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Radio frequency identification (RFID) is a technology with numerous benefits in applications where objects have to be identified automatically. However, cost, fragile tags, collision and reading errors are some of issues to be concerned with in an RFID implementation. Mainly, this paper proposes a method for tag identification and a method for the selection of the binary codes to program on the tags in order to facilitate the identification process. For the identification method a heuristic based on Hamming distance is developed where the basic idea is to utilize the information obtained in consecutive read attempts to help identify a tag. For the selection method three models based on Hamming distance are also developed which strive to find the set with the greatest dissimilarity among the codes. Computer simulations are performed to verify the validity of the proposed methods.

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Based on a case study, this paper deals with the production planning and scheduling problem of the glass container industry. This is a facility production system that has a set of furnaces where the glass is produced in order to meet the demand, being afterwards distributed to a set of parallel molding machines. Due to huge setup times involved in a color changeover, manufacturers adopt their own mix of furnaces and machines to meet the needs of their customers as flexibly and efficiently as possible. In this paper we proposed an optimization model that maximizes the fulfillment of the demand considering typical constraints from the planning production formulation as well as real case production constraints such as the limited product changeovers and the minimum run length in a machine. The complexity of the proposed model is assessed by means of an industrial real life problem.