To automatically annotate songs with descriptive keywords, a variety of content-based auto-tagging strategies have been proposed in recent years. Different approaches may capture different aspects of a song’s musical content, such as timbre, temporal dynamics, rhythmic qualities, etc. As a result, some auto-taggers may be better suited to model the acoustic characteristics commonly associated w...

scheduling for job shop is very important in both fields of production management and combinatorial op-timization. however, it is quite difficult to achieve an optimal solution to this problem with traditional opti-mization approaches owing to the high computational complexity. the combination of several optimization criteria induces additional complexity and new problems. in this paper, we pro...

We consider a single inventory location where multiple types of repairable spare parts are kept to service several different fleets of assets. Demand for each part is modeled by a Markov modulated Poisson process (MMPP). Each fleet has a target for the maximum expected mean number of assets down for lack of a spare part. The inventory manager can meet this target by stocking repairables and by ...

For some time we have been studying the is sues involved in job shop scheduling in an envi ronment of cooperative distributed agents none of which has a complete view of the resources available or of the tasks to be scheduled Sched ules produced cooperatively by such distributed agents using constraint satisfaction methods are often not optimal because of the inherent asyn chronicity of the dis...

Flexible flow shop scheduling problem (also called blended flow shop scheduling problem) is a sort of complex Job Shop Scheduling problem. For the Flexible Flow Shop scheduling problem, only in very special cases, there are polynomial optimal algorithms. In most of the other cases, the problems are NP-Hard. It is a simplification of the original problem to solve Flexible flow shop scheduling wi...

Simulation technology holds tremendous promise for the manufacturing industry. A machine shop data model has been developed at the National Institute of Standards and Technology (NIST) to represent neutral machine shop data for supporting machine shop manufacturing simulation [1]. This paper discusses the data model and its application in manufacturing simulation. The paper also proposes an app...

In this paper, we analyze the characteristics of the dynamic job shop scheduling problem when machine breakdown and new job arrivals occur. A hybrid approach involving neural networks(NNs) and geneticalgorithm(GA) is presented to solve the dynamic job shop scheduling problem as a static scheduling problem. The objective of this kind of job shop scheduling problem is minimizing the completion ti...

The distributed blocking flow shop scheduling problem (DBFSP) allows modeling the scheduling process in companies with more than one factory. It configures production systems as flow shop lines where the blocking constraint must be considered. To the best of our knowledge, this variant of the distributed permutation flow shop scheduling problem has not been studied. In this working paper, we sh...