Multi-objective reconfigurable production line scheduling forsmart home appliances

In a typical discrete manufacturing process, new type of reconfigurable production line is introduced, which aims to help small- and mid-size enterprises improve machine utilization reduce cost. order effectively handle the scheduling problem for system, an improved multi-objective particle swarm optimization algorithm based on Brownian motion (MOPSO-BM) proposed. Since existing MOPSO algorithms are easily stuck in local optimum, global search ability proposed method enhanced random mechanism BM. To further strengthen capacity, strategy fitting inertia weight with piecewise Gaussian cumulative distribution function (GCDF) included, helps maintain excellent convergence rate algorithm. Based commonly used indicators generational distance (GD) hypervolume (HV), we compare MOPSO-BM several other latest benchmark functions, it shows better overall performance. Furthermore, real smart home appliances, three algorithms, namely non-dominated sorting genetic algorithm-II (NSGA-II), decomposition-based (dMOPSO) MOPSO-BM, applied tackle problem. It demonstrated that outperforms others terms quality solutions.