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演化算法求运算树表达的最大值，通过后序遍历求得适应度函数值，通过演化算法优化最优解-Evolutionary algorithms seek to express the maximum value of the tree operations, through the postorder fitness function values obtained by evolutionary algorithm to optimize the optimal solution
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量子进化算法和免疫算法都是解决优化问题的强有力算法。在分析了量子进化算法搜索的特点和免疫算法的机理基础上，对它们进行比较，阐明了二者的不同特点-Quantum-inspired evolutionary algorithms and immune algorithms are a powerful algorithm to solve optimization problems. After analyzing the characteristics of the quantum evoluti
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分析量子进化算法和免疫算子的特点,提出一种分级变异的量子进化算法,用于求解多目标优化问题-Analysis of quantum-inspired evolutionary algorithms and immune operator characteristics, presents a hierarchical variation of the quantum-inspired evolutionary algorithm for solving multi-objective optimi
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Flower pollination is an intriguing process in the natural world. Its evolutionary
characteristics can be used to design new optimization algorithms. In this paper, we
propose a new algorithm, namely, flower pollination algorithm, inspired by the
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Standard Genetic Algorithm in Python. With this code you are able to solve optimization problems by using evolutionary algorithms
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Simple Evolutionary Algorithms from a Chapter of book published by Springer
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multi-objective dynamic optimization using evolutionary algorithms
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In the field of artificial intelligence, a genetic algorithm (GA) is a search heuristic that mimics the process of natural selection. This heuristic (also sometimes called a metaheuristic) is routinely used to generate useful solutions to optimizatio
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jmetal优化算法工具包，整合了许多常见进化算法，用于数值优化-jmetal optimization toolkit which integrates multiple evolutionary algorithms for numerical optimization
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