Abstract: The distributed no-idle permutation flowshop scheduling problem (DNIPFSP) has widely existed in various manufacturing systems. The makespan and total tardiness are optimized simultaneously ...

Non-linear regression modeling is common in epidemiology for prediction purposes or estimating relationships between predictor and response variables. Restricted cubic spline (RCS) regression is one ...

Machine learning holds the potential to solve many real-world problems, but interpretability is a necessary prerequisite for practitioners in high-stakes domains such as medicine and law. Decision ...

Vehicle Routing Problem or simply VRP is a well known combinatorial optimization problem and a generalization of the travelling salesman problem. A definition of the problem is this: We have a number ...

Abstract: With the global energy shortage, climate anomalies, environmental pollution becoming increasingly prominent, energy saving scheduling has attracted more and more concern than before. This ...

Automatic detection of macromolecular complexes is an open and challenging problem in cellular cryoelectron tomography. Existing computational methods rely on known structural templates or manually ...

This work addresses the problem of reference tracking in autonomously learning robots with unknown, nonlinear dynamics. Existing solutions require model information or extensive parameter tuning, and ...

1 College of Mathematics and Statistics, Sichuan University of Science & Engineering, Zigong, China. 2 Sichuan Province University Key Laboratory of Bridge Non-destruction Detecting and Engineering ...