CIESC Journal ›› 2014, Vol. 65 ›› Issue (S1): 391-397.DOI: 10.3969/j.issn.0438-1157.2014.z1.063

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Particle swarm optimization with two new strategies for heat exchangers network synthesis

HE Qiaole, CUI Guomin, XU Haizhu   

  1. School of Energy and Power Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
  • Received:2014-02-10 Revised:2014-02-16 Online:2014-05-30 Published:2014-05-30
  • Supported by:

    supported by the National Natural Science Foundation of China (51176125).

基于新策略粒子群算法优化换热网络

何巧乐, 崔国民, 许海珠   

  1. 上海理工大学能源与动力工程学院, 上海 200093
  • 通讯作者: 崔国民
  • 基金资助:

    国家自然科学基金项目(51176125)。

Abstract: The optimization of heat exchanger networks synthesis (HENS) still remains an open problem because of the complexity nature of stream matches. The complexity of mixed integer nonlinear program (MINLP) keeps the opening for the heuristic algorithms including particle swarm optimization (PSO), and the HENS play an important role in the chemical process optimization. Two strategies that dedicated to improve the performance of PSO for optimal design of heat exchanger network are proposed. Although the standard PSO algorithm is capable of detecting the promising region, it exhibits the deficiency of that they cannot perform a refined local search to compute the optimum with high accuracy once there. The matter that the best position ever recorded is not the true minimum fitness will lead to the excessive roaming the search spaces and frequent updating. Local search technique to overcome above difficulties was proposed. In local search component, two local search strategies that perform more refined search around potential solutions of particle at hand were proposed. In cases take consideration of the fixed equipment cost, a formula alteration strategy was proposed to overcome the matter that, due to existence of the non-zero fixed equipment cost a, the evolution will likely to be trapped into a local optimum. Since the area cost is relatively small compared with the fixed equipment cost a in the initial iteration phase of evolution. The proposed strategies has been applied to several four streams cases taken from the literature and the results are very encouraging. The presented case studies revealed special search ability in local optimization incorporated with the proposed strategies.

Key words: particle swarm optimization, heuristic algorithm, heat exchangers network synthesis, local search strategies

摘要: 换热网络综合优化是过程系统中最广泛研究的方向。尽管如此,MINLP的复杂性给粒子群算法的应用提供了广泛的空间。首先,提出两种不同机理的局部搜索策略来完善粒子群算法作为启发式算法局部搜索能力不强和精度不高的问题,使算法能更有利地接近全局最优的局部极值。其次,对含固定投资费用的算例,采用费用计算替换公式的策略,来避免迭代计算初期面积较小时因为固定投资费用权重较大而使算法陷入局部最优问题。最后用4个四股流算例分别从不同侧面说明以上两种策略的有效性,并都得到了该算例目前为止最好的局部极值。

关键词: 粒子群算法, 启发式算法, 换热网络综合, 局部搜索策略

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