PEGA: A Privacy-Preserving Genetic Algorithm for Combinatorial Optimization

Evolutionary algorithms (EAs), such as the genetic algorithm (GA), offer an elegant way to handle combinatorial optimization problems (COPs). However, limited by expertise and resources, most users lack the capability to implement EAs for solving COPs. An intuitive and promising solution is to outso...

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Bibliographic Details
Published in:	IEEE transactions on cybernetics Vol. 54; no. 6; pp. 3638 - 3651
Main Authors:	Zhao, Bowen, Chen, Wei-Neng, Wei, Feng-Feng, Liu, Ximeng, Pei, Qingqi, Zhang, Jun
Format:	Journal Article
Language:	English
Published:	United States IEEE 01.06.2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Approximation Cloud computing Combinatorial analysis Combinatorial optimization Datasets Encryption Evolutionary algorithms Evolutionary computation evolutionary computation as a service (ECaaS) Genetic algorithms Knapsack problem Optimization Privacy privacy protection secure computing Servers Social factors Statistics Traveling salesman problem
ISSN:	2168-2267, 2168-2275, 2168-2275
Online Access:	Get full text
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