Biogeography-based multi-objective optimization algorithm with hybrid migration and applying in ethylene cracking process

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• 英文论文题名：Biogeography-based multi-objective optimization algorithm with hybrid migration and applying in ethylene cracking process
• 论文作者：Zheming Huang ; Rongbin Qi
• 英文论文作者：Zheming Huang ; Rongbin Qi ; East China University of Science and Technology ; Key Laboratory of Advanced Control and Optimization for Chemical Process ; Ministry of Education
• 年：2017
• 作者机构：East China University of Science and Technology,Key Laboratory of Advanced Control and Optimization for Chemical Process,Ministry of Education;
• 英文论文关键词：biogeography-based optimization ; multi-objective ; self-adaptive migration ; ethylene cracking optimization
• 会议召开时间：2017-07-26
• 会议录名称：第36届中国控制会议论文集（B）
• 英文会议录名称：Proceedings of the 36th Chinese Control Conference（B）
• 语种：英文
• 分类号：TQ221.211
• 学会代码：KZLL
• 会议名称：第36届中国控制会议
• 会议地点：中国辽宁大连
• 主办单位：中国自动化学会控制理论专业委员会
• 学会名称：中国自动化学会控制理论专业委员会
• 页数：6
• 文件大小：426k
• 原文格式：D
• 会议级别：全国

摘要

The Ethylene cracking is highly nonlinear, complex process with many constraints because of the complex running state of cracking furnace groups. For the solutions to multi-objective problems of yield, cost and benefits, this paper puts forward a biogeography-based multi-objective optimization algorithm with hybrid migration(BBMOHM). The hybrid migration strategy combines the self-adaptive migration with the simplex operator and the replication migration, which strengthens the convergence and the search ability, to avoid falling into local optimum. For the goal of utilizing the dominance information between individuals, this algorithm adopts the migration model of dominance degree to assist migration strategies improving the performance of the algorithm. Finally, experiments about the ZDT test function and the multi-objective optimization problem of the ethylene cracking process is verified the BBMOHM achieves good performance on convergence and distribution.
The Ethylene cracking is highly nonlinear, complex process with many constraints because of the complex running state of cracking furnace groups. For the solutions to multi-objective problems of yield, cost and benefits, this paper puts forward a biogeography-based multi-objective optimization algorithm with hybrid migration(BBMOHM). The hybrid migration strategy combines the self-adaptive migration with the simplex operator and the replication migration, which strengthens the convergence and the search ability, to avoid falling into local optimum. For the goal of utilizing the dominance information between individuals, this algorithm adopts the migration model of dominance degree to assist migration strategies improving the performance of the algorithm. Finally, experiments about the ZDT test function and the multi-objective optimization problem of the ethylene cracking process is verified the BBMOHM achieves good performance on convergence and distribution.

引文

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