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Improved optimization algorithm based on virtual fitness and Pareto solution stratification

An optimization algorithm and fitness technology, applied in computing, computing models, data processing applications, etc., can solve problems such as the loss of the best individual, the inability of individuals to expand, and the inability to evenly distribute, so as to improve computing speed and robustness, reduce Complexity, effects of loss prevention

Inactive Publication Date: 2018-08-17
NANJING INST OF TECH
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Problems solved by technology

Only by limiting the capacity of the external file will cause the individuals in the quasi-Pareto domain to not expand to the entire Pareto domain, nor can they be evenly distributed in the Pareto domain, which may lead to the loss of the best individual
Using the adaptive grid method to evaluate the density greatly increases the amount of calculation, and it cannot make the solutions in the external archive evenly distributed in the Pareto domain

Method used

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  • Improved optimization algorithm based on virtual fitness and Pareto solution stratification
  • Improved optimization algorithm based on virtual fitness and Pareto solution stratification
  • Improved optimization algorithm based on virtual fitness and Pareto solution stratification

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Embodiment Construction

[0063] The technical solution of the present invention will be specifically described below in conjunction with the accompanying drawings.

[0064] The present invention provides a kind of improved optimization algorithm based on virtual fitness and Pareto solution set layering, virtual fitness and Pareto solution set layering are used to improve the firefly algorithm, and proceed as follows:

[0065] Step 1. Algorithm initialization, including setting algorithm parameters, initializing firefly positions, initializing firefly brightness, and performing non-dominated sorting on the initialized population;

[0066] Step 2. Update the position of fireflies according to the Pareto dominance relationship;

[0067] Step 3. Update firefly brightness;

[0068] Step 4, updating and maintaining external files;

[0069] Step 5, output the optimal solution.

[0070] Specifically, the above step 1 is carried out as follows:

[0071] I. Set algorithm parameters, including: population si...

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Abstract

The invention discloses an improved optimization algorithm based on virtual fitness and Pareto solution stratification. The method comprises: step one, carrying out algorithm initialization; step two,updating a firefly position according to a Pareto dominance relationship; step three, updating the firefly Brightness; step four, updating and maintaining an external file; and step five, outputtingan optimal solution. According to the invention, because the Pareto solution stratification method and concept of virtual fitness are introduced into the firefly initialization stage and the positionand brightness updating stage, son the one hand, the complexity of the non-inferior solution sorting calculation is reduced and the operation speed is increased; and on the other hand, individuals inthe quasi Pareto domain can be extended to the whole Pareto domain uniformly, so that losing of an optimal individual is avoided and a phenomenon that the result falls into local optimization is avoided.

Description

technical field [0001] The invention relates to the field of multi-objective optimization algorithms, in particular to an improved optimization algorithm based on virtual fitness and Pareto solution set layering. Background technique [0002] In most fields of engineering and science, many problems are multi-objective optimization problems, that is, there are multiple conflicting goals, and what method can be used to obtain the optimal solution of such problems has always attracted the attention of the academic and engineering circles. Multi-objective optimization is different from single-objective optimization. In multi-objective optimization problems, in most cases, the improvement of one objective may cause the performance of other objectives to decrease. It is impossible to achieve the optimal performance of multiple objectives at the same time. Coordinate trade-offs and compromises among the objectives to make all objective functions as optimal as possible, and the opti...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06N3/00
CPCG06Q10/04G06N3/006
Inventor 刘海涛许伦张潮
Owner NANJING INST OF TECH
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