Local Search for Flowshops with Setup Times and Blocking Constraints

Abstract

Permutation flowshop scheduling problem (PFSP) is a classical combinatorial optimisation problem. There exist variants of PFSP to capture different realistic scenarios, but significant modelling gaps still remain with respect to real-world industrial applications such as the cider production line. In this paper, we propose a new PFSP variant that adequately models both overlapable sequence-dependent setup times (SDST) and mixed blocking constraints. We propose a computational model for makespan minimisation of the new PFSP variant and show that the time complexity is NP Hard. We then develop a constraint-guided local search algorithm that uses a new intensifying restart technique along with variable neighbourhood descent and greedy selection. The experimental study indicates that the proposed algorithm, on a set of wellknown benchmark instances, significantly outperforms the state-of-the-art search algorithms for PFSP.