Flexible job-shop scheduling with tolerated time interval and limited starting time interval based on hybrid discrete PSO-SA: An application from a casting workshop
PulseAugur coverage of Flexible job-shop scheduling with tolerated time interval and limited starting time interval based on hybrid discrete PSO-SA: An application from a casting workshop — every cluster mentioning Flexible job-shop scheduling with tolerated time interval and limited starting time interval based on hybrid discrete PSO-SA: An application from a casting workshop across labs, papers, and developer communities, ranked by signal.
2 day(s) with sentiment data
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LLM-based world model enhances dynamic scheduling, cuts tardiness by up to 46%
Researchers have developed a novel approach called Afterstate World-Model Planning (AWMP) that leverages large language models (LLMs) to improve dynamic scheduling. AWMP integrates an LLM as an exogenous component withi…
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BOLT learning approach optimizes job-shop scheduling with transport coupling
Researchers have developed BOLT, a novel multi-bottleneck learning approach for flexible job-shop scheduling, specifically addressing scenarios where scarce vehicle fleets transport jobs between stations. This method co…
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Deep Reinforcement Learning Tackles Time-Lag Scheduling in Module Factories
Researchers have developed a novel time-lag-aware deep reinforcement learning approach to optimize scheduling in prefabricated module factories. This method specifically addresses the significant delays caused by post-o…