Hopfield Neural Network in Solution of the Close Enough Orienteering Problem

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F20%3A00355324" target="_blank" >RIV/68407700:21230/20:00355324 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Hopfield Neural Network in Solution of the Close Enough Orienteering Problem

Popis výsledku v původním jazyce

In this paper, we report on the Hopfield Neural Network (HNN) for the Orienteering Problem (OP) that is generalized to solve instances of the Close Enough Orienteering Problem (CEOP). In the orienteering problems, we are searching for a limited budget tour to maximize collected rewards by visiting selected target locations. In the CEOP, it is allowed to collect the reward remotely within a non-zero communication range. Thus we can save travel costs by collecting rewards at suitable visiting locations of the disk-shaped neighborhoods of target locations. The proposed approach combines the HNN for the OP with the Second-Order Cone Programming (SOCP) that is employed to determine locally optimal locations of visits to the disk-shaped neighborhoods of the target locations. Regarding the reported evaluation results using standard benchmarks, the proposed SOCP-based approach provides solutions with the improved solution quality compared to the previous HNN-based method with discrete samples of the possible locations of visits.

Název v anglickém jazyce

Hopfield Neural Network in Solution of the Close Enough Orienteering Problem

Popis výsledku anglicky

In this paper, we report on the Hopfield Neural Network (HNN) for the Orienteering Problem (OP) that is generalized to solve instances of the Close Enough Orienteering Problem (CEOP). In the orienteering problems, we are searching for a limited budget tour to maximize collected rewards by visiting selected target locations. In the CEOP, it is allowed to collect the reward remotely within a non-zero communication range. Thus we can save travel costs by collecting rewards at suitable visiting locations of the disk-shaped neighborhoods of target locations. The proposed approach combines the HNN for the OP with the Second-Order Cone Programming (SOCP) that is employed to determine locally optimal locations of visits to the disk-shaped neighborhoods of the target locations. Regarding the reported evaluation results using standard benchmarks, the proposed SOCP-based approach provides solutions with the improved solution quality compared to the previous HNN-based method with discrete samples of the possible locations of visits.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/GA19-20238S" target="_blank" >GA19-20238S: Multi-robotické monitorování dynamických prostředí</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2020

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

CEUR Workshop Proceedings

ISBN

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ISSN

1613-0073

e-ISSN

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Počet stran výsledku

7

Strana od-do

169-175

Název nakladatele

CEUR-WS.org

Místo vydání

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Místo konání akce

Oravská Lesná

Datum konání akce

18. 9. 2021

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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