This article treats the dynamic lot size model with quantity discount in purchase price. We study the problem with two different cost structures: the all-units-discount cost structure and the incremental-discount cost structure. We solve the problem under both discount cost structures by dynamic programming algorithms of complexity O(T3) and O(T2), respectively, with T the number of periods in the planning horizon.
We consider distribution systems with a depot and many geographically dispersed retailers each of which faces external demands occurring at constant, deterministic but retailer specific rates. All stock enters the system through the depot from where it is distributed to the retailers by a fleet of capacitated vehicles combining deliveries into efficient routes. Inventories are kept at the retailers but not at the depot.
PASTA (Poisson Arrivals See Time Averages) is a term coined by R. Wolff in his well known 1982 paper. In keeping with Wolff's terminology, we use the term anti-PASTA to refer to the following converse of PASTA. Given that arrivals do indeed see time averages, when must the arrival process necessarily be Poisson? We show that anti-PASTA is satisfied in a pure-jump Markov process, provided that the arrival process corresponds to a subset of the Markov process jumps.
We examine two measures of monthly manufacturing production. The first is the index of industrial production; the second is constructed from the accounting identity that output equals sales plus the change in inventories. We show that the means, variances, and serial correlation coefficients of the log growth rates differ substantially between the two series, and the cross-correlations are in most cases less than 0.4.
We consider a single-server queueing system with Poisson arrivals and general service times. While the server is up, it is subject to breakdowns according to a Poisson process. When the server breaks down, we may either repair the server immediately or postpone the repair until some future point in time. The operating costs to the system include customer holding costs, repair costs and running costs. The objective is to find a corrective maintenance policy which minimizes the long-run average operating costs of the system. The problem is formulated as a semi-Markov decision process.
This paper describes efforts to validate a multiple car dispatch queueing (MCD) model of police patrol operations using New York City data. The MCD model was designed for use in a computer system that has been disseminated to many police departments in the U.S. to help planners allocate patrol cars among precincts. It has also been used to evalute specific changes in patrol policy in New York. We define validation as a series of hierarchical procedures ranging from tests of mathematical correctness to evaluations of model robustness.
In this paper, we develop the control rules for job shop scheduling based on the Flow Rate Control model. We derive optimal control results for job shops with work station in series (transfer line). We use these results to derive rules which are suboptimal, robust against random events, and easy to implement and expand.
The PDF above is a preprint version of the article. The final version may be found at The Annals of Operations Research.
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.
We provide a deterministic example in which parties sign a contract which they anticipate will be subsequently renegotiated. The renegotiation is socially desirable. In the example, the cost of writing and enforcing contracts increases their complexity.