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Published in 2019 at "Journal of Intelligent Manufacturing"
DOI: 10.1007/s10845-017-1358-7
Abstract: In this paper we propose the evolutionary clustering search (ECS) algorithm combined with a variable neighbourhood search (VNS) for the m-machine blocking flow shop scheduling problem with total tardiness minimization. The proposed ECS uses NEH-based…
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Keywords:
flow shop;
search;
clustering search;
evolutionary clustering ... See more keywords
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Published in 2021 at "IEEE Access"
DOI: 10.1109/access.2021.3116092
Abstract: Clustering is an unsupervised learning technique used in data mining for finding groups with increased object similarity within but not between them. However, the absence of a-priori knowledge on the optimal clustering criterion, and the…
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Keywords:
enhanced evolutionary;
evolutionary clustering;
ecac enhanced;
clustering using ... See more keywords
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Published in 2022 at "Computational Intelligence and Neuroscience"
DOI: 10.1155/2022/8714870
Abstract: Nowadays, the recommendation is an important task in the decision-making process about the selection of items especially when item space is large, diverse, and constantly updating. As a challenge in the recent systems, the preference…
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Keywords:
evolutionary clustering;
time;
memetic evolutionary;
algorithm ... See more keywords
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Published in 2019 at "Energies"
DOI: 10.3390/en12142668
Abstract: Customers’ electricity consumption behavior can be studied from daily load data. Studying the daily load data for user behavior pattern analysis is an emerging research area in smart grid. Traditionally, the daily load data can…
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Keywords:
daily load;
evolutionary clustering;
consumption;
load ... See more keywords