RFID network planning using a new hybrid ANNs-based approach. Issue 1 (31st December 2022)

• Record Type: Journal Article
• Authors: Maimouni, Mustapha; Abou El Majd, Badr; Bouya, Mohsine
• Is Part Of: Connection science. Volume 34:Issue 1(2022)
• Page Start: 2265
• Page End: 2290
• Publication Date: 2022-12-31
• Subjects: Meta-heuristics -- redundant antenna elimination -- optimisation -- artificial neural networks -- RFID network planning; Neural computers -- Periodicals; Artificial intelligence -- Periodicals; Cognitive science -- Periodicals; Connectionism -- Periodicals; 006.3
• DOI: 10.1080/09540091.2022.2115011
• Languages: English
• ISSNs: 0954-0091

Abstract

Abstract : Radio frequency identification (RFID) is a wireless technology that uses radio waves to automatically identify and track objects within a certain range. Due to the benefits of the technology, RFID technology has been adopted as a reliable and efficient solution and is an important technology used in various IoT applications. The deployment of the RFID system has caused an RFID network planning (RNP) problem. However, the RNP problem can be defined as an NP-hard combinatorial optimisation problem that requires the examination of a large number of combinations to obtain the best solution. The goal of this research is to introduce and describe a new hybrid approach to solve the problem of RNP optimisation that is based on artificial intelligence algorithms that require a minimum number of initial parameters. Based on widely used benchmarks, our approach is compared against a hybrid approach based on the genetic algorithm, and the results are efficient, cost-effective and assure a good deployment of the RFID system.