Feasibility and cost minimisation for a lithium extraction problem
Author
dc.contributor.author
Bosch, P.
Author
dc.contributor.author
Contreras, J. P.
Author
dc.contributor.author
Munizaga Rosas, J.
Admission date
dc.date.accessioned
2020-04-07T17:12:58Z
Available date
dc.date.available
2020-04-07T17:12:58Z
Publication date
dc.date.issued
2020
Cita de ítem
dc.identifier.citation
Computers and Operations Research 115 (2020) 104724
es_ES
Identifier
dc.identifier.other
10.1016/j.cor.2019.05.029
Identifier
dc.identifier.uri
https://repositorio.uchile.cl/handle/2250/173831
Abstract
dc.description.abstract
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.