually needs to consider some parameters and rules. Specifically, the parameter definitions are shown in Table 1.

[0097] Table 1

[0098]

[0099] The specific rules of hybrid power control are as follows:

[0100] Rule 1: If the speed is below Voff, turn off the internal combustion engine.

[0101] Rule 2: If the battery state of charge is greater than SOCmax, then turn off (Note: SOCmax is not the maximum value of the battery state of charge, here only indicates the battery state of charge level, and its state value makes the battery no longer charge.).

[0102] Rule 3: If the battery state of charge is less than SOCmin, turn off the internal combustion engine.

[0103] Rule 4: If the internal combustion engine is on and the speed is less than V1, do action 1.

[0104] Rule 5: If the internal combustion engine is on and the speed is between V1 and V2, do action 2.

...

example 2

[0133] Example 2, refer to Figure 7 , the method in Example 2 includes:

[0134] Population initialization, specifically, random initialization generates 100 individuals satisfying the constraints and the upper and lower bounds, that is, the initial solution set.

[0135] Judging whether the number of iterations of the current population cycle satisfies the preset condition: specifically, the preset condition is that the number of iterations of the current population cycle is 1, 5, 10, 15 until the end of the cycle, and the total number of iterations of the population cycle can be 100.

[0136] When the preset conditions are not met, the initial solution set is crossed and mutated to obtain the initial offspring and the target preference solution set is updated according to the initial offspring.

[0137] When the preset conditions are met, the offspring is generated based on the generative confrontation network, and the preference offspring is obtained, and the target prefe...

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Abstract

The invention discloses a multi-objective optimization method, apparatus and device, and a medium. The method comprises the steps of obtaining a population and a preset optimization objective; initializing the population according to a preset optimization target to obtain an initial solution set; obtaining a preset reference coefficient, and performing preference classification on the initial solution set according to the preset reference coefficient to obtain a first preference solution set and a first non-preference solution set; training a preset generative adversarial network according to the first preference solution set and the first non-preference solution set to obtain a first preference filial generation; and performing environment selection according to the initial solution set and the first preference filial generation to obtain a target preference solution set. According to the multi-objective optimization method obtained by introducing expert knowledge and the generative adversarial network, the problem of multi-objective optimization is effectively solved. Particularly, in the face of the multi-objective optimization problem in the hybrid power control system, the multi-objective optimization is effectively realized, so that the control of the hybrid power control system is more reasonable.

Description

technical field [0001] The present invention relates to the field of computer technology, in particular to a multi-objective optimization method, device, equipment and medium. Background technique [0002] In industrial production and life, many problems are composed of multiple goals that conflict and influence each other. People often encounter optimization problems that make multiple objectives as optimal as possible in a given area at the same time, that is, multi-objective optimization problems. In the design of hybrid power control system, the designer's main goal is to reduce fuel consumption. However, in addition to fuel consumption, factors such as driving experience, noise, vibration and harshness also need to be considered. Existing methods often only consider the design of the hybrid control system with fuel consumption as a single objective, and do not consider the multi-objective optimization problem of the hybrid control system. Contents of the invention ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F30/27G06F30/15G06K9/62G06N3/00G06N3/04G06N3/08G06F111/06G06F119/10
CPCG06F30/27G06F30/15G06N3/006G06N3/08G06F2111/06G06F2119/10G06N3/045G06F18/214G06F18/241
Inventor 程然侯章禄柏卉林剑清
Owner SOUTH UNIVERSITY OF SCIENCE AND TECHNOLOGY OF CHINA
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