Decomposition-based multi-objective firefly algorithm for RFID network planning with uncertainty |
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| Affiliation: | 1. School of Mathematics and Computer Sciences, Anhui Normal University, Wuhu 241000, China;2. Australasian Joint Research Centre for Building Information Modelling, School of Built Environment, Curtin University, Perth, WA 6845, Australia;3. Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks, Nanjing, Jiangsu 210003, China;4. Sino-Australia Collaborative Innovation Alliance for Megaproject Management in the Era of Internet+ and Big Data, Australia;5. School of Mathematics, Chongqing Normal University, Chongqing 400047, China;6. Department of Naval Architecture and Ocean Engineering, Pusan National University, Busan, South Korea;7. Department of Housing and Interior Design, Kyung Hee University, Seoul, South Korea;1. IME, Universidade Federal de Goiás, Goiânia, GO 74001-970, Brazil;2. DM, Universidade Federal do Piauí, Teresina, PI 64049-500, Brazil;3. COPPE/Sistemas, Universidade Federal do Rio de Janeiro, Rio de Janeiro, RJ 21945-970, Brazil;4. GREQAM-AMSE, Aix-Marseille University, France;1. Dept. of Electronics and Communication Engineering, RCC Institute of Information Technology, Kolkata 700015, India;2. Electronics and Communication Sciences Unit, Indian Statistical Institute, Kolkata 700 108, India;3. Dept. of Electronics and Telecommunication Engineering, Jadavpur University, Kolkata 700032, India;1. Iran University of Science and Technology, School of Mechanical Engineering, Tehran, Iran;2. Chalmers University of Technology, Department of Applied Mechanics, Gothenburg, Sweden;3. University of Houston, Department of Mechanical Engineering, Houston, USA |
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| Abstract: | Radio frequency identification (RFID) is widely used for item identification and tracking. Due to the limited communication range between readers and tags, how to configure a RFID system in a large area is important but challenging. To configure a RFID system, most existing results are based on cost minimization through using 0/1 identification model. In practice, the system is interfered by environment and probabilistic model would be more reliable. To make sure the quality of the system, more objectives, such as interference and coverage, should be considered in addition to cost. In this paper, we propose a probabilistic-based multi-objective optimization model to address these challenges. The objectives to be optimized include number of readers, interference level and coverage of tags. A decomposition-based firefly algorithm is designed to solve this multi-objective optimization problem. Virtual force is integrated into random walk to guide readers moving in order to enhance exploitation. Numerical simulations are introduced to demonstrate and validate our proposed method. Comparing with existing methods, such as Non-dominated Sorting Genetic Algorithm-II and Multi-objective Particle Swarm Optimization approaches, our proposed method can achieve better performance in terms of quality metric and generational distance under the same computational environment. However, the spacing metric of the proposed method is slightly inferior to those compared methods. |
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| Keywords: | RFID network planning Multi-objective firefly algorithm Decomposition Identification probability |
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