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Solving integer multi-objective optimization problems using TOPSIS, Differential Evolution and Tabu Search

This paper presents a method to solve non-linear integer multiobjective optimization problems. First the problem is formulated using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Next, the Differential Evolution (DE) algorithm in its three versions (standard DE, DE best and DEGL) are used as optimizer. Since the solutions found by the DE algorithms are continuous, the Tabu Search (TS) algorithm is employed to find integer solutions during the optimization process. Experimental results show the effectiveness of the proposed method.

preprint2022arXivOpen access
Renato A. KrohlingErick R. F. A. Schneider
Neural and Evolutionary Computing
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Open access2 authors1 topic
Imported metadata coverageMissing code, dataset, citation and institution fields are tracked without dominating the paper.Details
Citations: 0Reviews: 0Saves: 0Code: not linkedDataset: not linkedInstitutions: 0

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Renato A. KrohlingErick R. F. A. Schneider

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