A Reliable Parallel Interval Global Optimization Algorithm Based on Mind Evolutionary Computation

Yong-mei Lei, Shao-jun Chen
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引用次数: 5

Abstract

In this paper, we investigate the parallel reliable computational model and propose a parallel interval evolutionary algorithm that integrates interval arithmetic and Mind Evolutionary Computation method. The major aim is to explorer the new parallel interval decomposition scheme can solve computation intensive problem and can determine the all optimal solution reliably. The proposed algorithm is experimentally testified on the ZiQiang 3000 cluster of Shanghai High Education Grid-e-Grid Computational Application Platform with a test suit containing 6 complex multi-modal function optimization benchmarks.
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基于思维进化计算的可靠并行区间全局优化算法
本文研究了并行可靠计算模型,提出了一种结合区间算法和思维进化计算方法的并行区间进化算法。主要目的是探索一种新的并行区间分解方案,该方案既能解决计算量大的问题,又能可靠地确定所有最优解。采用包含6个复杂多模态函数优化基准的测试服,在上海高等教育网格-e-网格计算应用平台自强3000集群上进行了实验验证。
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