In order to solve the problem of complex function optimization, the ecological balance dynamics-based optimization (EBDO) algorithm is proposed based on the Lotka–Volterra ecological balance dynamics. The algorithm assumes that there are three populations of nurturers, consumers, and decomposers in an ecosystem. The self-plowing is mainly the plant; the consumer is mainly the animal who feeds on the nourish; the decomposer mainly breaks down the dead body of the consumer, and the nutrient is supplied to the self-raised person. According to the relationship among the populations in the above ecosystem, the consumer-autotrophic operator, the self-coter decomposer operator, the decomposer-consumer operator and the growth operator are constructed. The growth change of the population of the self-employed, the consumer and the decomposer is equivalent to the search space trying to move from one location to another. The algorithm has the characteristics of strong search ability and global convergence, it provides a solution for solving complex optimization problems.

中文翻译：

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一种生态平衡动力学优化方法

为解决复杂函数优化问题，在Lotka-Volterra生态平衡动力学的基础上，提出了基于生态平衡动力学的优化（EBDO）算法。该算法假设生态系统中有养育者、消费者和分解者三个群体。自耕主要是植物；消费者主要是以饲料为食的动物；分解器主要分解消费者的尸体，提供养分给自养人。根据上述生态系统中种群之间的关系，构造了消费-自养算子、自生分解算子、分解-消费算子和生长算子。个体户人口的增长变化，消费者和分解者相当于试图从一个位置移动到另一个位置的搜索空间。该算法具有搜索能力强和全局收敛的特点，为解决复杂的优化问题提供了解决方案。