尹洪超
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基于群体智能算法的换热网络同步最优综合
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Indexed by:期刊论文

Date of Publication:2022-06-29

Journal:化工学报

Issue:4

Page Number:1116-1123

ISSN No.:0438-1157

Abstract:Heat exchanger network is an important energy recovery system in chemical processes. Recently, simultaneous synthesis methods have been frequently applied to designing a cost-optimal heat exchanger network. Simultaneous synthesis problem is usually formulated as a mixed-integer non-linear programming model, which is non-convex, nonlinearity, non-continuous, and belongs to one of the toughest non-deterministic polynomial-time hard(NP-hard)problems. Medium or large -scale simultaneous synthesis problems in many cases cannot be solved in a reasonable time. A two-level approach was proposed for solving HENS problem. A hybrid methodology consisting of binary particle swarm optimization and genetic algorithm was utilized to generate the network structure in the upper level, while in the lower level, the heat load of exchangers and split-stream fractions were optimized by an improved particle swarm optimization. Two benchmark problems were solved to prove the efficiency of the proposed method. © All Rights Reserved.

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Supervisor of Master's Candidates

Gender:Male

Alma Mater:大连理工大学

Degree:Doctoral Degree

School/Department:能源与动力学院

Discipline:Thermal Engineering. Chemical Engineering. Operation Research and Control Theory

Business Address:大连理工大学能源与动力学院712室

Contact Information:电话:13940865971 邮箱:hcyin@dlut.edu.cn

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