Engineering constraint parameter optimization method based on improved chaotic bee colony algorithm

Abstract

An engineering constraint parameter optimization method based on an improved chaotic bee colony algorithm is a novel optimization algorithm of bionics, and is a mode method for determination and selection by means of honeybee colonies to search routes of honey sources. A conventional engineering constraint parameter optimization method has many unsatisfying problems and cannot meet requirements of engineering constraint parameter optimization. High adaptability, positive feedback and robustness are exhibited if a conventional bee colony algorithm is utilized for engineering parameter optimization, however, a limit of local optimal solution also exists. In terms of the chaotic bee colony algorithm, problems that the bee colony algorithm is liable to converge too early, is prone to local optimization and is inaccurate in edge positioning are overcome through full permutation and also through the characteristics of ergodicity, randomness and regularity of chaotic variables. The chaotic bee colony algorithm is employed for engineering constraint parameter optimization. The method is quick, clear, accurate, and highly effective.

Description

technical field [0001] The invention belongs to the technical field of intelligent algorithm application, in particular to an engineering constraint parameter optimization method based on an improved bee colony algorithm. Background technique [0002] Engineering parameter optimization problems widely exist in daily production and life. Traditional engineering constraint parameter optimization methods have many unsatisfactory problems, and it is difficult to meet the needs of engineering constraint parameter optimization. In general, engineering parameter optimization problems are under the premise of many linear or nonlinear constraints. However, due to the lack of deep understanding of the solution methods for parameter optimization problems with engineering constraints, if the search space is not differentiable or the parameters are nonlinear, the global optimal solution is often not obtained, that is, it falls into local optimization. Therefore, the balance mechanism of...

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Problems solved by technology

[0004] The purpose of the present invention is to provide a method that can make up for the shortcomings of the traditional bee colony algorithm, such as complex structure, difficult to determine, local optimization, and low search efficiency, and propose a fast, clear, and accurate algorithm to solve general engineering constraint parameters.

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