Cyclic scheduling line with uncertain data

Abstract

In this paper, a cyclic permutation flow shop problem for a certain production line with uncertain data is considered. The goal is to minimize the cycle time. The uncertain elements in the system are identified and modeled as fuzzy numbers. A metaheuristic fuzzy-aware algorithm is developed and tested against 3 deterministic algorithms. The fuzzy algorithm significantly outperforms deterministic algorithms 70% of the time with similar computation time. The fuzzy algorithm is also more reliable, providing solutions with smaller standard deviation.