Water Network Synthesis Using Mutation-Enhanced Particle Swarm Optimization
Water Network Synthesis Using Mutation-Enhanced Particle Swarm Optimization
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DOI：
10.1205/psep06065
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发表时间：
2007
影响因子：
7.8
通讯作者：
S. Hul;R. Tan;J. Auresenia;T. Fuchino;D. Foo
中科院分区：
文献类型：
--
作者：
S. Hul;R. Tan;J. Auresenia;T. Fuchino;D. Foo
摘要在最近的过程集成研究中，工业水回用/再循环网络的合成技术得到了发展。这些工具包括从图形夹点分析方法到数学规划模型。后者的优点是足够灵活，以纳入各种水网络的限制，但在许多情况下，这些往往是非线性的，从而使识别全局最优值困难。最近的工作已经证明了元启发式算法的有效性，如粒子群优化（PSO），找到好的解决方案，这些问题。这项工作描述了使用改进的粒子群算法求解混合整数非线性规划（MINLP）模型的水网络合成。通过将变异算子的二进制变量的模型中，该算法是能够逃脱次优的网络拓扑结构，并进行更好的解决方案比可以找到普通的PSO。使用两个涉及水回收/再利用的案例研究来演示新的设计方法。
Abstract Different techniques for the synthesis of industrial water reuse/recycle networks have been developed in recent process integration research. These tools range from graphical pinch analysis approaches to mathematical programming models. The latter have the advantage of being flexible enough to incorporate various water network constraints, but in many cases these are often non-linear, thus making the identification of global optima difficult. Recent work has demonstrated the effectiveness of metaheuristic algorithms such as particle swarm optimization (PSO), for finding good solutions these problems. This work describes the use of a modified PSO for solving mixed integer non-linear programming (MINLP) models for water network synthesis. By incorporating a mutation operator for the binary variables in the model, the algorithm is able to escape sub-optimal network topologies and proceed towards better solutions than can be found with ordinary PSO. Two case studies involving water recycle/reuse are used to demonstrate the new design methodology.