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Feasibility and cost minimisation for a lithium extraction problem

机译:锂提取问题的可行性和成本最小化

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In this paper we address the problem of allocating extraction pumps to wells, when exploiting lithium rich brines, as part of the production of lithium salts. The problem of choosing the location of extraction wells is defined using a transportation network structure. Based on the transportation network, the lithium rich brines are pumped out from each well and then mixed into evaporation pools. The quality of the blend will be based on the chemical concentrations of the different brines, originating from different wells. The objective of the problem is then to determine a pumping plan such that the final products have predefined concentrations, and the process is operated in the cheapest possible way. The problem is modelled as a combinatorial optimisation problem and a potential solution to it is sought using a genetic algorithm. The evaluation function of the genetic algorithm needs a method to determine feasible minimum cost flows for the proposed pumping allocation, thus requiring the formulation of a blending model in a flow network for which a new iterative non-convex local optimisation algorithm is proposed. The model was implemented and tested to measure the algorithm's efficiency. (C) 2019 Elsevier Ltd. All rights reserved.
机译:在本文中,我们解决了在开采富含锂的盐水时,将抽水泵分配至井的问题,这是锂盐生产的一部分。使用运输网络结构定义了选择提取井位置的问题。根据运输网络,从每口井中抽出富含锂的盐水,然后将其混合到蒸发池中。混合物的质量将取决于来自不同井的不同盐水的化学浓度。问题的目的然后是确定泵送计划,以使最终产品具有预定的浓度,并且该过程以尽可能便宜的方式进行。将该问题建模为组合优化问题,并使用遗传算法寻求该问题的潜在解决方案。遗传算法的评估功能需要一种方法来确定拟议的抽水分配的可行最小成本流,因此需要在流网络中制定混合模型,为此提出了一种新的迭代非凸局部优化算法。该模型已实现并经过测试,以衡量算法的效率。 (C)2019 Elsevier Ltd.保留所有权利。

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