An effective approach in robustness optimization for solving the RFID network planning problem with uncertainty

RFID technology enables remote storage and retrieval of data on RFID tags, making it a versatile and efficient tool with widespread applications in various industries.  This paper presents a solution to the challenge of deploying RFID readers, which has been a persistent problem in the RFID technology practical and theoretical communities.  To address the deployment problem, the paper proposes a robust multi-objective approach that optimizes many requested objectives as: coverage, the number of deployed readers, and interference while taking into account uncontrollable

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

Radio-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 affect

Semi-active vibration absorbers for the high-rise objects

To determine the optimal parameters of the dynamic vibration absorber (DVA), a complete multi-parameter model of the dynamics of machines and structures is required. A model with two degrees of freedom is unacceptable for a sufficiently precise calculation with sufficient accuracy of the oscillations of the design, and thus for an adequate description of its dynamic characteristics. Therefore, in practice, it is necessary to investigate the design using a complex model.

Розроблення методики оцінювання важливості характеристик стеганографічних алгоритмів

In this paper the problem of estimating the importance of each of the characteristics of steganographic algorithms is solved. The resulting estimates are used in the analysis of the existing algorithms for information embedding and multiobjective choice of the best algorithm. The technique allows providing an equally weighted algorithms estimation, and also considers the importance of coefficients of characteristics.