In this paper we address the problem of batching orders in a warehouse, with the objective of minimizing the total travel time. Order batching is an NP-hard optimization problem that is very difficult to solve exactly in practice. Thus, most implemented solutions are based on elementary heuristic methods that perform a relatively limited exploration of the solution space. As an alternative, we ...

In this paper we provide a novel approach to characterize the order process of an (s, S) and an (r, nQ) inventory policy. These inventory policies are commonly used when a fixed order cost is present. We provide two distinct perspectives. First, we analyze the time between subsequent replenishments, as well as the size of the replenishment orders, and characterize the distribution of both. Seco...

Order picking has been considered as one of the most critical operations in warehouse. In this study, we propose an analytical approximation model based on probability and queueing network theory to analyze order batching and picking area zoning on the mean order throughput time in a synchronized zone picker-to-part order picking system. The resulting model can be easily applied in the design a...

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...

This paper develops Order Acceptance for an Integrated Production-Distribution Problem in which Batch Delivery is implemented. The aim of this problem is to coordinate: (1) rejecting some of the orders (2) production scheduling of the accepted orders and (3) batch delivery to maximize Total Net Profit. A Mixed Integer Programming is proposed for the problem. In addition, a hybrid meta-heuristic...

This paper introduces a grouped genetic algorithm (GGA) to solve the order batching and sequencing problem with multiple pickers (OBSPMP) objective of minimizing total completion time. To best our knowledge, for first time, an OBSPMP is solved by means GGA considering picking devices heterogeneous load capacity. For this, encoding scheme proposed represent in chromosome orders assigned batches,...

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...