Author

Gerald M. Knapp

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Preprint Aug 2026

Dynamic Multi-Depot Vehicle Routing with Online Requests: Event-Driven Transformer--DRL and Rolling-Horizon Benchmarking

This paper presents an event-driven learning and benchmarking framework for the Dynamic Multi-Depot Vehicle Routing Problem with progressively revealed requests and evolving vehicle states. Masked MLP and Transformer policies are trained through behavior cloning and proximal policy optimization. Deterministic feasibili...

Faezeh Ardali, Gerald M. Knapp · 0 citations

#reinforcement learning Conference Open access Sep 2026

A Deep Reinforcement Learning (DRL) Based Transformer Method for Solving the Open Shop Scheduling Problem

In this study, we investigate the potential of a Deep Reinforcement Learning (DRL) based Transformer neural network architecture to solve large-scale open shop scheduling problems. The open shop scheduling problem (OSSP) involves sequencing n jobs across m machines, where each machine handles only one job at a time, an...

Faezeh Ardali, Gerald M. Knapp · IISE Annual Conference &... · 0 citations