Distribution network design: Selection and sizing of congested connections

This paper focuses on certain types of distribution networks in which commodity flows must go through connections that are subject to congestion. Connections serve as transshipment and/or switching points and are modeled as M/G/1 queues. The goal is to select connections, assign flows to the connections, and size their capacities, simultaneously. The capacities are controlled by both the mean and the variability of service time at each connection. We formulate this problem as a mixed integer nonlinear optimization problem for both the fixed and variable service rate cases. For the fixed service rate case, we prove that the objective function is convex and then develop an outer approximation algorithm. For the variable service rate case, both mean and second moment of service time are decision variables. We establish that the utilization rates at the homogeneous connections are identical for an optimal solution. Based on this key finding, we develop a Lagrangian relaxation algorithm. Numerical experiments are conducted to verify the quality of the solution techniques proposed. The essential contribution of this work is the explicit modeling of connection capacity (through the mean and the variability of service time) using a queueing framework. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2005.

[1]  C. R. Bector Programming Problems with Convex Fractional Functions , 1968, Oper. Res..

[2]  G. Nemhauser,et al.  Integer Programming , 2020 .

[3]  Carl M. Harris,et al.  Fundamentals of queueing theory , 1975 .

[4]  Michael J. Magazine,et al.  A Classified Bibliography of Research on Optimal Design and Control of Queues , 1977, Oper. Res..

[5]  Oded Berman,et al.  The median problem with congestion , 1982, Comput. Oper. Res..

[6]  Ludo Gelders,et al.  A microcomputer-based optimization model for the design of automated warehouses , 1985 .

[7]  Morton E. O'Kelly,et al.  The Location of Interacting Hub Facilities , 1986, Transp. Sci..

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

[9]  Oded Berman,et al.  The Stochastic Queue p-Median Problem , 1987, Transp. Sci..

[10]  Ignacio E. Grossmann,et al.  An outer-approximation algorithm for a class of mixed-integer nonlinear programs , 1987, Math. Program..

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

[12]  Gabriel R. Bitran,et al.  Tradeoff Curves, Targeting and Balancing in Manufacturing Queueing Networks , 1989, Oper. Res..

[13]  Rajan Batta,et al.  Locating Facilities on the Manhattan Metric with Arbitrarily Shaped Barriers and Convex Forbidden Regions , 1989, Transp. Sci..

[14]  Kelvin C. W. So,et al.  The effect of the coefficient of variation of operation times on the allocation of storage space in , 1991 .

[15]  J. George Shanthikumar,et al.  On optimal arrangement of stations in a tandem queueing system with blocking , 1992 .

[16]  Oded Berman,et al.  Optimal Location of Discretionary Service Facilities , 1992, Transp. Sci..

[17]  James F. Campbell,et al.  Integer programming formulations of discrete hub location problems , 1994 .

[18]  T. Aykin Lagrangian relaxation based approaches to capacitated hub-and-spoke network design problem , 1994 .

[19]  Kurt M. Bretthauer Capacity planning in networks of queues with manufacturing applications , 1995 .

[20]  C. Floudas Nonlinear and Mixed-Integer Optimization: Fundamentals and Applications , 1995 .

[21]  Jack Brimberg,et al.  A note on the allocation of queuing facilities using a minisum criterion , 1997 .

[22]  I. Duff,et al.  The state of the art in numerical analysis , 1997 .

[23]  George O. Wesolowsky,et al.  Allocation of queuing facilities using a minimax criterion , 1997 .

[24]  D. McKinney,et al.  Decomposition methods for water resources optimization models with fixed costs , 1998 .

[25]  S. T. Enns Work flow analysis using queuing decomposition models , 1998 .

[26]  Andreas T. Ernst,et al.  The capacitated multiple allocation hub location problem: Formulations and algorithms , 2000, Eur. J. Oper. Res..

[27]  Qian Wang,et al.  Algorithms for a Facility Location Problem with Stochastic Customer Demand and Immobile Servers , 2002, Ann. Oper. Res..

[28]  Shaler Stidham,et al.  Analysis, Design, and Control of Queueing Systems , 2002, Oper. Res..

[29]  Simin Huang,et al.  Variable capacity sizing and selection of connections in a facility layout , 2003 .

[30]  Vladimir Marianov,et al.  Location of Multiple-Server Congestible Facilities for Maximizing Expected Demand, when Services are Non-Essential , 2003, Ann. Oper. Res..

[31]  Marshall L. Fisher,et al.  The Lagrangian Relaxation Method for Solving Integer Programming Problems , 2004, Manag. Sci..