Hyper-heuristic for flexible job shop scheduling problem with stochastic job arrivals

Abstract

Flexible job shop is prevalent in high-mix, low-volume (HMLV) production. Real-world HMLV production environments are subjected to fluctuating demands that cause jobs to arrive stochastically. This research presents a simulated annealing-based hyper-heuristic (SA-HH) for solving a flexible job shop scheduling problem with stochastic job arrivals. Two variants of SA-HH that involve a heuristic scheme with and without problem state features are introduced. Experimental results reveal that in terms of the average makespan, SA-HH outperforms a benchmark heuristic on all 10 benchmark instances.