Teaching - Learning-based optimization approach for enhancing remanufacturability pre-evaluation system's reliability

Remanufacturability pre-evaluation is an important step at used products consolidation stage. In order to provide a quick sorting speed and reliable evaluation with a long lifespan, radio frequency identification (RFID) system is often employed in practice. A major factor that influences RFID system's reliability is the inaccuracy arising from missing data and reading errors, which are magnified to produce deleterious effects on reliability. A good yet simple solution is to add more redundant components (i.e., RFID readers) to smooth the RFID system's reliability. In this paper, we first formulate our focal scenario as a reliability-redundancy allocation problem (RRAP). Then, one of the recently developed swarm intelligence approach called teaching - learning-based optimization (TLBO), which is based on the effect of the influence of a teacher on the output of learners in a class, is employed to address our focal problem. Simulation results suggest that the proposed TLBO is a viable optimization technique in dealing with the optimization of RFID system's reliability.