Configuration of a Dynamic MOLS Algorithm for Bi-objective Flowshop Scheduling
Résumé
In this work, we propose a dynamic multi-objective local search (MOLS) algorithm whose parameters are modified while it is running and a protocol for automatically configuring this algorithm. Our approach applies automated configuration to a static pipeline that sequentially runs multiple configurations of the MOLS algorithm. In a series of experiments for well-known benchmark instances of the bi-objective permutation flowshop scheduling problem, we show that our dynamic approach produces substantially better results than static MOLS, and that longer pipeline (with a higher number of parameters) outperform shorter ones.