Friday, August 12, 2016

Multi-objective operation optimization of ethylene cracking furnace based on AMOPSO algorithm



CATEGORY: ETHYLENE CRACKING
Multi-objective operation optimization
 of ethylene cracking furnace based on AMOPSO algorithm
Type
Journal Article
Author
Zhiqiang Geng
Author
Zun Wang
URL
Volume
153
Pages
21-33
Publication
Chemical Engineering Science
Date
October 22, 2016
Abstract
Describes design of a strategy to efficiently solve the multi-objective operation optimization problem of ethylene cracking furnace. Authors present an adaptive multi-objective particle swarm optimization (AMOPSO) algorithm based on dynamic analytic hierarchy process (AHP). The algorithm adopts fuzzy consistent matrix to select the global best solution, which ensures the correct direction of particle evolution.
They measure the evolution state to adjust the weight and learning coefficients adaptively. They apply the method to the operation optimization of ethylene cracking furnace. Two cases studies are offered, including the fixed cracking cycle with four objectives and the non-fixed cracking cycle with five objectives.

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