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Ensemble of Strategies and Perturbation Parameter Based SOMA for Constrained Technological Design Optimization Problem

机译:基于策略和摄动参数的SOMA组合约束技术设计优化问题

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In this paper, we are introducing a novel ensemble based adaptive strategy for the Self Organizing Migrating Algorithm (SOMA), namely the "Ensemble of Strategies and Perturbation Parameter in SOMA" (ESP-SOMA). The proposed algorithm as well as several other state of the art selected metaheuristic algorithms are utilized in the task of optimization of waste processing batch reactor geometry and control. Since there is a growing demand for intelligent and fast problem solution or optimal utilization of resources in modern industrial field, especially in the Industry 4.0 era, this paper represents an insight into the applicability and effectivity of modern adaptive state of the art metaheuristic optimization algorithms in the task of highly constrained industrial design optimization problem. The simple statistical comparison of the results given by three different metaheuristic algorithms is also reported here.
机译:在本文中,我们为自组织迁移算法(SOMA)介绍了一种基于整体的自适应策略,即“ SOMA中的策略和扰动参数的集合”(ESP-SOMA)。所提出的算法以及其他几种最先进的选择元启发式算法被用于优化废物处理批处理反应器的几何形状和控制的任务中。由于在现代工业领域,尤其是在工业4.0时代,对智能,快速的问题解决方案或资源的最佳利用的需求不断增长,因此,本文对现代自适应最新元启发式优化算法的适用性和有效性进行了深入的了解。高度约束的工业设计优化问题的任务。此处还报告了由三种不同的元启发式算法给出的结果的简单统计比较。

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