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|Title:||Self-adaptive Differential Evolution with Taboo List for Constrained Optimization Problems and Its Application to Pooling Problems||Authors:||Zhang, H.
|Issue Date:||2011||Citation:||Zhang, H., Rangaiah, G.P. (2011). Self-adaptive Differential Evolution with Taboo List for Constrained Optimization Problems and Its Application to Pooling Problems. Computer Aided Chemical Engineering 29 : 573-576. ScholarBank@NUS Repository. https://doi.org/10.1016/B978-0-444-53711-9.50115-2||Abstract:||Differential evolution (DE), a population-based global optimization algorithm, has been gaining popularity in the recent past due to its capability to handle non-convex and nondifferentiable functions. In this study, Self-adaptive Differential Evolution with Taboo List (SaDETL) with a novel constraint handling technique is proposed. It is tested for solving benchmark problems with equality and/or inequality constraints, and then applied to pooling problems, which are challenging with many constraints and important in process industries. In SaDETL, mutation strategy and parameter are selfadapted according to the learning experience from the previous generations, and taboo list is used to avoid revisiting the same area, to increase the population diversity and exploration of search space with fewer function evaluations, and to prevent premature convergence. An efficient constraint handling technique is incorporated with SaDETL; it is based on adaptive relaxation of constraints to improve the search and feasibility approach for selection. The results show that SaDETL with this technique is better than recent stochastic techniques for solving benchmark constrained problems, and is reliable and promising for solving pooling problems. © 2011 Elsevier B.V.||Source Title:||Computer Aided Chemical Engineering||URI:||http://scholarbank.nus.edu.sg/handle/10635/117414||ISSN:||15707946||DOI:||10.1016/B978-0-444-53711-9.50115-2|
|Appears in Collections:||Staff Publications|
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