Big Data Analysis and Scheduling Optimization System Oriented Assembly Process for Complex Equipment

Scalable System Scheduling for HPC and Big Data

In the rapidly expanding field of parallel processing, job schedulers are the “operating systems” of modern big data architectures and supercomputing systems. Job schedulers allocate computing resources and control the execution of processes on those resources. Historically, job schedulers were the domain of supercomputers, and job schedulers were designed to run massive, long-running computati...

Equipment capacity optimization of an educational building’s CCHP system by genetic algorithm and sensitivity analysis

Combined cooling, heating, and power (CCHP) systems produce electricity, cooling, and heat due to their high efficiency and low emission. These systems have been widely applied in various building types, such as offices, hotels, hospitals and malls. In this paper, an economic and technical analysis to determine the size and operation of the required gas engine for specific electricity, cooling, ...

Big Data Analysis for Resource-Constrained Surgical Scheduling

The scheduling of surgical operations in a hospital is a complex problem, with each surgical specialty having to satisfy their demand while competing for resources with other hospital departments. This project extends the construction of a weekly timetable, the Master Surgery Schedule, which assigns surgical specialties to operating theater sessions by taking into account the post-surgery resou...

Convex Optimization for Big Data

This article reviews recent advances in convex optimization algorithms for Big Data, which aim to reduce the computational, storage, and communications bottlenecks. We provide an overview of this emerging field, describe contemporary approximation techniques like first-order methods and randomization for scalability, and survey the important role of parallel and distributed computation. The new...

Big Data Complex Data