模糊生物燃料供应链系统优化的随机矩阵生成器

T. Ganesan, P. Vasant, Pratik Sanghvi, Joshua Thomas, I. Litvinchev
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引用次数: 20

摘要

复杂的工业系统往往包含各种不确定性。因此,复杂的模糊优化(元启发式)技术已经变得司空见惯;是目前此类系统有效设计、维护和运行所不可缺少的。不幸的是,这种最先进的技术在应用于大规模问题时存在一些缺陷。为了提高元启发式算法的性能,本文提出了模糊随机矩阵理论(RMT)作为布谷鸟搜索(CS)技术的补充来解决模糊大规模多目标(MO)优化问题;生物燃料供应链。模糊生物燃料供应链问题解释了生物燃料发电厂年发电量[千瓦时/年]波动所带来的不确定性。介绍和分析了这些调查的细节。这是一篇在知识共享署名许可(http://creativecommons.org/licenses/by/4.0/)条款下发布的开放获取文章,该许可允许在任何媒介上不受限制地使用、分发和复制,只要原始作品被适当引用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Random Matrix Generators for Optimizing a Fuzzy Biofuel Supply Chain System
Complex industrial systems often contain various uncertainties. Hence sophisticated fuzzy optimization (metaheuristics) techniques have become commonplace; and are currently indispensable for effective design, maintenance and operations of such systems. Unfortunately, such state-of-the-art techniques suffer several drawbacks when applied to largescale problems. In line of improving the performance of metaheuristics in those, this work proposes the fuzzy random matrix theory (RMT) as an add-on to the cuckoo search (CS) technique for solving the fuzzy large-scale multiobjective (MO) optimization problem; biofuel supply chain. The fuzzy biofuel supply chain problem accounts for uncertainties resulting from fluctuations in the annual electricity generation output of the biomass power plant [kWh/year]. The details of these investigations are presented and analyzed.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium provided the original work is properly cited.
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