Solving workshop layout by hybridizing invasive weed optimization with simulated annealing

We herein model workshop layout problem as quadratic assignment problem (QAP), which is an important NP-hard problem in logistics system. Moreover, we proposed an effective algorithm hybridizing invasive weed optimization (IWO for short) with the simulated annealing (SA) for solving this problem. Our basic idea is to employ IWO for providing diversity to explore solution, and use metropolis criterion of SA to provide a better direction. In our algorithm, we employed an offspring generation rule with disturbance, and used random-keys encoding to produce new solution for solving QAP. We also designed a harmonic coefficient to improve the fluctuation problem effectively. The computational results from equipment layout problems validated our algorithm.