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Improved Genetic Algorithm and Its Application in Solving MVCP

Zhou Ben-da

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Abstract

To improve the effect of traditional Genetic Algorithm(GA) in solving Minimum Vertices Covering Problem(MVCP),based on the mechanism of ideal density model and characteristic of MVCP,the crossover operation in GA is redesigned by using the principle of Uniform Design Sampling(UDS) and combining the locale search strategy.This paper proposes a Genetic Algorithm Based on Uniform Design Sampling(UGA) and applies it to solve MVCP.Compared with Simple GA(SGA) and Good Point-set GA(GGA),the simulation results show that UGA has superiority in speed,accuracy and overcoming premature.

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What this paper is about

To improve the effect of traditional Genetic Algorithm(GA) in solving Minimum Vertices Covering Problem(MVCP),based on the mechanism of ideal density model and characteristic of MVCP,the crossover operation in GA is redesigned by using the principle of Uniform Design Sampling(UDS) and combining the locale search strategy.This paper proposes a Genetic Algorithm Based on Uniform Design Sampling(UGA) and applies it to solve MVCP.Compared with Simple GA(SGA) and Good Point-set GA(GGA),the simulation results show that UGA has superiority in speed,accuracy and overcoming premature.

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Available abstract

To improve the effect of traditional Genetic Algorithm(GA) in solving Minimum Vertices Covering Problem(MVCP),based on the mechanism of ideal density model and characteristic of MVCP,the crossover operation in GA is redesigned by using the principle of Uniform Design Sampling(UDS) and combining the locale search strategy.This paper proposes a Genetic Algorithm Based on Uniform Design Sampling(UGA) and applies it to solve MVCP.Compared with Simple GA(SGA) and Good Point-set GA(GGA),the simulation results show that UGA has superiority in speed,accuracy and overcoming premature.

Key concepts: Crossover, Computer science, Genetic algorithm, Algorithm, Ideal (ethics), Sampling (signal processing), Set (abstract data type), Simple (philosophy)

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