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Optimal Resource Allocation Problems (ORAP) G(V ) in TND

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Introduction to Queueing Networks

Overview

Chapter 7 begins the last of three chapters on optimization problems in topological network design (TND). While all the optimization problems are closely intertwined, we separate them due to the complexity and detail involved. We will build upon the open and closed algorithms which regulate the performance of the network and add optimization algorithms to define the best resources within the network.

• Resource Allocation Problems (ORAP)

These are the foremost problems one considers in improving stochastic flow processes as they are the most obvious ones and also some of the most significant.

• Optimal Routing Problems (ORTE)

Routing problems while related to the resource allocation ones in Chapter 7 are normally distinguishable because of certain application requirements. Accessibility and egress are good examples where routing is critical, but in telecommunications and computer network, routing problems are very significant. We will address these in Chapter 8

• Optimal Topology Problems (OTOP)

Optimal topology problems are perhaps the most challenging and complex network design problems because of their frequent integer requirements. Since they often comprise the resource allocation and routing problems, they are also quite significant to applications. We will close this volume in Chapter 9 by examining the OTOP.

Since the fabric of the universe is most perfect and the work of a most wise Creator, nothing at all takes place in the universe in which some rule of maximum or minimum does not appear

Leonard Euler

With four parameters I can fit an elephant, and with five I can make him wiggle his trunk.

John von Neumann

But I think it is a fact that no self-respecting company can get along without having some form of optimization in its planning structure or some kind of optimization in its day-to-day operations. Otherwise they’ll go out of business. They won’t be in competition with the others any more.

Harold Kuhn

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Notes

  1. 1.

    The following parameter values are used throughout all experiments reported in this paper: \(P = \$30.00/unit,V = \$10.00/unit,\bar{H} = \$0.50/unit\).

References

  1. Akyildiz, I.F., 1988. “On the Exact and Approximate Throughput Analysis of Closed Queueing Networks with Blocking,” IEEE Trans. Software Engineering, SE-14 (1), 62-71.

    Google Scholar 

  2. T. Altiok and S. Stidham, 1983. The allocation of interstage buffer capacities in production lines. IIE Transactions, 15:251–261.

    Article  Google Scholar 

  3. Buzacott, J.A., and Shantikumar, G. 1993. Stochastic Models of Manufacturing Systems. Prentice-Hall.

    MATH  Google Scholar 

  4. Daly, Leo A., 2012 “Checkpoint Design Guide (CDG).” Transportation Security Administration Revision 4.0, August 29,2012.

    Google Scholar 

  5. Fox, B.L., 1966. “Discrete Optimization via Marginal Analysis,” Mgmt. Sci., 3, 210-216.

    Article  Google Scholar 

  6. D. Gross and C. Harris. Fundamentals of Queueing Theory, Second Edition. John Wiley & Sons, New York, 2008.

    Book  Google Scholar 

  7. Himmelblau, D.M., 1972. Applied Nonlinear Programming. Mc-Graw-Hill.

    Google Scholar 

  8. Kelton, D.W, R. Sadowski, and D. Sturrock, 2003. Simulation with Arena. New York: McGraw-Hill.

    Google Scholar 

  9. Kerbache, L. and J. MacGregor Smith, 1987. “The Generalized Expansion Method for Open Finite Queueing Networks.” The European Journal of Operations Research 32, 448–461.

    Google Scholar 

  10. Onvural, Raif, and H. Perros 1989. “Throughput Analysis in Cyclic Queueing Networks with Blocking.” IEEE Trans. on Software Engineering. SE-15, 800-808.

    Google Scholar 

  11. Rolfe, A.J., 1971. “A Note on Marginal Allocation in Multiple Server Systems,” Mgmt. Sci., 9, 656-658.

    Article  Google Scholar 

  12. Rue, R.C. and Rosenshine, M., 1981. “Some Properties of Optimal Control Policies for Entries to an M/M/1 Queue,” Nav. Res. Log. Quart. 28, 525-532.

    Google Scholar 

  13. Smith, J. MacGregor and Sophia Daskalaki, 1988. Buffer space allocation in automated assembly lines. Operations Research, 36(2):343–358, March-April.

    Google Scholar 

  14. Smith, J. MacGregor and F.R.B. Cruz, 2005. “The Buffer Allocation Problem for General Finite Buffer Queueing Networks,” IIE Transactions: Design and Manufacturing 37(4), 343-365.

    Google Scholar 

  15. Smith, J. MacGregor and F.R.B. Cruz, 2014. “MGcc State Dependent Travel Time Models and Properties.” Physica A 395, 560-579.

    Google Scholar 

  16. Smith, J. MacGregor, 2017. “Simultaneous Buffer and Service Rate Allocation in Open Finite Queueing Networks.” accepted in IISE Transactions.

    Google Scholar 

  17. Smith, J. MacGregor, 2017. “Joint Optimization of Buffers and Network Population for Closed Finite Queueing Systems,” International Journal of Production Research. 54 (17), 5111-5135.

    Google Scholar 

  18. Smith, J. MacGregor and J. Kerbache, 2018. “Optimization of Service Rates and Servers for Closed Finite Queueing Systems.” accepted for publicationJournal of Manufacturing Systems.

    Google Scholar 

  19. Stidham, S., 2009 Optimal Design of Queueing Systems. CRC Press: Boca Raton.

    Book  Google Scholar 

  20. Yuzukirmizi, Mustafa Ph.D. 2005. “Closed Finite Queueing Networks with Multiple Servers and Multiple Customer Types,” Ph.D. Dissertation. Department of Industrial Engineering and Operations Research at the University of Massachusetts, Amherst Campus, Amherst, MA 10003.

    Google Scholar 

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Smith, J.M. (2018). Optimal Resource Allocation Problems (ORAP) G(V ) in TND. In: Introduction to Queueing Networks. Springer Series in Operations Research and Financial Engineering. Springer, Cham. https://doi.org/10.1007/978-3-319-78822-7_7

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