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A Pareto-Based Symbiotic Relationships Model for Unconstrained Continuous Optimization

机译：基于帕累托的无约束连续优化共生关系模型

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Symbiotic relationships are one of several phenomena that can be observed in nature. These relationships consist of interactions between organisms and can lead to benefits or damages to those involved. In an optimization context, symbiotic relationships can be used to perform information exchange between populations of candidate solutions to a given problem. This paper presents an information exchange model inspired by symbiotic relationships and applies the model to unconstrained single-objective continuous optimization problems. The symbiotic relationships are modelled using the Pareto dominance criteria inside a computational ecosystem for optimization. The Artificial Bee Colony algorithm is used to compound the populations of the ecosystem. Four models of relationships are analyzed: slavery, competition, altruism and mutualism. Thirty unconstrained single-objective continuous benchmark functions with high number of dimensions (d = 200) are tested and obtained results compared. Results suggest that the proposed model for information exchange favors the balance between exploration and exploitation leading to better results.
机译：共生关系是自然界中可以观察到的几种现象之一。这些关系包括生物体之间的相互作用，并且可能导致所涉人员受益或遭受损害。在优化上下文中，共生关系可用于在给定问题的候选解决方案群体之间执行信息交换。本文提出了一种受共生关系启发的信息交换模型，并将该模型应用于无约束的单目标连续优化问题。使用计算生态系统内的帕累托优势标准对共生关系进行建模以进行优化。人工蜂群算法用于复合生态系统的种群。分析了四种关系模型：奴隶制，竞争，利他主义和互惠主义。测试了三十个具有高维数（d = 200）的无约束单目标连续基准函数，并比较了获得的结果。结果表明，所提出的信息交换模型有利于勘探与开发之间的平衡，从而带来更好的结果。

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