EURO 2024 Copenhagen
Abstract Submission

EURO-Online login

1695. Periodic and Real-Time Dispatching Rule Selection for the Dynamic Job Shop Scheduling Problem

Invited abstract in session WB-60: Job shop scheduling, stream Project Management and Scheduling.

Wednesday, 10:30-12:00
Room: S09 (building: 101)

Authors (first author is the speaker)

1. Nuno Marques
Faculty of Engineering, University of Porto
2. Gonçalo Figueira
INESC-TEC, Faculty of Engineering of Porto University
3. Luis Guimarães
INESC TEC, Faculadade de Engenharia, Universidade do Porto

Abstract

Aggressive competition and wider production mixes are profoundly impacting manufacturing settings, which, in turn, have become more technological, flexible and dynamic. With growing uncertainty in the shop floor, dynamic scheduling emerged as a relevant topic to explore. In highly dynamic environments, dispatching rules (DRs) became a popular solution method for scheduling problems due to their reactive nature, ease of implementation and interpretability. However, DRs do not cope well with varying conditions in two main dimensions: shop load and job urgency. Therefore, researchers have proposed machine-learning-based systems that select DRs as conditions change over time. Two main approaches emerged in the literature: the periodic rule selection (PRS) and the real-time rule selection (RTRS). The goals of this work are twofold. First, propose PRS and RTRS systems that can outperform state-of-the-art DRs by relying on effective state and action sets. Secondly, contrast PRS and RTRS in the same dynamic job shop instances for stationary and non-stationary conditions, filling a gap in the literature. Results show that the best rule selection system reduces tardiness, on average, 14.8% in stationary instances, and 3.5% in non-stationary instances. Even in the hardest instances, the system comes within 1% of the best DR. Moreover, PRS reveals to be the most effective approach for stationary instances. In non-stationary conditions, RTRS was better.

Keywords

Status: accepted

Back to the list of papers