Fireworks algorithm on basis of simulated annealing and Gauss disturbance

A fireworks algorithm and simulated annealing technology, applied in computing, computational models, biological models, etc., can solve the problems of poor stability and slow convergence speed of fireworks algorithm, so as to improve the convergence speed, calculation accuracy and stability, and improve the convergence speed. , the effect of increasing local search performance

Inactive Publication Date: 2017-05-31
SHENYANG AEROSPACE UNIVERSITY
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Problems solved by technology

[0013] In order to solve the problems that the fireworks algorithm also has slow convergence speed in the later stage, is easy to fall into a local optimal solution, and with the increase of position offset, the stability of the fireworks algorithm is poor, etc., the present invention proposes a firework algorithm based on simulated annealing and Gaussian perturbation Algorithm, this algorithm is better than Fireworks Algorithm (FWA), Standard Particle Swarm Optimization (SPSO) and Enhanced Fireworks Algorithm in terms of convergence speed, calculation accuracy and stability.

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  • Fireworks algorithm on basis of simulated annealing and Gauss disturbance
  • Fireworks algorithm on basis of simulated annealing and Gauss disturbance
  • Fireworks algorithm on basis of simulated annealing and Gauss disturbance

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Embodiment Construction

[0042] The existing fireworks algorithm has problems such as slow convergence speed in the later stage, easy to fall into local optimal solution, and with the increase of position offset, the stability of the fireworks algorithm is poor. The idea of ​​is introduced into the fireworks algorithm, and Gaussian disturbance is performed on some individual fireworks in the fireworks algorithm.

[0043] Step 1: Randomly assign values ​​to the positions of the fireworks, calculate the fitness value of the fireworks, and generate an initial population; Step 2: Set the number of fireworks N=5, the maximum number of sparks Max=40, the minimum number of sparks Min=2, and the function that needs to be solved Feasible domain D (different functions are different), the number of sparks of Gaussian variation N g = 5, the sum of explosion amplitudes A = 40 and the maximum number of evaluations of the function It max = 300000;

[0044] Step 3: Find the individual with the worst fitness value i...

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Abstract

The invention provides a fireworks algorithm on the basis of simulated annealing and Gauss disturbance. The fireworks algorithm has the advantages that simulated annealing algorithms and the fireworks algorithm are combined with one another, Gauss disturbance is carried out on fireworks with the poorest adaptive values, and accordingly an elitist which is better than the poorest fireworks individuals can be obtained; the probability of acceptance difference solutions is decreased along with gradual decrease of the temperatures, accordingly, the convergence performance of the fireworks algorithm can be improved, and the fireworks algorithm is obviously progressed in the aspects of convergence rates, computational accuracy and stability.

Description

Technical field: [0001] The invention relates to a firework algorithm based on simulated annealing and Gaussian perturbation. Background technique: [0002] The Fireworks Algorithm (FWA) is a swarm intelligence algorithm proposed by Professor Tan Ying in 2010, inspired by the explosion of fireworks in the night sky. FWA establishes a corresponding mathematical model by simulating the behavior of fireworks exploding in the air, and forms a parallel explosive search method by introducing random factors and selection strategies, and then develops into a global probability search method that can solve the optimal solution of complex problems. FWA is similar to the general swarm intelligence optimization algorithm. First, N fireworks are randomly initialized, and then each fireworks undergoes explosion and mutation operations, and the mapping rules are applied to ensure that the mutated individuals are still in the feasible region. Finally, the optimal fireworks are retained, and...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/00G06N3/00
CPCG06F17/00G06N3/006
Inventor 李席广韩守飞拱长青
Owner SHENYANG AEROSPACE UNIVERSITY
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