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Multi-objective RFID network planning with probabilistic coverage model by guided fireworks algorithm

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RFID technology is increasingly incorporated in many facets of life and accordingly represents an active research area. RFID network planning is a hard optimization problem that determines positions of readers and transmitter power parameters in order to satisfy requirements about coverage, interference, power consumption, total cost, etc. For such hard optimization problems, where deterministic mathematical methods are inadequate, stochastic swarm intelligence algorithms are very successful. In this paper we adjusted the recent guided fireworks algorithm for the RFID network planning problem with probabilistic model of coverage. Our proposed approach was tested on standard benchmark networks and compared with other algorithms from literature. Our approach proved to be better than other compared methods, considering the coverage, number of employed readers, used power and interference.

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RFID technology is increasingly incorporated in many facets of life and accordingly represents an active research area. RFID network planning is a hard optimization problem that determines positions of readers and transmitter power parameters in order to satisfy requirements about coverage, interference, power consumption, total cost, etc. For such hard optimization problems, where deterministic mathematical methods are inadequate, stochastic swarm intelligence algorithms are very successful. In this paper we adjusted the recent guided fireworks algorithm for the RFID network planning problem with probabilistic model of coverage. Our proposed approach was tested on standard benchmark networks and compared with other algorithms from literature. Our approach proved to be better than other compared methods, considering the coverage, number of employed readers, used power and interference.

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