Traditional high performance computing (HPC)/ supercomputing, analytics and mainstream realtime/batch computing are quickly converging. Mainstream workloads are crossing over the high performance computing arena, demanding faster analytics/batching, resource-intensive computations and algorithms. To succeed in today’s accelerating digital world, enterprises must collect and analyze mind-bogglin...

We describe an extension procedure for constructing new standardized time series procedures from existing ones. The approach is based on averaging over sample paths obtained by permuting path segments. Analytical and empirical results indicate that permuting improves standardized time series methods. We compare permuting to an alternative extension procedure known as batching. We demonstrate th...

In this work, a novel sequence-based mixed-integer linear programming formulation for the simultaneous batching and scheduling in multi-product multi-stage batch plants is developed. The selection of batches, the allocation of batches to processing units and the sequencing of batches in each unit constitute the discrete decisions of our model. Batch processing times and sizes are variables. Bat...

Advances in deep neural networks (DNN) and computer vision (CV) algorithms have made it feasible to extract meaningful insights from large-scale deployments of urban cameras. Tracking an object interest across the camera network near real-time is a canonical problem. However, current tracking platforms two key limitations: 1) They are monolithic, proprietary lack ability rapidly incorporate sop...

In this research, we study an extended version of the joint order batching and scheduling optimization for manual vegetable picking packing lines with consideration workers’ fatiguing effect. This problem is faced by many B2C fresh produce grocers in China on a daily basis which could severely decrease overall workflow efficiency distribution center customer satisfaction. sequencing problem, se...