Robust multi-objective optimization for solving the RFID network planning problem

Simple item page
dc.citation.epage626
dc.citation.issue4
dc.citation.spage616
dc.contributor.affiliationУніверситет Мохаммеда V в Рабаті
dc.contributor.affiliationMohammed V University in Rabat
dc.contributor.authorС. Аіт Лгадж Ламін
dc.contributor.authorРагіб, А.
dc.contributor.authorБ. Абоу Ель Маджд
dc.contributor.authorS. Ait Lhadj Lamin
dc.contributor.authorRaghib, A.
dc.contributor.authorB. Abou El Majd
dc.coverage.placenameЛьвів
dc.coverage.placenameLviv
dc.date.accessioned2023-11-01T07:49:44Z
dc.date.available2023-11-01T07:49:44Z
dc.date.created2021-03-01
dc.date.issued2021-03-01
dc.description.abstractРадіочастотна ідентифікація (РЧІ) — це нова технологія, що використовується для ідентифікації та в дстеження об’єктів або людей за допомогою радіочастотних хвиль з метою полегшення автоматизованого відстеження та збору даних. Система РЧІ складається з електронної бирки, прикріпленої до об’єкта, зчитувачів та програмного забезпечення. У найновіших реальних додатках, заснованих на технології РЧІ, розташування зчитувачів стало центральним питанням планування мережі РЧІ за рахунок оптимізації кількох цілей, таких як охоплення бирок, кількість зчитувачів та завад читачів/тегів. На практиці на систему впливають невизначеність та неконтрольовані параметри навколишнього середовища. Тому оптимальне розв’язування задачі планування мережі РЧІ можна значно звузити за рахунок неконтрольованих змін деяких параметрах, таких як передавана потужність зчитувача. У цій роботі пропонується надійний підхід багатоцільової оптимізації для вирішення задачі розміщення зчитувачів РЧІ. Таким чином, досягнено надійних оптимальних рішень, нечутливих до невизначеностей параметрів оптимізації.
dc.description.abstractRadio-frequency identification (RFID) is a new technology used for identifying and tracking objects or people by radio-frequency waves to facilitate automated traceability and data collection. The RFID system consists of an electronic tag attached to an object, readers, and a middleware. In the latest real applications based on the RFID technology, the deployment of readers has become a central issue for RFID network planning by means of optimizing several objectives such as the coverage of tags, the number of readers, and the readers/tags interferences. In practice, the system is affected by uncertainty and uncontrollable environmental parameters. Therefore, the optimal solutions to the RFID network planning problem can be significantly reduced with uncontrollable variations in some parameters, such as the reader’s transmitted power. In this work, we propose a robust multi-objective optimization approach to solve the deployment of RFID readers. In this way, we achieve robust optimal solutions that are insensitive to uncertainties in the optimization parameters.
dc.format.extent616-626
dc.format.pages11
dc.identifier.citationS. Ait Lhadj Lamin Robust multi-objective optimization for solving the RFID network planning problem / S. Ait Lhadj Lamin, A. Raghib, B. Abou El Majd // Mathematical Modeling and Computing. — Lviv : Lviv Politechnic Publishing House, 2021. — Vol 8. — No 4. — P. 616–626.
dc.identifier.citationenS. Ait Lhadj Lamin Robust multi-objective optimization for solving the RFID network planning problem / S. Ait Lhadj Lamin, A. Raghib, B. Abou El Majd // Mathematical Modeling and Computing. — Lviv : Lviv Politechnic Publishing House, 2021. — Vol 8. — No 4. — P. 616–626.
dc.identifier.doi10.23939/mmc2021.04.616
dc.identifier.urihttps://ena.lpnu.ua/handle/ntb/60451
dc.language.isoen
dc.publisherВидавництво Львівської політехніки
dc.publisherLviv Politechnic Publishing House
dc.relation.ispartofMathematical Modeling and Computing, 4 (8), 2021
