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Hybrid biological symbiosis search method for single target optimization

A biosymbiosis and single-objective technology, applied in the field of hybrid biosymbiosis search, can solve problems such as insufficient convergence accuracy and slow convergence speed, and achieve the effects of improving convergence speed and convergence accuracy, reducing time, and strong robustness

Inactive Publication Date: 2017-10-24
NORTHEAST DIANLI UNIVERSITY
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Problems solved by technology

[0008] In view of this, the present invention provides a hybrid symbiotic search method for single-objective optimization aiming at the problems of slow convergence speed, insufficient convergence precision and easy to fall into local optimum in the symbiotic search algorithm

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  • Hybrid biological symbiosis search method for single target optimization
  • Hybrid biological symbiosis search method for single target optimization
  • Hybrid biological symbiosis search method for single target optimization

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Embodiment Construction

[0042] The implementation of the present invention will be described in detail below with examples, so as to fully understand and implement the implementation process of how the present invention uses technical means to solve technical problems and achieve technical effects.

[0043] The present invention provides a kind of method for the hybrid biological symbiosis search of single-objective optimization, comprising the following steps:

[0044] Step 1. Determine the initial number of evolutionary individuals N, the dimension D of the population, the number of maximum fitness evaluations and other related parameters; use a random method to generate N individuals to form the initial population X; each individual in X The jth dimension component of randomly generated, In the formula, l j and u j are the lower bound and upper bound of the jth dimension of the decision variable of the problem to be solved, and rand represents a random number of (0, 1);

[0045] Step 2. Evalu...

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Abstract

The invention discloses a method for searching a mixed biological symbiosis for single-objective optimization, which comprises the following steps: initializing the number of individuals N, the dimension D of the population, the parameters related to the maximum number of function evaluation times, and randomly generating the initial population; For fitness evaluation, select the best individual among them; update the population by adopting the mutual-benefit symbiosis strategy; update the population by adopting the partial-benefit symbiosis strategy; update the population by adopting the parasitic-symbiosis strategy; judge whether the termination condition is met, and then output the optimal individual and fitness value , if not, continue to repeat the three symbiotic strategies to update the population. The method of the present invention can obtain the solution required by the problem in a small number of iterations in the actual problem solving, which reduces the time required for solving the problem to a certain extent.

Description

technical field [0001] The invention belongs to the field of artificial intelligence, and in particular relates to a method for single-objective optimized hybrid biological symbiosis search. Background technique [0002] The symbiotic search algorithm is a new swarm intelligence optimization algorithm that imitates the interaction of different organisms in nature, which has the advantages of fast search speed and few parameter settings. Compared with the current excellent differential evolution algorithm, particle swarm algorithm, spider algorithm, etc., it has better test results, but similar to other evolutionary algorithms, it still has problems such as slow convergence speed and easy to fall into local optimum. This is because the exploration ability and development ability of the algorithm are a pair of contradictory relationship. The exploration ability refers to the ability of the algorithm to find the global optimal solution by searching the search space globally. T...

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Application Information

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IPC IPC(8): G06N3/00
CPCG06N3/006
Inventor 王艳娇陶欢欢
Owner NORTHEAST DIANLI UNIVERSITY
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