We consider single machine batching and scheduling problem in which the processing time of each job is known, but the setup time is a random variable from the distribution with an unknown parameter. Batch sizes are determined sequentially, that is, the size and jobs of the first batch are determined by using the prior knowledge and observed the value of a setup time, then the size and jobs of t...

Material handling robots are routinely used for transferring parts in an interconnected multi-machine cell. The sequence of robot movements between machines is arrived at by the operator, either intuitively or by the use of some form of off-line analysis. It would be extremely beneficial if robots can be provided with additional intelligence to automatically sequence their control programs the...

In this paper, we consider an integrated scheduling problem of production and distribution for manufacturers. In the production part, the batch-processing machines have fixed capacity and the jobs have arbitrary sizes and processing times. Jobs in a batch can be processed together, provided that the total size of the jobs in the batch does not exceed the machine capacity. The processing time of...

Online job scheduling has demonstrated to be a key factor impacting the output performance of batch processing systems. Existing researches either proposed solutions to a single-machine processing system, or focused on minimizing the total job completion time for multiple-machine batch processing systems. Yet the study on the approaches with the objective of minimizing the job delay time on a p...

An important special case of the problem studied in Cheng and Kovalyov (1996) arises when there are equal setup times and equal job processing times. Computational complexity of this case was indicated to be open, however. I prove its NP-hardness. Cheng and Kovalyov [l] introduced the following due date assignment and scheduling problem. There are n groups of jobs to be scheduled for processing...

A flow-shop batching problem with consistent batches is considered in which the processing times of all jobs on each machine are equal to p and all batch set-up times are equal to s. In such a problem one has to partition the set of jobs into batches and to schedule the batches on each machine. The processing time of a batch Bi is the sum of processing times of operations in Bi and the earliest...

This paper proposes an online solver of the dual formulation of support vector machines for structured output spaces. We apply it to sequence labelling using the exact and greedy inference schemes. In both cases, the per-sequence training time is the same as a perceptron based on the same inference procedure, up to a small multiplicative constant. Comparing the two inference schemes, the greedy...

While both cost-sensitive learning and online learning have been studied extensively, the effort in simultaneously dealing with these two issues is limited. Aiming at this challenge task, a novel learning framework is proposed in this paper. The key idea is based on the fusion of online ensemble algorithms and the state of the art batch mode cost-sensitive bagging/boosting algorithms. Within th...

Automatic post-editing (APE) for machine translation (MT) aims to fix recurrent errors made by the MT decoder by learning from correction examples. In controlled evaluation scenarios, the representativeness of the training set with respect to the test data is a key factor to achieve good performance. Real-life scenarios, however, do not guarantee such favorable learning conditions. Ideally, to ...

In this paper we consider the problem of scheduling N jobs on a single machine, where the jobs are processed in batches and the processing time of each job is a simple linear increasing function depending on job’s waiting time, which is the time between the start of the processing of the batch to which the job belongs and the start of the processing of the job. Each batch starts from the setup ...