Abstract Process mining techniques use event data to describe business processes, where the provided insights are used for predicting processes’ future states ( Predictive Monitoring ). Remaining Time Prediction of process instances is an important task in field (PPM). Existing approaches have two key limitations developing Models (RTM): (1) The features predictions lack context, and created mo...

We address the problem of scheduling a single batching machine to minimize the maximum lateness with a constraint restricting the batch size. A solution for this NP-hard problem is defined by a selection of jobs for each batch and an ordering of those batches. As an alternative, we choose to represent a solution as a sequence of jobs. This approach is justified by our development of a dynamic p...

This paper considers a scheduling problem for a single burn-in oven in the semiconductor manufacturing industry where the oven is a batch processing machine and each batch processing time is represented by the largest processing time among those of all the jobs contained in the batch. Each job belongs to one of the given number of families.Moreover, the release times of the jobs are di!erent fr...

In this paper we present the experience of a lean implementation in a Hospital. It all steamed out from a need to cut cost, and the focus on inventory reduction. The methodology adopted and the peculiarities of an implementation in a hospital are presented. A strong reduction in inventory has been achieved but, more important, broken processes which lead to excessive inventories have been ident...

We present a new algorithm for efficient occlusion culling using hardware occlusion queries. The algorithm significantly improves on previous techniques by making better use of temporal and spatial coherence of visibility. This is achieved by using adaptive visibility prediction and query batching. As a result of the new optimizations the number of issued occlusion queries and the number of ren...

Remote tusking encompasses different functionality, such as remote forking, multiple remote spawning, and task migration. In order to overcome the relatively high costs of these mechunisms, optimizations can be upplied at various levels of the underlying operating system or application. Optimizations include concurrent message transmission, increased throughput and reduced latency at the distri...

Hypercube algorithms are developed for a variety of communication-intensive tasks such as transposing a matrix, histogramming, sending a (long) message from one node to another, broadcasting a message from one node to all others, broadcasting a message from each node to all others, and exchanging messages between nodes via a fixed permutation. The algorithm for exchanging via a fixed permutatio...

Hypercube algorithms are developed for a variety of communication-intensive tasks such as transposing a matrix, histogramming, one node sending a (long) message to another, broadcasting a message from one node to all others, each node broadcasting a message to all others, and nodes exchanging messages via a fixed permutation. The algorithm for exchanging via a fixed permutation can be viewed as...

We consider a batch scheduling problem in which the processing time of a batch of jobs equals the maximum of the processing times of all jobs in the batch. This is the case, for example, for burn-in operations in semiconductor manufacturing, and other testing operations. Processing times are assumed to be random, and we consider minimizing the makespan and the flowtime. The problem is much more...

We consider the problem of partitioning interval graphs into cliques of bounded size. Each interval has a weight, and the cost of a clique is the maximum weight of any interval in the clique. This natural graph problem can be interpreted as a batch scheduling problem. Solving an open question from [7, 4, 5], we show NP-hardness, even if the bound on the clique sizes is constant. Moreover, we gi...