Decision-making of online rescheduling procedures using neuroevolution of augmenting topologies

HUOM! TÄMÄn MANUSKAn EMBARGO ON YLIPITKÄ KUNNES ARTIKKELI ON JULKAISTU JA JULKAISUVIIVE MÄÄRITELTY KUSTANTAJAN JULKAISUPÄIVÄSTÄ ALKAEN. The manuscript's embargo is very long until the article has been published and the embargo date can be defined. HUOM 2: Varmista, että julkaisun nimi pysyy samana: 29th European Symposium on Computer Aided Chemical [EI PROCESS KUTEN NYT JULKAISUN KUVAUKSESSA] EngineeringOnline scheduling requires appropriate timing of rescheduling procedures, as well as the determination of relevant horizon length. Optimal choices of these quantities are highly dependent on the uncertainty of the scheduling environment and may vary over time. We propose an approach where a neural network is trained to make online decisions on these quantities, as well as on the choice of the rescheduling method (mathematical programming or metaheuristics). In our approach, the neural network is trained using neuroevolution of augmenting topologies (NEAT) in a simulated environment. In this paper, we also optimize the rescheduling interval and horizon length of a conventional periodically occurring rescheduling on a dynamic routing problem. The resulting approach is the baseline for the development of the proposed neural network approach.Peer reviewe