Random Matrix Generators for Optimizing a Fuzzy Biofuel Supply Chain System
Abstract
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.
Keywords
Full Text:
PDFTime cited: 0
DOI: http://dx.doi.org/10.25073/jaec.202041.268
Refbacks
- There are currently no refbacks.
Copyright (c) 2020 Journal of Advanced Engineering and Computation
This work is licensed under a Creative Commons Attribution 4.0 International License.