This book is to presents and evaluates a way of modelling and optimizing nonlinear RFID Network
Planning (RNP) problems using artificial intelligence techniques. It uses Artificial Neural
Network models (ANN) to bind together the computational artificial intelligence algorithm with
knowledge representation an efficient artificial intelligence paradigm to model and optimize
RFID networks. This effort leads to proposing a novel artificial intelligence algorithm which
has been named hybrid artificial intelligence optimization technique to perform optimization of
RNP as a hard learning problem. This hybrid optimization technique consists of two different
optimization phases. First phase is optimizing RNP by Redundant Antenna Elimination (RAE)
algorithm and the second phase which completes RNP optimization process is Ring Probabilistic
Logic Neural Networks (RPLNN). The hybrid paradigm is explored using a flexible manufacturing
system (FMS) and the results are compared with well-known evolutionary optimization technique
namely Genetic Algorithm (GA) to demonstrate the feasibility of the proposed architecture
successfully.
