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Industrial water management by multiobjective optimization: from individual to collective solution through eco-industrial parks

机译:多目标优化的工业用水管理:从个体解决方案到集体解决方案,再到生态工业园区

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摘要

Industrial water networks are designed in the first part by a multiobjective optimization strategy, where fresh water, regenerated water flow rates as well as the number of network connections (integer variables) are minimized. The problem is formulated as a Mixed-Integer Linear Programming problem (MILP) and solved by the ε-constraint method. The linearization of the problem is based on the necessary conditions of optimality defined by Savelski and Bagajewicz (2000). The approach is validated on a published example involving only one contaminant. In the second part the MILP strategy is implemented for designing an Eco-Industrial Park (EIP) involving three companies. Three scenarios are considered: EIP without regeneration unit, EIP where each company owns its regeneration unit and EIP where the three companies share regeneration unit(s). Three possible regeneration units can be chosen, and the MILP is solved under two kinds of conditions: limited or unlimited number of connections, same or different gains for each company. All these cases are compared according to the global equivalent cost expressed in fresh water and taking also into account the network complexity through the number of connections. The best EIP solution for the three companies can be determined.
机译:在第一部分中,工业水网络是通过多目标优化策略设计的,其中淡水,再生水流速以及网络连接数(整数变量)被最小化。该问题被公式化为混合整数线性规划问题(MILP),并通过ε约束方法解决。问题的线性化是基于Savelski和Bagajewicz(2000)定义的最优性的必要条件。该方法在仅涉及一种污染物的公开示例中得到了验证。在第二部分中,实施了MILP战略,以设计一个由三家公司组成的生态工业园区(EIP)。考虑了三种方案:不带再生单元的EIP,每个公司拥有其再生单元的EIP和三个公司共享再生单元的EIP。可以选择三个可能的再生单元,并且在两种情况下可以解决MILP:连接数量有限或无限,每个公司的收益相同或不同。所有这些情况都是根据淡水中表示的全球等效成本进行比较的,并考虑了通过连接数的网络复杂性。可以确定这三家公司的最佳EIP解决方案。

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