dc.relation.references[1] Raghib A., Abou El Majd B. Hierarchical multiobjective approach for optimising RFID reader deployment. International Journal of Mathematical Modelling and Numerical Optimisation. 9 (1), 70–88 (2019).
dc.relation.references[2] Guan Q., Liu Y., Yang Y. P., Yu W. S. Genetic Approach for Network Planning in the RFID Systems. Sixth International Conference on Intelligent Systems Design and Applications. 2, 567–572 (2006).
dc.relation.references[3] Chen H. N., Zhu Y. L. RFID Networks Planning Using Evolutionary Algorithms and Swarm Intelligence. 2008 4th International Conference on Wireless Communications, Networking and Mobile Computing. 1–4 (2008).
dc.relation.references[4] Chen H., Zhu Y., Hu K. Multi-colony bacteria foraging optimization with cell-to-cell communication for RFID network planning. Applied Soft Computing. 10 (2), 539–547 (2010).
dc.relation.references[5] Chen H., Zhu Y., Hu K. RFID networks planning using a multi-swarm optimizer. 2009 Chinese Control and Decision Conference. 3548–3552 (2009).
dc.relation.references[6] Chen H., Zhu Y., Hu K., Ku T. Dynamic RFID Network Optimization Using a Self-adaptive Bacterial Foraging Algorithm. International Journal of Artificial Intelligence. 7 (11), 219–231 (2011).
dc.relation.references[7] Chen H., Zhu Y., Ma L., Niu B. Multiobjective RFID Network Optimization Using Multiobjective Evolutionary and Swarm Intelligence Approaches. Mathematical Problems in Engineering. 2014, Article ID: 961412 (2014).
dc.relation.references[8] Ma L., Chen H., Hu K., Zhu Y. Hierarchical Artificial Bee Colony Algorithm for RFID Network Planning Optimization. The Scientific World Journal. 2014, Article ID: 941532 (2014).
dc.relation.references[9] Oscar B., Chaouch H. RFID network topology design based on Genetic Algorithms. 2011 IEEE International Conference on RFID-Technologies and Applications. 300–305 (2011).
dc.relation.references[10] Gong Y.-J., Shen M., Zhang J., Kaynak O., Chen W.-N., Zhan Z.-H. Optimizing RFID Network Planning by Using a Particle Swarm Optimization Algorithm With Redundant Reader Elimination. IEEE Transactions on Industrial Informatics. 8 (4), 900–912 (2012).
dc.relation.references[11] Tuba M., Bacanin N., Alihodzic A. Firefly algorithm for multi-objective RFID network planning problem. 2014 22nd Telecommunications Forum Telfor (TELFOR). 95–98 (2014).
dc.relation.references[12] Bacanin N., Tuba M., Jovanovic R. Hierarchical Multiobjective RFID Network Planning Using Firefly Algorithm. 2015 International Conference on Information and Communication Technology Research (ICTRC). 282–285 (2015).
dc.relation.references[13] Tuba M., Bacanin N., Beko M. Fireworks algorithm for RFID network planning problem. 2015 25th International Conference Radioelektronika (RADIOELEKTRONIKA). 440–444 (2015).
dc.relation.references[14] Tuba M., Bacanin N., Beko M. Multiobjective RFID Network Planning by Artificial Bee Colony Algorithm with Genetic Operators. International Conference in Swarm Intelligence. 247–254 (2015).
dc.relation.references[15] Raghib A., El Majd B. A., Ouchetto O., Aghezzaf B. Robustness optimization for solving the deployment of RFID readers problem. 2016 5th International Conference on Multimedia Computing and Systems (ICMCS). 509–513 (2016).
dc.relation.references[16] Zhao C., Wu C., Chai J., Wang X., Yang X., Lee J. M., Kim M. Decomposition-based multi-objective firefly algorithm for RFID network planning with uncertainty. Applied Soft Computing. 55, 549–564 (2017).
dc.relation.references[17] Vector T., Alihodzic A., Tuba M. Multi-objective RFID network planning with probabilistic coverage model by guided fireworks algorithm. 2017 10th International Symposium on Advanced Topics in Electrical Engineering (ATEE). 882–887 (2017).
dc.relation.references[18] Bouhouche T., Raghib A., El Majd B. A., Bouya M., Boulmalf M. A middleware architecture for rfidenabled traceability of air baggage. MATEC Web of Conferences. 105, Article Number: 00008 (2017).
