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A methodology for the design of efficient resource conservation networks using adaptive swarm intelligence

机译:利用自适应群智能设计有效资源节约网络的方法

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The implementation of resource conservation schemes in industry can be enhanced through the application of systematic design methodologies. In particular, process integration methods allow resource consumption and waste generation in industrial plants to be reduced through the identification of efficient material reuse/recycle schemes. Various approaches, ranging from graphical pinch analysis to mathematical programming, have been developed by different researchers. Mathematical programming techniques provide considerable flexibility in the representation of network design problems, although in many cases, these approaches result in mixed integer non-linear programming (MINLP) models which are difficult to solve. This paper presents a simplified approach using a zero-one programming or "knapsack" formulation for the design of industrial material reuse/recycle networks. It is possible to solve the resulting model using an efficient heuristic algorithm based on adaptive particle swarm optimization. Two sample applications are provided to illustrate the methodology. The first case shows the application of the methodology to the implementation of industrial water conservation and the second case demonstrates its use in the design of a hydrogen gas reuse/recycle scheme in a refinery.
机译:可以通过应用系统设计方法来增强工业中资源节约计划的实施。尤其是,过程集成方法可通过识别有效的材料再利用/回收计划来减少工厂的资源消耗和废物产生。不同的研究人员已经开发出各种方法,从图形捏分析到数学编程。数学编程技术在表示网络设计问题方面提供了相当大的灵活性,尽管在许多情况下,这些方法导致混合整数非线性编程(MINLP)模型难以解决。本文提出了一种简化的方法,该方法使用零一编程或“背包”公式来设计工业材料的再利用/回收网络。可以使用基于自适应粒子群优化的高效启发式算法来求解结果模型。提供了两个示例应用程序来说明该方法。第一种情况说明了该方法在实施工业节水方面的应用,第二种情况说明了该方法在精炼厂氢气再利用/再循环方案设计中的使用。

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