Sensors deployment in logistics system by genetic invasive weed optimization

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Abstract

Real-time management for the production and manufacturing process of materials is necessary for the flexible manufacturing systems, RFID technique can master the processing situation of material transportation in real-time and thus improve the transportation control as well as the efficiency for the manufacturing system. We herein deploy the RFID readers and tags in the logistics system to manage the production process; and build the deployment mathematical model and the optimization strategies for RFID readers. We also propose a genetic invasive weed optimization (IWOGA) based on the invasive weed optimization (IWO) and genetic algorithm (GA) to optimize the deployment of RFID readers, IWOGA involves a comprehensive evolutionary mechanism therein with the objective of covering all the RFID tags in the whole system using the minimum number of RFID readers with the minimum working frequency. We validate the proposed optimization algorithm in comparison with IWO and GA respectively by a practical numerical example of sensors deployment in logistics system.

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Shi, Y., Hou, L., Sun, X., & Pan, Y. (2016). Sensors deployment in logistics system by genetic invasive weed optimization. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9864 LNCS, pp. 381–392). Springer Verlag. https://doi.org/10.1007/978-3-319-45940-0_35

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