dc.relation.references[19] Kalyanmoy D. Multi-Objective Optimization Using Evolutionary Algorithms. New York, John Wiley & Sons (2001).
dc.relation.references[20] Beyer H. G., Sendhoff B. Robust optimization-A comprehensive survey. Computer Methods in Applied Mechanics and Engineering. 196 (33–34), 3190–3218 (2007).
dc.relation.references[21] Taguchi G. Introduction to quality engineering: designing quality into products and processes. The Organization Tokyo (1986).
dc.relation.references[22] Gunawan S., Azarm S. Multi-objective robust optimization using a sensitivity region concept. Structural and Multidisciplinary Optimization. 29 (1), 50–60 (2014).
dc.relation.references[23] Kuroiwa D., Lee G. M. On robust multiobjective optimization. Vietnam Journal of Mathematics. 40 (2&3), 305–317 (2012).
dc.relation.references[24] Ehrgott M., Ide J., Sch¨obel A. Minmax robustness for multi-objective optimization problems. European Journal of Operational Research. 239 (1), 17–31 (2014).
dc.relation.references[25] Yu H., Liu H. Robust multiple objective game theory. Journal of Optimization Theory and Applications. 159 (1), 272–280 (2013).
dc.relation.references[26] Deb K., Pratap A., Agarwal S., Meyarivan T. A fast and elitist multi-objective genetic algorithm: NSGAII. IEEE Transactions on Evolutionary Computation. 6 (2), 182–197 (2002).
dc.relation.referencesen[1] Raghib A., Abou El Majd B. Hierarchical multiobjective approach for optimising RFID reader deployment. International Journal of Mathematical Modelling and Numerical Optimisation. 9 (1), 70–88 (2019).
dc.relation.referencesen[2] Guan Q., Liu Y., Yang Y. P., Yu W. S. Genetic Approach for Network Planning in the RFID Systems. Sixth International Conference on Intelligent Systems Design and Applications. 2, 567–572 (2006).
dc.relation.referencesen[3] Chen H. N., Zhu Y. L. RFID Networks Planning Using Evolutionary Algorithms and Swarm Intelligence. 2008 4th International Conference on Wireless Communications, Networking and Mobile Computing. 1–4 (2008).
dc.relation.referencesen[4] Chen H., Zhu Y., Hu K. Multi-colony bacteria foraging optimization with cell-to-cell communication for RFID network planning. Applied Soft Computing. 10 (2), 539–547 (2010).
dc.relation.referencesen[5] Chen H., Zhu Y., Hu K. RFID networks planning using a multi-swarm optimizer. 2009 Chinese Control and Decision Conference. 3548–3552 (2009).
dc.relation.referencesen[6] Chen H., Zhu Y., Hu K., Ku T. Dynamic RFID Network Optimization Using a Self-adaptive Bacterial Foraging Algorithm. International Journal of Artificial Intelligence. 7 (11), 219–231 (2011).
dc.relation.referencesen[7] Chen H., Zhu Y., Ma L., Niu B. Multiobjective RFID Network Optimization Using Multiobjective Evolutionary and Swarm Intelligence Approaches. Mathematical Problems in Engineering. 2014, Article ID: 961412 (2014).
dc.relation.referencesen[8] Ma L., Chen H., Hu K., Zhu Y. Hierarchical Artificial Bee Colony Algorithm for RFID Network Planning Optimization. The Scientific World Journal. 2014, Article ID: 941532 (2014).
dc.relation.referencesen[9] Oscar B., Chaouch H. RFID network topology design based on Genetic Algorithms. 2011 IEEE International Conference on RFID-Technologies and Applications. 300–305 (2011).
dc.relation.referencesen[10] Gong Y.-J., Shen M., Zhang J., Kaynak O., Chen W.-N., Zhan Z.-H. Optimizing RFID Network Planning by Using a Particle Swarm Optimization Algorithm With Redundant Reader Elimination. IEEE Transactions on Industrial Informatics. 8 (4), 900–912 (2012).
dc.relation.referencesen[11] Tuba M., Bacanin N., Alihodzic A. Firefly algorithm for multi-objective RFID network planning problem. 2014 22nd Telecommunications Forum Telfor (TELFOR). 95–98 (2014).
dc.relation.referencesen[12] Bacanin N., Tuba M., Jovanovic R. Hierarchical Multiobjective RFID Network Planning Using Firefly Algorithm. 2015 International Conference on Information and Communication Technology Research (ICTRC). 282–285 (2015).
