27 citations · 30 across the 5 of their papers we have counts for
5 papers · 1 filter
Distributed Optimization of Modular Production Systems using Model-based Reinforcement Learning with Inverse Models
Andreas Schwung, Steve Yuwono, Sofiene Lassoued +1
This paper presents a novel approach for data-driven self-learning control of highly flexible, modular manufacturing systems. Specifically, we employ a novel framework for model-ba…
Policy-Based Deep Reinforcement Learning Hyperheuristics for Job-Shop Scheduling Problems
Sofiene Lassoued, Asrat Gobachew, Stefan Lier +1
This paper proposes a policy-based deep reinforcement learning hyper-heuristic framework for solving the Job Shop Scheduling Problem. The hyper-heuristic agent learns to switch sch…
Policy-Based Reinforcement Learning with Action Masking for Dynamic Job Shop Scheduling under Uncertainty: Handling Random Arrivals and Machine Failures
Sofiene Lassoued, Stefan Lier, Andreas Schwung
We present a novel framework for solving Dynamic Job Shop Scheduling Problems under uncertainty, addressing the challenges introduced by stochastic job arrivals and unexpected mach…
Flexible Manufacturing Systems Intralogistics: Dynamic Optimization of AGVs and Tool Sharing Using Coloured-Timed Petri Nets and Actor-Critic RL with Actions Masking
Sofiene Lassoued, Laxmikant Shrikant Bahetic, Nathalie Weiß-Borkowskib +2
Flexible Manufacturing Systems (FMS) are pivotal in optimizing production processes in today's rapidly evolving manufacturing landscape. This paper advances the traditional job sho…
Introducing PetriRL: An Innovative Framework for JSSP Resolution Integrating Petri nets and Event-based Reinforcement Learning
Sofiene Lassoued, Andreas Schwung
Resource utilization and production process optimization are crucial for companies in today's competitive industrial landscape. Addressing the complexities of job shop scheduling p…