Single target optimization problem method integrating explosion strategy, opposition-based learning and bat algorithm and system

A technology of reverse learning and bat algorithm, applied in the field of data processing, can solve problems such as premature convergence and local optimization, and achieve the effect of avoiding local optimal solutions, high efficiency, and improving local exploration capabilities.

Pending Publication Date: 2018-10-23
WUHAN UNIV
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Problems solved by technology

This method solves the problems of easily falling into local optimum and premature convergence in single-objective optim

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  • Single target optimization problem method integrating explosion strategy, opposition-based learning and bat algorithm and system
  • Single target optimization problem method integrating explosion strategy, opposition-based learning and bat algorithm and system
  • Single target optimization problem method integrating explosion strategy, opposition-based learning and bat algorithm and system

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[0074] In order to facilitate those of ordinary skill in the art to understand and implement the invention, the present invention will be described in further detail below in conjunction with the accompanying drawings and examples. It should be understood that the examples described here are only used to illustrate and explain the present invention, and are not intended to limit the present invention. .

[0075] please see figure 1 , the technical solution adopted by the present invention is: a single-objective optimization problem method combining explosion strategy, reverse learning and bat algorithm, comprising the following steps:

[0076] Step 1: Initialize the function parameters of the problem, initialize the population size N, and search the frequency range of the pulse [f min , f max ], the maximum pulse frequency r 0 , the maximum pulse sound intensity A, the sound intensity attenuation coefficient α, the frequency increase coefficient γ, the maximum number of ite...

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Abstract

The invention relates to a bat algorithm and a system, belonging to the field of data processing, and particularly relates to a single target optimization problem method integrating explosion strategy, opposition-based learning and bat algorithm and a system. In the optimization process, the opposition-based population of each bat in the bat algorithm is obtained by opposition-based learning, andthe elite selection is performed on the two populations, thus the diversity of the population is increased, and the global search ability is improved, the local optimal solution is avoided, the explosion strategy is added during the flight process, thus the local exploration ability of the algorithm is improved, and the optimal solution is more accurately searched. Through the simulation test of 12 typical test functions and knapsack problems, it is proved that DGOBA has higher efficiency for solving continuous and discrete optimization problems.

Description

technical field [0001] The invention relates to a single-objective optimization method, a bat algorithm, an explosion strategy and a reverse learning strategy of a firework explosion algorithm, and belongs to the field of data processing, and specifically relates to a single-objective optimization problem method combining an explosion strategy, reverse learning and a bat algorithm and system. Background technique [0002] Bat Algorithm (BA) is a novel optimization algorithm developed by simulating the biological characteristics of bats searching and preying on prey through ultrasonic waves in nature. It was first proposed by Yang X.S. The algorithm has the characteristics of simple model, fast convergence speed, potential parallelism and distribution, etc. Similar to other meta-heuristic algorithms, the basic bat algorithm is also easy to fall into local optimum, premature convergence, and slow convergence speed in the later period. question. [0003] Fireworks Explosion A...

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Application Information

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IPC IPC(8): G06N3/00G06N3/08
CPCG06N3/006G06N3/084
Inventor 何发智雍嘉诗何黎俊李浩然陈壹林
Owner WUHAN UNIV
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