Tradeoff Curves, Targeting and Balancing in Manufacturing Queueing Networks

In this paper, we introduce the notions of tradeoff curves, targeting and balancing in manufacturing systems to describe the relationship between variables such as work-in-process, lead-time and capacity. We consider multiproduct manufacturing systems modeled by open networks of queues and formulate the targeting TP and balancing BP problems as nonlinear programs. These formulations are based primarily on parametric decomposition methods for estimating performance measures in open queueing networks. Since TP and BP typically are hard to solve, we show that under fairly realistic conditions they can be approximated by easily solvable convex programs. We present heuristics to obtain approximate solutions to these problems and to derive tradeoff curves. We also provide bounds on the performance of the heuristics, relative to the approximation problems, and show that they are asymptotically optimal under mild conditions.

[1]  David D. Yao,et al.  Reducing the congestion in a class of job shops , 1987 .

[2]  David D. Yao,et al.  Stochastic Monotonicity of the Queue Lengths in Closed Queueing Networks , 1987, Oper. Res..

[3]  Leon S. Lasdon,et al.  Optimization Theory of Large Systems , 1970 .

[4]  Arnoldo C. Hax,et al.  Production and inventory management , 1983 .

[5]  W. Whitt,et al.  Performance of the Queueing Network Analyzer , 1983, The Bell System Technical Journal.

[6]  J. Shanthikumar,et al.  Stochastic convexity and its applications , 1988, Advances in Applied Probability.

[7]  D C LittleJohn A Proof for the Queuing Formula , 1961 .

[8]  J. A. Buzacott,et al.  On Approximate Queueing Models of Dynamic Job Shops , 1985 .

[9]  Yu-Chi Ho,et al.  Optimization of large multiclass (non-product. form queueing networks using perturbation analysis , 1984 .

[10]  Dimitri P. Bertsekas,et al.  Constrained Optimization and Lagrange Multiplier Methods , 1982 .

[11]  Ward Whitt,et al.  A Light-Traffic Approximation for Single-Class Departure Processes from Multi-Class Queues , 1988 .

[12]  W. Whitt,et al.  The Queueing Network Analyzer , 1983, The Bell System Technical Journal.

[13]  Yves Dallery,et al.  An efficient method to determine the optimal configuration of a flexible manufacturing system , 1988 .

[14]  J. A. Buzacott,et al.  Flexible manufacturing systems: a review of analytical models , 1986 .

[15]  Rajan Suri,et al.  A Concept of Monotonicity and Its Characterization for Closed Queueing Networks , 1985, Oper. Res..

[16]  D. Yao,et al.  The effect of increasing service rates in a closed queueing network , 1986 .

[17]  R. Hayes Restoring our competitive edge , 1984 .

[18]  Kathryn E. Stecke,et al.  The Optimality of Unbalancing Both Workloads and Machine Group Sizes in Closed Queueing Networks of Multiserver Queues , 1985, Oper. Res..

[19]  J. George Shanthikumar,et al.  Optimal server allocation in a system of multi-server stations , 1987 .

[20]  J. A. Buzacott,et al.  Open queueing network models of dynamic job shops , 1981 .

[21]  Susan L. Albin,et al.  Delays for customers from different arrival streams to a queue , 1986 .

[22]  Mordecai Avriel,et al.  Nonlinear programming , 1976 .

[23]  D. Yao,et al.  The Optimal Input Rates To A System Of Manufacturing Cells , 1987 .

[24]  David D. Yao,et al.  On Server Allocation in Multiple Center Manufacturing Systems , 1988, Oper. Res..

[25]  Xi-Ren Cao,et al.  The phantom customer and marked customer methods for optimization of closed queueing networks with blocking and general service times , 1983, SIGMETRICS '83.

[26]  S. Wheelwright,et al.  Restoring Our Competitive Edge: Competing Through Manufacturing , 1984 .