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The article presents a paper, which shows how to determine the optimal number and routings of containers used to move mail among several cities. This paper extends the above system to more than two cities, with different schedules on different days and with transfer of containers permitted throughout the system. A mathematical formulation is developed that can be readily solved by known linear programming techniques. Critical assumptions are (a) periodic demand patterns and linear transportation costs between each city-pair, and (b) constant fixed cost per container in the system. The optimization problem is transformed into a network flow linear program for which efficient solution methods are known. The researchers have investigated a system where containerized mail would be sent between two cities. The problem solved in reference was that of determining the best number of containers to be sent each day between the two cities, based on (a) the distribution of mail volumes going between the cities each day and (b) the costs for sending containers, full or empty, and for sending mail by other means in case of container shortage. Thus the original convex programming problem has been converted to an especially tractable type of linear program, namely the optimization of a network flow.

This paper investigates the welfare implication of changes in the transportation system in two special areas. The first is when the origin-destination demand for transportation may be assumed to be fixed and the second case is where, considering only work trips, origins may vary but destinations may not. A technique is described that could be used to forecast the new origin-destination demand resulting from a change in the transportation system. The technique also provides an appropriate measure of the welfare implications. A particular objective of the paper is to point out the pitfalls of using transportation (generalized) cost saving as a welfare measure whenever origin-destination demand may not be assumed fixed. In this situation it is shown that the welfare measure must take into consideration the benefit derived from the increased choice in available housing sites. [ABSTRACT FROM AUTHOR]

This paper provides a simple test for the statistical significance of accident reductions. Such a test is applicable when some change has occurred at a highway location and we wish to know whether or not the difference between the number of accidents 'before' and 'after' represents a statistically significant reduction. In arriving at a decision based on random data we run the risk of occasionally (a) claiming a reduction in accidents when there is none (i.e., type I error), or (b) failing to claim a reduction when it exists (i.e., type II error). A decision procedure is proposed that considers these errors and their costs, and provides curves that indicate trade-offs in the probabilities of making each of the two types of error. Most of the statistical theory used in this paper is generally well known. However, the selection of significance levels based on economic considerations represents an improvement over the all too common practice of arbitrarily selecting significance levels for type I errors and ignoring type II errors altogether. [ABSTRACT FROM AUTHOR]

The paper considers the location of centers (e.g., plants, warehouses) on a network. Necessary conditions and sufficient conditions for optimal solutions to occur at nodes in the network are determined. The conditions include consideration of capacity constraints and the possibility that not all shipments are made via the `shortest route.' The cost functions may differ from arc to arc. A proof is given for the sufficiency of node locations in situations of multistage processing when transport costs are concave over each arc. Three sets of con conations under which it is necessary for an optimal solution to occur at a node are investigated. One set of conditions involves a production function characterization of the centers being located. [ABSTRACT FROM AUTHOR]

A method for estimating costs and benefits to commuters, over a period of time, is developed in this paper. The method will account for the variation of traffic volumes over the period of time considered. The cost structure of a transport mode is taken as a function of the volume of traffic on that mode. The distribution of traffic volumes is then used to measure the costs and benefits to the user and the state over a year. Commuters are divided into different social classes according to the value they place on the attributes of the different transport modes. Next the method is used to evaluate different road pricing schemes. Finally the road system is examined both as a public utility and as a public enterprise. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to estimate cost functions for the U.S. passenger airline industry in order to determine the sources of recent observed productivity, increases. A cost function is derived from the Cobb-Douglas production function, and the parameters of that reduced form equation are estimated. Special attention is given to effect of technology on costs. In general, it was found that there seem to be no scale economies present in the production of available seat miles, but that the level of technology has a substantial impact on cost and productivity. [ABSTRACT FROM AUTHOR]

The problem treated is that of locating in centers (processing facilities) in a network, so as to minimize the total transportation cost associated with their use. On the assumption that all movements occur between a vertex and a center nearest it, HAKIMI has shown that only vertex locations for the centers need be considered. The present paper shows that this conclusion remains valid under alternative assumptions more appropriate for some applications. [ABSTRACT FROM AUTHOR]

Recent developments in aircraft technology will create greater airlift capabilities at lower costs. How will this increased capability be effectively utilized by the Department of Defense? Time-series extrapolations of air-cargo demand have been made in the past for the civil sector of our economy and similar projections have been proposed for military airlift planning. These proved less than successful when compared with actual tonnages generated. This paper will explore a different methodology for predicting airlift demand in the military establishment. Basic data, consisting of approximately 3.8 million commodities and millions of shipments recorded on magnetic automatic data processing tapes, are obtained from all DOD supply management activities. Two information files are established. One is a catalogue file reflecting the physical characteristics (weight, cube, price, etc.) of the commodities that influence total distribution costs of delivering the items to overseas destinations. The second is a demandfile containing the actual volume and traffic flow of the commodities. From these files, total distribution costs for air and surface movement are computed by a mathematical model for each commodity to determine the break-even air rate. The economically air-eligible commodities are then correlated with the volume and traffic flow to determine the elasticity of demand at various air ton-mile rates. Based on known operating costs of new aircraft, logical requirements for airlift can be established. At the same time, criteria for selecting air-eligible commodities are based on economic considerations, thus producing the least-cost method of supplying overseas activities. [ABSTRACT FROM AUTHOR]

In the paper "Sources of Productivity Increases in the U.S. Passenger Airline Industry," a log-linear cross-section function was estimated with several independent variables of the "dummy" or "shift" form. In this type of estimating procedure, the dummy variable is interpreted as a shift in the intercept due to some discrete event that is thought to influence the dependent variable. However, the intercept of the estimated linear transformed equation is a multiplicative factor in the equation before transformation. The nontransformed equation, of course, has no intercept. For this reason, the impact of technical change on cost cannot be determined from the equation directly. Using some values for each of the continuous independent variables, use the equation to calculate cost. In this case the mean values of the logarithm were used. If the value of each of the dummy variables is zero, then this calculated cost is interpreted as the expected annual cost of running a propeller driven plane for the sample geometric seat miles, fuel-cost, etc. Replicate this procedure with the addition of a value of unity for the first dummy variable. This is interpreted as the expected annual cost of running a turboprop plane for the sample geometric mean values of the continuous independent variables.