Operations & Supply Chain Management

This paper is concerned with the general dynamic lot size model, or (generalized) Wagner-Whitin model. Let n denote the number of periods into which the planning horizon is divided. We describe a simple forward algorithm which solves the general model in 0(n log n) time and 0(n) space, as opposed to the well-known shortest path algorithm advocated over the last 30 years with 0(n2) time.

This article proposes a model that nests both a strict tree model and the Luce choice model. The multiplicative formulation allows for easy estimation using least-squares procedures. The model is shown to be more parsimonious than the hierarchical elimination method and in a small illustration, to significantly out-perform Luce in predicting soft-drink preferences.

In this paper we consider a class of single-server queueing systems with compound Poisson arrivals, in which, at service completion epochs, the server has the option of taking off for one or several vacations of random length. The cost structure consists of holding cost rate specified by a general non-decreasing function of the queue size, fixed costs for initiating and terminating service, and a variable operating cost incurred for each unit of time that the system is in operation.

A conceptual model is developed that describes the relationships among consumer values, utility, and ownership of durables. These relationships are tested empirically using data on a variety of discretionary durables collected from a sample of 735 adults. Results support the model structure and suggest that augmenting the List of Values (Kahle 1983) with a measure of materialism improves prediction of value-related consumer behavior.

In this paper we propose a model for describing consumer decision making among assortments or menus of options from which a single option will be chosen at a later time. Central to the derivation of the model is an assumption that consumers are uncertain about their future preferences. The model captures both the utility of the items within the assortments as well as the flexibility the items offer as a group. We support our model empirically with two laboratory experiments. In the first experiment we test the underlying assumptions.

In this paper, a new algorithm for computing optimal (s, S) policies is derived based upon a number of new properties of the infinite horizon cost function c(s, S) as well as a new upper bound for optimal order-up-to levels S* and a new lower bound for optimal reorder levels s*. The algorithm is simple and easy to understand. Its computational complexity is only 2.4 times that required to evaluate a (specific) single (s, S) policy. The algorithm applies to both periodic review and continuous review inventory systems.

We analyze a continuous-time, two-stage production/inventory system. In the first stage, a common intermediate product is produced in batches, and possibly stored. In the second phase, the intermediate product is fabricated into n distinct finished products. Several finished products may be included in a single production batch of limited capacity to exploit economies of scale. We propose a planning methodology to address the combined problem of joint setup costs and capacity limits (per setup).