This article proposes an end-to-end framework for solving multiobjective optimization problems (MOPs) using deep reinforcement learning (DRL), that we call DRL-based multiobjective optimization ...

Simulation results demonstrate that the proposed DRL-based utility optimization algorithm achieves faster inference speed compared to deep Q network and effectively improves the task processing rate, ...

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