A Review of Sensitivity Results for Linear Networks and a New Approximation to Reduce the Effects of Degeneracy

Estimating the reduced cost of an upper bound in a classical linear transshipment network is traditionally accomplished using the shadow price for this constraint, given by the standard calculation c ij = c ij + (pi) j - (pi) i . This reduced cost is only a subgradient due to network degeneracy and often exhibits errors of 50% or more compared to the actual change in the objective function if the upper bound were raised by one unit and the network reoptimized. A new approximation is developed, using a simple modification of the original reduced cost calculation, which is shown to be significantly more accurate. This paper summarizes the basic theory behind network sensitivity, much of which is known as folklore in the networks community, to establish the theoretical properties of the new approximation. The essential idea is to use least-cost flow augmenting paths in the basis to estimate certain directional derivatives which are used in the development of the approximation. The technique is motivated with an application to pricing in truckload trucking.

[1]  William C. Jordan,et al.  A STOCHASTIC, DYNAMIC NETWORK MODEL FOR RAILROAD CAR DISTRIBUTION , 1983 .

[2]  William W. White,et al.  Dynamic transshipment networks: An algorithm and its application to the distribution of empty containers , 1972, Networks.

[3]  A. Barrett Network Flows and Monotropic Optimization. , 1984 .

[4]  Warren B. Powell,et al.  A Stochastic Model of the Dynamic Vehicle Allocation Problem , 1986, Transp. Sci..

[5]  R. V. Helgason,et al.  Algorithms for network programming , 1980 .

[6]  William P. Allman An Optimization Approach to Freight Car Allocation Under Time-Mileage Per Diem Rental Rates , 1972 .

[7]  M. H. Schneider A complementary pivoting algorithm for linear network problems , 1986 .

[8]  Yen-Shwin Shan A dynamic multicommodity network flow model for real time optimal rail freight car management , 1985 .

[9]  Kenneth S. Nickerson,et al.  Maximizing Profits for North American Van Lines' Truckload Division: A New Framework for Pricing and Operations , 1988 .

[10]  William W. White,et al.  A Network Algorithm for Empty Freight Car Allocation , 1969, IBM Syst. J..

[11]  F. Glover,et al.  A computational analysis of alternative algorithms and labeling techniques for finding shortest path trees , 1979, Networks.

[12]  V. Srinivasan,et al.  Determining All Nondegenerate Shadow Prices for the Transportation Problem , 1977 .

[13]  S C Misra LINEAR PROGRAMMING OF EMPTY WAGON DISPOSITION , 1972 .

[14]  S. Sethi,et al.  The Dynamic Transportation Problem: A Survey , 1980 .

[15]  Don T. Phillips,et al.  Fundamentals Of Network Analysis , 1981 .

[16]  Maurice Snowdon,et al.  Network Flow Programming , 1980 .

[17]  Teodor Gabriel Crainic,et al.  Survey Paper - A Review of Empty Flows and Fleet Management Models in Freight Transportation , 1987, Transp. Sci..

[18]  Warren B. Powell,et al.  A COMPARATIVE REVIEW OF ALTERNATIVE ALGORITHMS FOR THE DYNAMIC VEHICLE ALLOCATION PROBLEM , 1988 .

[19]  Warren B. Powell,et al.  THE DYNAMIC VEHICLE ALLOCATION PROBLEM WITH UNCERTAIN DEMANDS , 1987 .