一种热集成系统的动态多智能体微分进化算法

计算物理 ›› 2016, Vol. 33 ›› Issue (3): 349-357.

一种热集成系统的动态多智能体微分进化算法

陈上, 崔国民, 张春伟, 段欢欢

上海理工大学能源与动力工程学院, 上海 200093

收稿日期:2015-05-26 修回日期:2015-09-10 出版日期:2016-05-25 发布日期:2016-05-25
作者简介:陈上(1991-),男,硕士研究生,研究方向为过程系统工程,E-mail:chenshang926@163.com
基金资助:
国家自然科学基金(51176125)和沪江基金研究基地专项(D14001)资助项目

Optimization of Heat Integration in Dynamic Multi-agent Differential Evolution Algorithm

CHEN Shang, CUI Guomin, ZHANG Chunwei, DUAN Huanhuan

School of Energy and Power Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China

Received:2015-05-26 Revised:2015-09-10 Online:2016-05-25 Published:2016-05-25

摘要/Abstract

摘要： 针对热集成系统换热网络存在的严重非凸非线性与多维多极值问题,提出动态多智能体微分进化算法.结合动态更新策略,并引入多智能体算法的环境感知能力,改进微分进化算法的种群生成方式与变异机制,并增强在大规模复杂非线性系统中的全局搜索能力.通过10SP2与9SP1换热网络经典算例优化,得到最佳年综合费用,体现出了改进算法更优的全局搜索能力.

关键词: 热集成系统, 动态更新, 多智能体微分进化, 全局最优化

Abstract: For optimization problem of heat integration system, serious nonlinear and non-convex heat exchanger network belonging to multi-extremum and multi-dimensional problems are considered. Dynamic multi-agent differential evolution algorithm is provided to solve the problem. It makes use of sensing capability of multi-agent with dynamic update strategy, which improves formation mechanism of population and mutation mechanism of differential evolution algorithm and globle searching ability in large scale nonlinear system. The algorithm was applied to 10SP2 and 9SP1 cases of heat exchanger network problems. Better total annual cost is obtained, which indicates better globle searching ability of the algorithm.

Key words: heat integration system, dynamic update, muti-agent dfferential evolution, globle optmization

中图分类号:

TK124

陈上, 崔国民, 张春伟, 段欢欢. 一种热集成系统的动态多智能体微分进化算法[J]. 计算物理, 2016, 33(3): 349-357.

CHEN Shang, CUI Guomin, ZHANG Chunwei, DUAN Huanhuan. Optimization of Heat Integration in Dynamic Multi-agent Differential Evolution Algorithm[J]. CHINESE JOURNAL OF COMPUTATIONAL PHYSICS, 2016, 33(3): 349-357.

参考文献

[1] YI D, HAN Z, WANG K, et al. Strategy for synthesis of flexible heat exchanger networks embedded with system reliability analysis[J]. Chinese Journal of Chemical Engineering (S1004-9541), 2013,21(7):742-753.
[2] LINNHOFF B, HINDMARSH E. The pinch design method for heat exchanger networks[J]. Chemical Engineering Science (S0009-2509), 1983,38(5):745-763.
[3] CERDA J, WESTERBERG A W. Minimum utility usage in heat exchanger network synthesis[J]. Chemical Engineering Science (S0009-2509), 1983,38(3):373-387.
[4] HUANG K F, AL-MUTAIRI E M, KARIMI I A. Heat exchanger network synthesis using a stagewise superstructure with non-isothermal mixing[J]. Chemical Engineering Science (S0009-2509), 2012,73:30-43.
[5] HUO Z, ZHAO L, YIN H, et al. A hybrid swarm intelligence algorithm for simultaneous synthesis of heat exchanger network[J]. CIESC Journal (S0438-1157), 2012,4:20.
[6] STORN R, PRICE K. Differential evolution-A simple and efficient heuristic for global optimization overcontinuous spaces[J]. Journal of Global Optimization (S1573-2916), 1997,11(4):341-359.
[7] WANG Y, LI H X, HUANG T, et al. Differential evolution based on covariance matrix learning and bimodal distribution parameter setting[J]. Applied Soft Computing (S1568-4946), 2014,18:232-247.
[8] BREST J, ZAMUDA A, FISTER I, et al. Large scale global optimization using self-adaptive differential evolution algorithm[C]//2010 IEEE Congress on Evolutionary Computation (CEC), Barcelona, 2010:1-8.
[9] YERRAMSETTY K M, MURTY C V S. Synthesis of cost-optimal heat exchanger networks using differential evolution[J]. Computers & Chemical Engineering (S0098-1354), 2008,32(8):1861-1876.
[10] COUELLAN N J, JORQUERA S, GEORGE T. Self-adaptive support vector machine:A multi-agent optimization perspective[J]. Expert Systems with Applications (S0957-4174), 2015,42(9):4284-4298.
[11] CHANG T H, WANG M Y. XF multi-agent distributed optimization via inexact consensus ADMM[J]. LEEE Transactions on Signal Processing (S1053-587X), 2015,63(2):482-497.
[12] 钟伟才,薛明志,刘静,等. 多智能体遗传算法用于超高维函数优化[J]. 自然科学进展, 2003,13(10):1078-1083.
[13] GROSSMANN I E, CABALLERO J A, YEOMANS H. Mathematical programming approachs to the synthesis of chemical process systems[J]. Korean Journal of Chemical Engineering (S0256-1115), 1999,16(4):407-426.
[14] RAVAGNANI M A S S, SILVA A P, ARROYO P A, et al. Heat exchanger network synthesis and optimisation using genetic algorithm[J]. Applied Thermal Engineering (S1359-4311), 2005,25(7):1003-1017.
[15] KHORASANY R F M. A novel approach for synthesis of cost-optimal heat exchanger networks[J]. Computers & Chemical Engineering (S0098-1354), 2008,33(8):1363-1370.
[16] ZHU X X, ONEILL B K, ROACH J R, et al. A method for automated heat exchanger network synthesis using block decomposition and non-linear optimization[J]. Chemical Engineering Research and Design, 1995,73(A8):919-930.
[17] HUO Zhaoyi, ZHAO Liang, YIN Hongchao, et al. Simultaneous synthesis of structural-constrained heat exchanger networks with and without stream splits[J]. The Canadian Journal of Chemical Engineering (S00084034), 2013,91(5):830-842.