Concept: Scheduling (production processes)
Spectral metrics predicted requirements integration effort
Using graph metrics to predict effort required for integrating complex system requirements
Enhanced grey wolf optimization improved cloud load balancing
Algorithm improves cloud computing resource distribution and workload balancing
Scheduling model integrates pallets, machines, and setup stations
Scheduling production when machines share loading stations and fixture pallets
Optimizing integrated energy systems with a virtual energy station framework: Exergy-based scheduling and multi-energy integration
A framework for coordinating electricity, heat, gas, and hydrogen in complex energy systems
Proactive VM consolidation cuts energy use and SLA violations
Predicting server resource needs to cut energy costs while maintaining service quality
Hybrid deep learning improved edge-cloud task scheduling in simulation
Smart task scheduling for edge-cloud systems using deep learning
Hybrid scheduling algorithm cuts pharmaceutical production costs
Optimizing pharmaceutical production schedules to reduce manufacturing costs.
AGENT improved makespan in heterogeneous cloud task allocation
Optimizing task scheduling in cloud computing with evolutionary algorithms
Online genetic programming improved scheduling in dynamic job shops
Evolving scheduling strategies in real-time factory environments
Liger+ dynamically balances latency and throughput in large model inference
Dynamically balancing speed and throughput for serving large AI models across multiple GPUs
