Due to their wide area of applications, queueing models with batch service, where the server can process several customers simultaneously, have been studied frequently. An important characteristic of such batch-service systems is the size of a batch, that is the number of customers that are processed simultaneously. In this paper, we analyse a two-class batch-service queueing model with variabl...

This paper addresses a production and outbound distribution scheduling problem in which a set of jobs have to be process on a single machine for delivery to customers or to other machines for further processing. We assume that there is a sufficient number of vehicles and the delivery costs is independent of batch size but it is dependent on each trip. In this paper, we present an Artificial Imm...

Due to slow time variation, variable run length and nonlinearity of sequencing batch reactor (SBR) wastewater treatment batch process, a multivariate statistical MPCA model based on double moving window along the time×variable axis and batch-axis is used for online monitoring the progress of sequencing batch reactor. Moving window MPCA along the time×variable axis can copy seamlessly with varia...

Abstract. Queueing systems with batch service have been investigated extensively during the past decades. However, nearly all the studied models share the common feature that an uncorrelated arrival process is considered, which is unrealistic in several real-life situations. In this paper, we study a discrete-time queueing model, with a server that only initiates service when the amount of cust...

Training deep neural networks with Stochastic Gradient Descent, or its variants, requires careful choice of both learning rate and batch size. While smaller batch sizes generally converge in fewer training epochs, larger batch sizes offer more parallelism and hence better computational efficiency. We have developed a new training approach that, rather than statically choosing a single batch siz...

Previously, we derived the two-dimensional transforms of the emptiness function, the transient workload and queue-length distributions in the single-server queue with general service times and a batch Markovian arrival process (BMAP). This arrival process includes the familiar phase-type renewal process and the Markov modulated Poisson process as special cases, as well as superpositions of thes...

This paper describes the application of batch trajectory alignment, outlier detection, and multiblock multiway principal component analysis (MPCA) to data from an industrial active pharmaceutical ingredient manufacturing process. The process data routinely collected from historical batches, including temperatures, pressures, and controller outputs, has been used to improve process operation and...