Matches in SemOpenAlex for { <https://semopenalex.org/work/W4304542783> ?p ?o ?g. }
- W4304542783 abstract "Recently, the efficient deployment of wireless sensor networks (WSNs) has become a leading field of research in WSN design optimization. Practical scenarios related to WSN deployment are often considered as optimization models with multiple conflicting objectives that are simultaneously enhanced. In the related literature, it had been shown that moving from mono-objective to multi-objective resolution of WSN deployment is beneficial. However, since the deployment of real-world WSNs encompasses more than three objectives, a multi-objective optimization may harm other deployment criteria that are conflicting with the already considered ones. Thus, our aim is to go further, explore the modeling and the resolution of WSN deployment in a many-objective (i.e., optimization with more than three objectives) fashion and especially, exhibit its added value. In this context, we first propose a many-objective deployment model involving seven conflicting objectives, and then we solve it using an adaptation of the Decomposition-based Evolutionary Algorithm “ $$theta$$ -DEA”. The developed adaptation is named “WSN- $$theta$$ -DEA” and is validated through a detailed experimental study." @default.
- W4304542783 created "2022-10-12" @default.
- W4304542783 creator A5018448962 @default.
- W4304542783 creator A5027742590 @default.
- W4304542783 creator A5028612749 @default.
- W4304542783 creator A5080575230 @default.
- W4304542783 date "2022-10-29" @default.
- W4304542783 modified "2023-10-14" @default.
- W4304542783 title "Many-objective optimization of wireless sensor network deployment" @default.
- W4304542783 cites W1588375755 @default.
- W4304542783 cites W1804891470 @default.
- W4304542783 cites W1972805606 @default.
- W4304542783 cites W1982913063 @default.
- W4304542783 cites W1999988397 @default.
- W4304542783 cites W2000825106 @default.
- W4304542783 cites W2016918622 @default.
- W4304542783 cites W2022485595 @default.
- W4304542783 cites W2036612697 @default.
- W4304542783 cites W2040622444 @default.
- W4304542783 cites W2040754349 @default.
- W4304542783 cites W2047821354 @default.
- W4304542783 cites W2055179962 @default.
- W4304542783 cites W2065366002 @default.
- W4304542783 cites W2067544246 @default.
- W4304542783 cites W2100166495 @default.
- W4304542783 cites W2106034210 @default.
- W4304542783 cites W2106334424 @default.
- W4304542783 cites W2110828487 @default.
- W4304542783 cites W2142789827 @default.
- W4304542783 cites W2143381319 @default.
- W4304542783 cites W2169062068 @default.
- W4304542783 cites W2170176908 @default.
- W4304542783 cites W2170239483 @default.
- W4304542783 cites W2198098822 @default.
- W4304542783 cites W2282452766 @default.
- W4304542783 cites W2811266402 @default.
- W4304542783 cites W2904619258 @default.
- W4304542783 cites W2996227956 @default.
- W4304542783 cites W2997630374 @default.
- W4304542783 cites W3009895648 @default.
- W4304542783 cites W3033425110 @default.
- W4304542783 cites W3103693542 @default.
- W4304542783 cites W3116185997 @default.
- W4304542783 cites W3212797097 @default.
- W4304542783 cites W3214863135 @default.
- W4304542783 cites W3216127487 @default.
- W4304542783 cites W4206561957 @default.
- W4304542783 cites W4210401277 @default.
- W4304542783 cites W4210747461 @default.
- W4304542783 cites W4242952145 @default.
- W4304542783 cites W4253925510 @default.
- W4304542783 cites W4286225555 @default.
- W4304542783 doi "https://doi.org/10.1007/s12065-022-00784-1" @default.
- W4304542783 hasPublicationYear "2022" @default.
- W4304542783 type Work @default.
- W4304542783 citedByCount "0" @default.
- W4304542783 crossrefType "journal-article" @default.
- W4304542783 hasAuthorship W4304542783A5018448962 @default.
- W4304542783 hasAuthorship W4304542783A5027742590 @default.
- W4304542783 hasAuthorship W4304542783A5028612749 @default.
- W4304542783 hasAuthorship W4304542783A5080575230 @default.
- W4304542783 hasBestOaLocation W43045427832 @default.
- W4304542783 hasConcept C105339364 @default.
- W4304542783 hasConcept C111919701 @default.
- W4304542783 hasConcept C11413529 @default.
- W4304542783 hasConcept C120314980 @default.
- W4304542783 hasConcept C120665830 @default.
- W4304542783 hasConcept C121332964 @default.
- W4304542783 hasConcept C137836250 @default.
- W4304542783 hasConcept C139807058 @default.
- W4304542783 hasConcept C151730666 @default.
- W4304542783 hasConcept C24590314 @default.
- W4304542783 hasConcept C2779343474 @default.
- W4304542783 hasConcept C31258907 @default.
- W4304542783 hasConcept C41008148 @default.
- W4304542783 hasConcept C555944384 @default.
- W4304542783 hasConcept C76155785 @default.
- W4304542783 hasConcept C86803240 @default.
- W4304542783 hasConceptScore W4304542783C105339364 @default.
- W4304542783 hasConceptScore W4304542783C111919701 @default.
- W4304542783 hasConceptScore W4304542783C11413529 @default.
- W4304542783 hasConceptScore W4304542783C120314980 @default.
- W4304542783 hasConceptScore W4304542783C120665830 @default.
- W4304542783 hasConceptScore W4304542783C121332964 @default.
- W4304542783 hasConceptScore W4304542783C137836250 @default.
- W4304542783 hasConceptScore W4304542783C139807058 @default.
- W4304542783 hasConceptScore W4304542783C151730666 @default.
- W4304542783 hasConceptScore W4304542783C24590314 @default.
- W4304542783 hasConceptScore W4304542783C2779343474 @default.
- W4304542783 hasConceptScore W4304542783C31258907 @default.
- W4304542783 hasConceptScore W4304542783C41008148 @default.
- W4304542783 hasConceptScore W4304542783C555944384 @default.
- W4304542783 hasConceptScore W4304542783C76155785 @default.
- W4304542783 hasConceptScore W4304542783C86803240 @default.
- W4304542783 hasFunder F4320320883 @default.
- W4304542783 hasLocation W43045427831 @default.
- W4304542783 hasLocation W43045427832 @default.
- W4304542783 hasLocation W43045427833 @default.
- W4304542783 hasOpenAccess W4304542783 @default.
- W4304542783 hasPrimaryLocation W43045427831 @default.