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Multiobjective Biogeography-Based Optimization Based on Predator-Prey Approach

机译:基于捕食-被捕食方法的多目标生物地理优化

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Biogeography is the science that studies the geographical distribution and the migration of species in an ecosystem. Biogeography-based optimization (BBO) is a recently developed global optimization algorithm as a generalization of biogeography to evolutionary algorithm and has shown its ability to solve complex optimization problems. BBO employs a migration operator to share information between the problem solutions. The problem solutions are identified as habitat, and the sharing of features is called migration. In this paper, a multiobjective BBO, combined with a predator-prey (PPBBO) approach, is proposed and validated in the constrained design of a brushless dc wheel motor. The results demonstrated that the proposed PPBBO approach converged to promising solutions in terms of quality and dominance when compared with the classical BBO in a multiobjective version.
机译:生物地理学是研究生态系统中物种的地理分布和迁移的科学。基于生物地理的优化(BBO)是一种新近开发的全局优化算法,将生物地理学扩展为进化算法,并且已显示出解决复杂优化问题的能力。 BBO雇用迁移操作员在问题解决方案之间共享信息。问题解决方案被标识为栖息地,要素共享称为迁移。本文提出了一种结合捕食者-猎物(PPBBO)方法的多目标BBO,并在无刷直流轮式电动机的约束设计中对其进行了验证。结果表明,与多目标版本的经典BBO相比,拟议的PPBBO方法在质量和支配性方面已收敛到有希望的解决方案。

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