Order picking is a warehouse function dealing with the retrieval of articles from their storage location in order to satisfy a given demand specified by customer orders. Of all warehouse operations, order picking is considered to include the most cost-intensive ones. Even though there have been different attempts to automate the picking process, manual order picking systems are still prevalent ...

Batching plays an important role in performance evaluation of manufacturing systems. Three types of batching are commonly seen: transfer batches, parallel batches and serial batches. To model the batching behavior correctly, a comprehensive classification of batching is proposed. Eight types of batching behavior are classified and corresponding queueing models are given. The newly proposed mode...

Marcus et al. (2011) describe using Amazon’s Mechanical Turk (MTurk) systems utilizing crowds for database sorts and joins. Crowdsourcing activities for these types of queries are typical costly in order to ensure accuracy and reliability. The authors present an interface for optimizing these functions in order to determine cost-effectiveness of various methods (simple join, naïve batching, and...

Savings in the number of page accesses due to batching on sequential, tree-structured, and random files are well known and have been reported in the literature. This paper asserts that substantial savings can also be obtained in database organizations by batching the requests for records (in queries), and also by batching intermediate processing requests while traversing the database. A simple ...

 Building a Transparent Batching Layer for Storm Matthias J. Sax, Malu Castellanos HP Laboratories HPL-2013-69 streaming data, distributed streaming system, batching, performance, optimization Storm is a distributed intra-node-parallel stream processing system built for very low latency processing. One major drawback of Storm is its relatively low throughput. In order to increase Storm's throu...

We address the problem of batching messages generated at nodes of a sensor network for the purpose of reducing communication energy at the expense of added latency. We consider a time-based batching approach. We first develop baseline analytical models based on Markovian assumptions, derive conditions under which batching is profitable, and explicitly determine a batching time that optimizes a ...

In this paper, we present the results of a simulation study for the performance evaluation of certain batching strategies in a multi-product semiconductor wafer fabrication facility (waferfab). Batching in waferfabs means that we can process different lots at the same time on the same machine. As opposite to common scheduling and dispatching decisions in manufacturing beside assignment and sequ...

The power of warehousing system to rapidly respond to customer demands participates an important function in the success of supply chain. Before picking the customer orders, effectively consolidating orders into batches can significantly speed the product movement within a warehouse. There is considerable product movement within a warehouse; the warehousing costs can be reduced by even a small ...

Performing inference on pre-trained neural network models must meet the requirement of low-latency, which is often at odds with achieving high throughput. Existing deep learning systems use batching to improve throughput, which do not perform well when serving Recurrent Neural Networks with dynamic dataflow graphs. We propose the technique of cellular batching, which improves both the latency a...

Paxos is probably the most known state machine replication protocol. Two optimizations that can greatly improve its performance are batching and pipelining. Their effectiveness depends significantly on the system properties, mainly network latency and bandwidth, but also on the CPU speed and properties of the application. This makes it hard to know when and how to use each optimization to achie...