Uncertain logistics RFID reader deployment method based on robust particle swarm optimization

Abstract

The invention discloses an uncertain logistics RFID reader deployment method based on robust particle swarm optimization. The method comprises the following steps: a reference sensor senses an uncertain-range probabilistic sensing model and establishes a coverage model; Monte carlo sampling is performed by a concentric circle method, and the degree of conflict is calculated; the cost is described with the number of readers used; a logistics RFID reader deployment robust optimization model with uncertain electronic tag positions is established by taking the coverage rate, the degree of conflict and the cost into consideration; and a sampling method in which the sample size changes with the number of iterations and a robust particle swarm optimization algorithm are fused. The method of the invention has the following beneficial effects: the robust optimization performance of the deployment method is improved under the condition of limited sample size; in the early stage of iteration, the expected value of sample size is small, and algorithm exploration is speeded up; and in the later stage of iteration, the expected value of sample size is large, and the precision of sample development is improved. By adopting the method, RFID readers can be deployed reasonably, an uncertain logistics RFID network can be optimized, the coverage of an RFID network can be increased, the conflict between readers can be reduced, and the cost of an RFID network can be lowered.

Description

technical field [0001] The invention relates to an RFID reader deployment method for uncertain logistics. Background technique [0002] When using RFID networks in logistics storage spaces such as warehouses and yards, items with electronic tags may be placed randomly. How to effectively arrange readers to make RFID network coverage higher, conflicts smaller, and lower costs , is an important issue in RFID applications. Due to the nonlinearity and complexity of the problem, many researchers currently use intelligent optimization methods, such as genetic algorithm, particle swarm optimization algorithm, etc., to study the deployment optimization of RFID readers under certain conditions. [0003] In the actual logistics storage space, the items in the RFID network may only be placed in the designated area, the items may be placed upright and reversed, and the label is only attached to one side of the item, so the label is often located in a certain range of uncertainty, rathe...

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Therefore, this relatively direct method requires more additional fitness function evaluations, ...

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