formation of manufacturing cell using queuing theory and considering reliability

In this paper, a stochastic cell formation problem is studied considering the queuing theory and the reliability concept. A novel probabilistic mathematical model is presented considering interarrival times, processing times, and machines’ breakdown. Since the cell formation problem is NP-Hard, two algorithms are developed based on genetic and modified particle swarm optimization (MPSO) algorithms. Since the structure of the problem contains multiple irregularities, a new heuristic method is developed, which produces effective feasible solutions on demand. A deterministic branch and bound (B&B) algorithm is used to evaluate the results of modified particle swarm optimization algorithm and the genetic algorithm. The results indicate that proposed algorithms have better performance than the B&B algorithm of Lingo software according to the mixed effect of solution quality and computational times. The solution of two metaheurstic algorithms is compared by the t-test method. Ultimately, the results of numerical examples indicate that considering reliability has significant effect on the block structures of machine-part

Keywords:

Cell formation problem , Queuing theory , Particle swarm optimization algorithm , Genetic algorithm , Reliability