Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The UMDA algorithm is a type of Estimation of Distribution Algorithms. This algorithm has better performance compared to others such as genetic algorithm in terms of speed, memory consumption and accuracy of solutions. It can explore unknown parts of search space ll. It uses a probability vector and individuals of the population are created through the sampling. Furthermore, EO algorithm is suitable for local search of near global best solution in search space, and it dose not stuck in local optimum. Hence, combining these two algorithms is able to create interaction beten two fundamental concepts in evolutionary algorithms, exploration and exploitation, and achieve better results of this paper represent the performance of the proposed algorithm on two NP-hard problems, multi processor scheduling problem and graph bi-partitioning problem.
['Mitra Hashemi', 'Mohammad Reza Meybodi']
I am writing a research paper on a idea Univariate marginal distribution algorithm in combination with extremal optimization (EO, GEO)
[{"from": "human", "value": "I am writing a research paper on a idea Univariate marginal distribution algorithm in combination with extremal optimization (EO, GEO)"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The UMDA algorithm is a type of Estimation of Distribution Algorithms. This algorithm has better performance compared to others such as genetic algorithm in terms of speed, memory consumption and accuracy of solutions. It can explore unknown parts of search space ll. It uses a probability vector and individuals of the population are created through the sampling. Furthermore, EO algorithm is suitable for local search of near global best solution in search space, and it dose not stuck in local optimum. Hence, combining these two algorithms is able to create interaction beten two fundamental concepts in evolutionary algorithms, exploration and exploitation, and achieve better results of this paper represent the performance of the proposed algorithm on two NP-hard problems, multi processor scheduling problem and graph bi-partitioning problem."}]