L. Kleinrock, Queueing Systems, Vol. I, Theory. Wiley, New York, 1976. [Pg.626]

The flow line is modeled by a tandem queueing system with m stages and with finite buffer capacities b, ..., b with bj = Zi + where is the number of spaces in buffer i, and exponentially distributed processing times with mean 1/fjLj, i = 1,2,. m. The Jobs arrive at the flow line according to a Poisson process with rate A. [Pg.1642]

Ml MU and M/M/c queueing systems can be directly applied to this queueing network model. Particularly when there is only a single machine at each machine center (i.e. Cj = 1, i = 1,.. . , m), we have [Pg.1651]

S. Stidham. Optimal control of admission to a queueing system. IEEE Trans. Automatic Control, AC-30 705-713, 1985. [Pg.391]

Kleinrock, L. 1975. Queueing Systems. Vol. 1. Toronto John Wiley Sons,pp. 71-72, 119-134. [Pg.854]

IX, b) be the mean number of customers in an M/M/l/b queueing system with arrival rate A, service rate fx, and buffer capacity b. If p = /p., [Pg.1642]

Let the outstanding orders correspond to the jobs in the queueing system. In the inventory system, each of these orders will materialize (or arrive —become available to supply demand) after a lead time. This corresponds to a queueing system with an infinite number of servers, so that any job will be served immediately on arrival. Hence, the overall cycle time of each job in the system is simply its service time, which corresponds to the lead time of orders in the inventory system. [Pg.1672]

Prior Scientific Instruments Ltd., London Rd., Bishop s Stanford, Herts. CM23 5NB. Queue Systems (see Camlab.). [Pg.330]

Gordon, W. J., and Newell, G. F. (1967), Qosed Queueing Systems with Exponential Servers, Operations Research, Vol. 15, pp. 254-265. [Pg.1668]

Suppose demand follows a Poisson process with rate A, and suppose the lead time is L, the time it takes to process and finish an order. Then the queueing system in question is an M/GI > model (see, e.g., Wolff 1989), and it is known that N follows a Poisson distribution with mean p = AE(L). That is, [Pg.1672]

The program comes with its own job queue system. Jobs are submitted to this queue via a script, which can be edited to utilize third-party batch-queuing systems instead. [Pg.331]

Sennott, L. I. (1999), Stochastic Dynamic Programming and the Control of Queueing Systems, John Wiley Sons, New York. [Pg.2648]

Batch-and-queue system Refers to a production management system that relies on large batches of material. This leads to large queues while waiting to complete a production step. Such systems are characterized by high work in process inventory and low velocity production. [Pg.518]

Gaussian is designed to execute as a batch job. It can readily be used with common batch-queueing systems. The program may be purchased as source code or executables and comes with hundreds of sample input and output files. These may be employed as examples of how to construct inputs. They may also be employed to verify that a compilation from source code was successful. In our experience, such verification is essential. [Pg.337]

Gaussian users will find that Q-Chem feels familiar. The ASCII input format is a bit more wordy than Gaussian it is more similar to GAMESS input. The output is very similar to Gaussian output, but a bit cleaner. The code can easily be used with a job-queueing system. [Pg.340]

Let D(t) be the demand in period t, t = 1, 2,. . . Suppose demand (per period) over time is independent and identically distributed. Let L denote the lead time to flU each replenishment order. The number of outstanding orders, as explained in Section 2.1, is equal to the number of jobs, N, in an infinite-server queueing system. In particular, if the per-period demand follows a Poisson distribution, then N also follows a Poisson distribution with mean E(N) = E(D) E(L) (= p in Section 2.1 here D denotes the generic per-peiiod demand). Since N follows a Poisson distribution, we know Var(A0 = E(A0- [Pg.1674]

There is a screen to set up the calculation that has menus for the most widely used functions. Many users will still need to know many of the keywords, which can be typed in. There was no default comment statement, so the input file created would not be valid if the user forgot to include a comment. A calculation can be started from the graphic interface, which will be run interactively by default. The script that launches the calculation was not too dilficult to modify for use with a job-queueing system. [Pg.350]

The calculation setup screens list a good selection of the options that are most widely used. However, it is not a complete list. The user also chooses which queue to use on the remote machine and can set queue resource limits. All of this is turned into a script with queue commands and the job input file. The user can edit this script manually before it is run. Once the job is submitted, the inputs are transferred to the server machine, the job is run and the results can be sent back to the local machine. The server can be configured to work with an NQS queue system. The system administrator and users have a reasonable amount of control in configuring how the jobs are run and where files are stored. The administrator should look carefully at this configuration and must consider where results will be sent in the case of a failed job or network outage. [Pg.332]

AMPAC can also be run from a shell or queue system using an ASCII input file. The input file format is easy to use. It consists of a molecular structure defined either with Cartesian coordinates or a Z-matrix and keywords for the type of calculation. The program has a very versatile set of options for including molecular geometry and symmetry constraints. [Pg.341]

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