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A hybrid algorithm based on genetic algorithm and plant growth simulation algorithm

Xu Liang, Tao Mu, Huang Ming

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Abstract

In order to solve the deceptive and pre-maturity problem of genetic algorithm, we combined plant growth simulation algorithm with genetic algorithm, so a new hybrid genetic algorithm occurred. Because of the searching way is better both in direction and randomness balance, which decided by plant hormone in plant growth simulation algorithm, so the deceptive problem of genetic algorithm is well settled and we got the globally optimal solution in a relatively efficient way. The simulation results show that very nice effects are obtained.

About this research paper

What this paper is about

In order to solve the deceptive and pre-maturity problem of genetic algorithm, we combined plant growth simulation algorithm with genetic algorithm, so a new hybrid genetic algorithm occurred. Because of the searching way is better both in direction and randomness balance, which decided by plant hormone in plant growth simulation algorithm, so the deceptive problem of genetic algorithm is well settled and we got the globally optimal solution in a relatively efficient way. The simulation results show that very nice effects are obtained.

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OpenAlex reports 4 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

In order to solve the deceptive and pre-maturity problem of genetic algorithm, we combined plant growth simulation algorithm with genetic algorithm, so a new hybrid genetic algorithm occurred. Because of the searching way is better both in direction and randomness balance, which decided by plant hormone in plant growth simulation algorithm, so the deceptive problem of genetic algorithm is well settled and we got the globally optimal solution in a relatively efficient way. The simulation results show that very nice effects are obtained.

Key concepts: Algorithm, Genetic algorithm, Population-based incremental learning, Randomness, Computer science, Cultural algorithm, Hybrid algorithm (constraint satisfaction), Algorithm design

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