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An interactive multi-objective optimization decision-making method based on stochastic automata

A technology of multi-objective optimization and decision-making method, which is applied in the field of interactive multi-objective optimization and decision-making based on stochastic automata, and achieves the effect of wide application prospects, speeding up the process of multi-objective optimization, and significant engineering practical value.

Inactive Publication Date: 2019-02-15
SOUTH CHINA UNIV OF TECH
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0005] The purpose of the present invention is to solve the above-mentioned defects in the prior art and provide an interactive multi-objective optimization decision-making method based on stochastic automata. This method can not only effectively integrate the preference of the decision maker, but also consider the game It is suitable for solving complex multi-objective optimization decision-making problems

Method used

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  • An interactive multi-objective optimization decision-making method based on stochastic automata
  • An interactive multi-objective optimization decision-making method based on stochastic automata
  • An interactive multi-objective optimization decision-making method based on stochastic automata

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Embodiment

[0049] like figure 1 As shown, in this embodiment, the DTLZ2 standard test function is used as the simulation object and the number of selected targets is three to specifically illustrate the stochastic automata-based interactive multi-objective optimization decision-making method of the present invention.

[0050] minimize f 1 (x)=(1+g(x M ))cos(π / 2x 1 )cos(π / 2x 2 ),

[0051] minimize f 2 (x)=(1+g(x M ))cos(π / 2x 1 )sin(π / 2x 2 ),

[0052] minimize f 3 (x)=(1+g(x M ))sin(π / 2x 1 ),

[0053] 0≤x i ≤1, i=1,2,...,n,

[0054]

[0055] Step S1. Determine the range of variation of each objective function value. In this embodiment, each objective is completely opposite to each other. Through the single-objective optimization of each objective function under the given constraints, the lower limit values ​​are all calculated as 0. The upper limit values ​​of the objective functions are all set to 1, so the variation ranges of the three objective functions are all in th...

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Abstract

The invention discloses an interactive multi-objective optimization decision-making method based on a stochastic automata. The Pareto solution set is obtained by multi-objective optimization of the objective set in the given variation range, which is used as the candidate solution set. Combined with the decision-maker's preference, the reference point of multi-objective solution set is obtained byusing the learning behavior of variable structure stochastic automata and the game model of automata. The scalar function is combined with the existing candidate solution set and reference point to select the most preferred candidate solution at this time. By updating the upper limit of each objective function, the output set of stochastic automata is updated to get a new reference point, and thetarget set is optimized in the changed range after updating, and the final scheme is obtained. The invention effectively integrates the preference of the decision maker and considers the characteristics of the game among the objectives, and has remarkable engineering practical value and wide application prospect.

Description

technical field [0001] The invention relates to the technical field of multi-objective optimization decision-making, in particular to an interactive multi-objective optimization decision-making method based on stochastic automata. Background technique [0002] In many practical problems, such as engineering design, economics, management, military and other fields, it is often difficult to judge the quality of a scheme with one indicator, but it needs to be compared with multiple objectives, which is essentially a multi-objective optimization problem. However, these goals are sometimes not coordinated or even contradictory, so it is impossible to have a unique optimal solution to make these goals optimal at the same time. What is obtained through multiple objectives is a set, which is called the Pareto solution set, and each solution in the solution set cannot be mutually dominated. But in the actual application environment, only the only solution can be implemented, which r...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04
CPCG06Q10/04
Inventor 吴青华郑杰辉秦颖婕
Owner SOUTH CHINA UNIV OF TECH
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