Economics Insights @ CBS

We establish sufficient conditions for the recoverability and uniqueness of utility functions (preferences) generating consumption and asset demands in a two-period setting under uncertainty.

We address the combined problem of allocating a scarce resource among several locations, and planning deliveries using a fleet of vehicles. Demands are random, and holding and shortage costs must be considered in the decision along with transportation costs. We show how to extend some of the available methods for the deterministic vehicle routing problem to this case. Computational results using one such adaptation show that the algorithm is fast enough for practical work, and that substantial cost savings can be achieved with this approach.

We show that any triangulation of the 5-cube I⁵ by complete truncation, i.e., "slicing off" the even (or the odd) vertices, cannot use less than 67 or more than 68 pieces.

Consider a central depot that supplies several locations experiencing random demands. Periodically, the depot may place an order for exogenous supply. Orders arrive after a fixed leadtime, and are then allocated among the several locations. Each allocation reaches its destination after a further delay. We consider the special case where the penalty-cost/holding-cost ratio is constant over the locations. Several approaches are given to approximate the dynamic program describing the problem.

This paper presents an algorithm to compute an optimal (s,S) policy under standard assumptions (stationary data, well-behaved one-period costs, discrete demand, full backlogging, and the average-cost criterion). The method is iterative, starting with an arbitrary, given (s,S) policy and converging to an optimal policy in a finite number of iterations. Any of the available approximations can thus be used as an initial solution. Each iteration requires only modest computations. Also, a lower bound on the true optimal cost can be computed and used in a termination test.