Improvement And Application Of Coral Reefs Algorithm

With the development of the times and the advancement of science,intelligent optimization algorithms have played an increasingly important role in our lives.A large number of new algorithms are constantly emerging,and the coral reef optimization algorithm is a new type of intelligent optimization algorithm,which based on the propagation of coral polyps and the formation of coral reefs.It has received extensive attention.In this thesis,the standard coral reef optimization algorithm is improved,and the test function is used to prove the effectiveness of the improvement.The improved coral reef algorithms for solving traveling salesman problem,fuzzy soft set parameter approximate reduction problem,reliability analysis problem and complex network cascading failure problem are proposed respectively.The effectiveness of the improved coral reef algorithm is verified by experimental simulation and comparison with other intelligent optimization algorithms.The main work is:(1)Combining simulated annealing algorithm,gaussian mutation and improved particle swarm optimization algorithm,an improved coral reef algorithm for solving function optimization problems is proposed.It was simulated in 15 test functions,and compared with the original coral reef optimization algorithm,gaussian variability coral reef algorithm,cauchy varietal coral reef algorithm,gaussian variation coral reef algorithm,particle swarm optimization algorithm,improved weight particle swarm optimization algorithm,improved particle swarm optimization algorithm,moth-flame optimization algorithm,multi-verse optimization algorithm and sine cosine optimization algorithm.Experiments show that the improved coral reef algorithm has better optimization performance in solving the function optimization problem.(2)Solving two types of combinatorial optimization problems.The first one is to propose an improved coral reef algorithm for solving path optimization problems.Firstly,the research significance and research status of path optimization problem are introduced.Then the problem is described,and the specific improvement,coding method and solution steps of the improved coral reef optimization algorithm for solving the problem are introduced.Finally,a real case simulation is carried out,and the results are compared with genetic algorithm,simulated annealing algorithm,tabu search algorithm and ant colony algorithm.The experimental results show that the improved coral reef optimization algorithm based on path optimization problem has better optimization effect in solving such problems.The second one is to propose an improved coral reef algorithm for solving the approximate reduction problem of fuzzy soft set parameters.Firstly,the research significance and research status of fuzzy soft set parameter approximate reduction are introduced.A reduction formula of fuzzy soft set approximate reduction and its relative fuzzy soft set approximation parameter reduction model are introduced.Then an improved coral reef algorithm for approximate reduction of fuzzy soft set parameters is proposed for the model.The specific improvement,coding method and solution steps of the coral reef algorithm for solving this problem are described.Finally,a real case simulation is performed and compared with the harmony search algorithm.The experimental results show that the improved coral reef algorithm based on fuzzy soft set parameter approximate reduction problem has good feasibility on this problem.(3)An improved coral reef algorithm for solving reliability analysis problems is proposed.Firstly,the significance and research status of reliability analysis are introduced.Then the specific improvement,coding method and solution steps of the improved coral reef algorithm for solving this problem are described.Finally,four reliability analysis models of complex system,series system,series-parallel system and over-speed system are simulated,and compared with the original coral reef algorithm,gaussian variability coral reef algorithm,cauchy variegated coral reef algorithm and gaussian coral reef algorithm.In addition,the results are compared with the results in the previous literature.The experimental results show that the improved coral reef algorithm based on reliability analysis has a better optimization effect on solving this problem.(4)An improved coral reef algorithm for solving complex network cascading failure problems is proposed.Firstly,the research significance and research status of complex network cascading failure problems and the specific model of cascading failure problems are introduced.Then to improve the form of understanding the problem,the creation of the dominant gene pool and the introduction of simulated annealing algorithms.Finally,the complex network cascading failure model is simulated and compared with the non-neighbor immune algorithm.The experimental results show that the improved coral reef algorithm based on the complex network cascading failure problem has a good optimization effect on this problem.