dc.relation.referencesen[13] Tuba M., Bacanin N., Beko M. Fireworks algorithm for RFID network planning problem. 2015 25th International Conference Radioelektronika (RADIOELEKTRONIKA). 440–444 (2015).
dc.relation.referencesen[14] Tuba M., Bacanin N., Beko M. Multiobjective RFID Network Planning by Artificial Bee Colony Algorithm with Genetic Operators. International Conference in Swarm Intelligence. 247–254 (2015).
dc.relation.referencesen[15] Raghib A., El Majd B. A., Ouchetto O., Aghezzaf B. Robustness optimization for solving the deployment of RFID readers problem. 2016 5th International Conference on Multimedia Computing and Systems (ICMCS). 509–513 (2016).
dc.relation.referencesen[16] Zhao C., Wu C., Chai J., Wang X., Yang X., Lee J. M., Kim M. Decomposition-based multi-objective firefly algorithm for RFID network planning with uncertainty. Applied Soft Computing. 55, 549–564 (2017).
dc.relation.referencesen[17] Vector T., Alihodzic A., Tuba M. Multi-objective RFID network planning with probabilistic coverage model by guided fireworks algorithm. 2017 10th International Symposium on Advanced Topics in Electrical Engineering (ATEE). 882–887 (2017).
dc.relation.referencesen[18] Bouhouche T., Raghib A., El Majd B. A., Bouya M., Boulmalf M. A middleware architecture for rfidenabled traceability of air baggage. MATEC Web of Conferences. 105, Article Number: 00008 (2017).
dc.relation.referencesen[19] Kalyanmoy D. Multi-Objective Optimization Using Evolutionary Algorithms. New York, John Wiley & Sons (2001).
dc.relation.referencesen[20] Beyer H. G., Sendhoff B. Robust optimization-A comprehensive survey. Computer Methods in Applied Mechanics and Engineering. 196 (33–34), 3190–3218 (2007).
dc.relation.referencesen[21] Taguchi G. Introduction to quality engineering: designing quality into products and processes. The Organization Tokyo (1986).
dc.relation.referencesen[22] Gunawan S., Azarm S. Multi-objective robust optimization using a sensitivity region concept. Structural and Multidisciplinary Optimization. 29 (1), 50–60 (2014).
dc.relation.referencesen[23] Kuroiwa D., Lee G. M. On robust multiobjective optimization. Vietnam Journal of Mathematics. 40 (2&3), 305–317 (2012).
dc.relation.referencesen[24] Ehrgott M., Ide J., Sch¨obel A. Minmax robustness for multi-objective optimization problems. European Journal of Operational Research. 239 (1), 17–31 (2014).
dc.relation.referencesen[25] Yu H., Liu H. Robust multiple objective game theory. Journal of Optimization Theory and Applications. 159 (1), 272–280 (2013).
dc.relation.referencesen[26] Deb K., Pratap A., Agarwal S., Meyarivan T. A fast and elitist multi-objective genetic algorithm: NSGAII. IEEE Transactions on Evolutionary Computation. 6 (2), 182–197 (2002).
dc.rights.holder© Національний університет “Львівська політехніка”, 2021
dc.subjectРЧІ
dc.subjectзадача планування радіомереж
dc.subjectнадійність
dc.subjectбагатоцільова оптимізація
dc.subjectневизначеність
dc.subjectRFID
dc.subjectRNP problem
dc.subjectrobustness
dc.subjectmulti-objective optimization
dc.subjectuncertainty
dc.titleRobust multi-objective optimization for solving the RFID network planning problem
dc.title.alternativeНадійна багатоцільова оптимізація для вирішення задачі планування мережі РЧІ
dc.typeArticle

Files

Original bundle

Now showing 1 - 2 of 2
Thumbnail Image
Name:
2021v8n4_S_Ait_Lhadj_Lamin-Robust_multi_objective_616-626.pdf
Size:
1.14 MB
Format:
Adobe Portable Document Format
Download
Thumbnail Image
Name:
2021v8n4_S_Ait_Lhadj_Lamin-Robust_multi_objective_616-626__COVER.png
Size:
469.19 KB
Format:
Portable Network Graphics
Download

License bundle

Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.85 KB
Format:
Plain Text
Description:
Download

Collections

Mathematical Modeling And Computing. – 2021. – Vol. 8, No. 4