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Please use this identifier to cite or link to this item: https://scholars.lib.ntu.edu.tw/handle/123456789/606194
Title: Metaheuristic Optimization on?Tensor-Type Solution via Swarm Intelligence and Its Application in the Profit Optimization in Designing Selling Scheme
Authors: Phoa F.K.H
Liu H.-P
Chen-Burger Y.-H.J
Lin S.-P.
SHAU-PING LIN 
Keywords: CPU parallelization;Selling scheme;Swarm intelligence;Tensor-type particle;Aerospace industry;Biomimetics;Profitability;Sales;Swarm intelligence;Tensors;Discrete domains;ITS applications;Meta-heuristic methods;Meta-heuristic optimizations;Profit optimization;Real applications;Scientific investigation;Statistical problems;Optimization
Issue Date: 2021
Journal Volume: 12689 LNCS
Start page/Pages: 72-82
Source: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Abstract: 
Nature-inspired metaheuristic optimization has been widely used in many problems in industry and scientific investigations, but their applications in designing selling scheme are rare because the solution space in this kind of problems is usually high-dimensional, and their constraints are sometimes cross-dimensional. Recently, the Swarm Intelligence Based (SIB) method is proposed for problems in discrete domains, and it is widely applied in many mathematical and statistical problems that common metaheuristic methods seldom approach. In this work, we introduce an extension of the SIB method that handles solutions with many dimensions, or tensor solution in mathematics. We further speed up our method by implementing our algorithm with the use of CPU parallelization. We then apply this extended framework to real applications in designing selling scheme, showing that our proposed method helps to increase the profit of a selling scheme compared to those suggested by traditional methods. ? 2021, Springer Nature Switzerland AG.
URI: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85112073718&doi=10.1007%2f978-3-030-78743-1_7&partnerID=40&md5=740b5eff1daa360186e949d0d35adbfa
https://scholars.lib.ntu.edu.tw/handle/123456789/606194
ISSN: 03029743
DOI: 10.1007/978-3-030-78743-1_7
Appears in Collections:生物科技研究所

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臺大位居世界頂尖大學之列,為永久珍藏及向國際展現本校豐碩的研究成果及學術能量,圖書館整合機構典藏(NTUR)與學術庫(AH)不同功能平台,成為臺大學術典藏NTU scholars。期能整合研究能量、促進交流合作、保存學術產出、推廣研究成果。

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