Consumer Behavior

No one has derived closed-form solutions for consumption with stochastic labor income and constant relative risk aversion utility. A numerical technique is used here to give an accurate approximation to the solution. The resulting consumption function is often dramatically different than the certainty equivalence solution typically used, in which consumption is proportional to the sum of financial wealth and the present value of expected future income.

Several recent studies have suggested that empirical rejections of the permanent income/life cycle model might be due to the existence of liquidity constraints. This paper tests the permanent income hypothesis against the alternative hypothesis that consumers optimize subject to a well-specified sequence of borrowing constraints. Implications for consumption in the presence of borrowing constraints are derived and then tested using time-series/cross-section data on families from the Panel Study of Income Dynamics.

This paper considers an M/G/c queueing system serving a finite number (J) of distinct customer classes. Performance of the system, as measured by the vector of steady-state expected waiting times of the customer classes (the performance vector), may be controlled by adopting an appropriate priority discipline.

This paper considers general (single facility) queueing systems with exponential service times, dealing with a finite number J of distinct customer classes. Performance of the system, as measured by the vector of steady state expected sojourn times of the customer classes (the performance vector) may be controlled by adopting an appropriate preemptive priority discipline.

We present an exact solution method for a single-server queueing system which alternates between periods in which service can be provided (on-periods) and periods in which the server is out of operation (off-periods). The arrival process is Poisson, on-periods are assumed to have a phase-type distribution, and service times and off-periods are assumed to be arbitrary.

We consider the polymatroidal flow network model which incorporates two important extensions of the standard maximal flow problem: general concave objective functions of the vector of supplies to a collection of sinks, as well as polymatroidal capacity restrictions on sets of arcs emanating from or pointing to a common node. A number of important applications are reviewed.

We consider general queueing models dealing with multiple classes of customers and address the question under what conditions and in what (stochastic) sense the marginal increase in various performance measures, resulting from the addition of a new class of customers to an existing system, is larger than if the same class were added to a system dealing with only a subset of its current customer base.

Heuristic solution methods for combinatorial optimization problems are often based on local neighborhood searches. These tend to get trapped in a local optimum and the final result is often heavily dependent on the starting solution. Simulated annealing methods attempt to avoid these problems by randomizing the procedure so as to allow for occasional changes that worsen the solution. In this paper we provide probabilistic analyses of different designs of these methods.