Reinforcement learning (RL) is one of the most remarkable branches of machine learning
and attracts the attention of researchers from numerous fields. Especially in recent years, the …

This paper solves the flow-shop scheduling problem (FSP) through the reinforcement
learning (RL), which approximates the value function with neural network (NN). Under the …

The non-permutation flow-shop scheduling problem (NPFS) is studied. We model it as a
Markov decision process, creating a massive arena for reinforcement learning (RL) …

During the shipbuilding process, a block assembly line suffers a bottleneck when the largest
amount of material is processed. Therefore, scheduling optimization is important for the …

Manufacturing sites encounter various scheduling problems, which must be dealt with to
efficiently manufacture products and reduce costs. With the development of smart factory …

The present status of quantum computing is of the noisy intermediate-scale quantum (NISQ)
era. In addition to the limited number of available qubits, NISQ devices generally possess …

Nowadays, business processes (BPs) constitute the cornerstone of modern enterprise
information systems. The behaviour conveyed by those BP expresses various endogenous …

In this paper, we are interested in flow-rack automated storage/retrieval systems (AS/RS),
which are compact AS/RS. For this configuration of AS/RS we propose a new storage …

智能制造是我国制造业发展的必然趋势, 而智能车间调度是制造业升级和深化“两化融合”
的关键技术. 主要研究强化学习算法在车间调度问题中的应用, 为后续的研究奠定基础 …