Please use this identifier to cite or link to this item: http://hdl.handle.net/11328/3710
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dc.contributor.authorLotfi, Mohamed-
dc.contributor.authorOsório, Gerardo J.-
dc.contributor.authorJavadi, Mohammad-
dc.contributor.authorAshraf, Abdelrahman-
dc.contributor.authorZahran, Mustafa-
dc.contributor.authorSamih, Georges-
dc.contributor.authorCatalão, João P. S.-
dc.date.accessioned2021-10-15T13:21:29Z-
dc.date.available2021-10-15T13:21:29Z-
dc.date.issued2021-09-
dc.identifier.citationLotfi, M., Osório, G. J., Javadi, M, Ashraf, A., Zahran, M., Samih, G., & Catalão, J. P. S. (221). A Dijkstra-inspired graph algorithm for fully autonomous tasking in industrial applications. IEEE Transactions on Industry Applications, 57(5), 5448-5460. DOI: 10.1109/TIA.2021.3091418. Disponível no Repositório UPT, http://hdl.handle.net/11328/3710pt_PT
dc.identifier.issn1939-9367-
dc.identifier.urihttp://hdl.handle.net/11328/3710-
dc.description.abstractAn original graph-based model and algorithm for optimal industrial task scheduling are proposed in this article. The innovative algorithm designed, dubbed “Dijkstra optimal tasking” (DOT), is suitable for fully distributed task scheduling of autonomous industrial agents for optimal resource allocation, including energy use. The algorithm was designed starting from graph theory fundamentals, from the ground up, to guarantee a generic nature, making it applicable on a plethora of tasking problems and not case-specific. For any industrial setting in which mobile agents are responsible for accomplishing tasks across a site, the objective is to determine the optimal task schedule for each agent, which maximizes the speed of task achievement while minimizing the movement, thereby minimizing energy consumption cost. The DOT algorithm is presented in detail in this manuscript, starting from the conceptualization to the mathematical formulation based on graph theory, having a thorough computational implementation and a detailed algorithm benchmarking analysis. The choice of Dijkstra, as opposed to other shortest path methods (namely, A * Search and Bellman-Ford) in the proposed graph-based model and algorithm, was investigated and justified. An example of a real-world application based on a refinery site is modeled and simulated and the proposed algorithm's effectiveness and computational efficiency are duly evaluated. A dynamic obstacle course was incorporated to effectively demonstrate the proposed algorithm's applicability to real-world applications.pt_PT
dc.language.isoengpt_PT
dc.publisherInstituto de Engenheiros Elétricos e Eletrônicospt_PT
dc.rightsopenAccesspt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectGraph theorypt_PT
dc.subjectAlgorithmspt_PT
dc.subjectTask schedulingpt_PT
dc.subjectEnergy managementpt_PT
dc.subjectDijkstrapt_PT
dc.subjectIndustrial applicationspt_PT
dc.titleA Dijkstra-inspired graph algorithm for fully autonomous tasking in industrial applicationspt_PT
dc.typearticlept_PT
dc.relation.publisherversionhttps://ieeexplore.ieee.org/document/9462369pt_PT
dc.peerreviewedyespt_PT
degois.publication.firstPage5448pt_PT
degois.publication.lastPage5460pt_PT
degois.publication.volume57pt_PT
degois.publication.issue5pt_PT
degois.publication.titleIEEE Transactions on Industry Applicationspt_PT
dc.identifier.doi10.1109/TIA.2021.3091418pt_PT
Appears in Collections:REMIT – Artigos em Revistas Internacionais / Papers in International Journals

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