3 accepted papers
Many autonomous mobile robot path planning scenarios require servicing grouped delivery points. Such clustered routing problems are naturally formulated as the clustered traveling salesman problem (CluTSP), which comprises two interdependent subproblems: global inter-cluster routing to determine the
Under the shift toward Industry 4.0, mass-customized manufacturing systems have introduced complex scheduling problems, such as the Flexible Job Shop Scheduling Problem (FJSSP). Recent Deep Reinforcement Learning (DRL)-based heuristics have shown promise, yet existing methods often suffer from two k
Reinforcement Learning (RL) has shown promising results in solving Job Scheduling Problems (JSPs), automatically deriving powerful dispatching rules from data without relying on expert knowledge. However, most RL-based methods train only a single decision-maker, which limits exploration capability a…