constraint programming
PulseAugur coverage of constraint programming — every cluster mentioning constraint programming across labs, papers, and developer communities, ranked by signal.
6 day(s) with sentiment data
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New ASP approach tackles UAM strategic deconfliction
Researchers have developed a new approach using Answer Set Programming (ASP) to manage strategic deconfliction in Urban Air Mobility (UAM) operations. This method focuses on synchronizing flight times and optimizing rou…
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Answer Set Programming enhanced with new semantics and LLM-driven optimization · 2 sources tracked
Two new research papers explore advancements in Answer Set Programming (ASP). The first paper introduces a unified logical framework, Bound-Founded Semantics, to characterize various semantics for ASP extensions with li…
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New global propagator for difference constraints boosts constraint programming efficiency
Researchers have developed a new global propagator for difference constraints within constraint programming. This approach treats all difference constraints simultaneously, offering a more efficient method than standard…
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New SEER method uses ML to optimize energetic reasoning in constraint programming
Researchers have developed a novel approach called SEER, which utilizes supervised machine learning to optimize the use of energetic reasoning propagators in constraint programming. This method aims to balance the compu…
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New dynamic programming method enhances optimization techniques
Researchers have developed a new method for column generation and branch-and-price (B&P) optimization techniques by integrating domain-independent dynamic programming (DIDP) as a generic pricing solver. This approach ai…
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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…
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New logic-based method optimizes energy costs in project scheduling
Researchers have developed novel approaches to tackle the Resource-Constrained Project Scheduling Problem (RCPSP) when incorporating time-of-use energy tariffs and machine states. The proposed methods include a monolith…
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AI models tackle complex aircraft disassembly scheduling
Researchers have developed new computational models to optimize the complex scheduling of aircraft disassembly. This process is critical for sustainability and profitability in the aviation industry, involving thousands…
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Researchers combine DP and CP for scheduling problem
Researchers have demonstrated a novel hybrid approach combining Dynamic Programming (DP) and Constraint Programming (CP) to tackle the Partial Shop Scheduling Problem (PSSP). This method uses DP as the main search frame…