Decision Making & Negotiations

Edited by John R. White.

This paper documents the revaluation practice over a ten-year period from 1981 of a large sample of Australian firms and examines the association between these revaluations and stock market prices and returns. The analysis uses several different approaches in order to obtain a thorough understanding of the reevaluation process in Australia. We include a description of hand-collected data from published financial statements, follow-up interviews with chief financial officers of the sample firms, and association tests between hand-collected accounting data and stock market measures.

In this chapter we discuss planning models for multi-echelon systems which allow for uncertain and nonstationary demand and lead time processes. We confine ourselves to so-called PUSH systems with a central decision maker, who possesses continuously or periodically updated information about all inventories of all products at all relevant facilities and production stages; all replenishment decisions in the system are determined centrally on the basis of this information.

We develop a simple O(n log n) solution method for the standard lot-sizing model with backlogging and a study horizon of n periods. Production costs are fixed plus linear and holding and backlogging costs are linear with general time-dependent parameters. The algorithm has linear [O(n)] time complexity for several important subclasses of the general model. We show how a slight adaptation of the algorithm can be used for the detection of a minimal forecast horizon and associated planning horizon.

We consider an inventory system with compound Poisson demands replenished by discrete production of units on a single-server facility. This facility may start a vacation at any production completion epoch; at the completion of a vacation the inventory level is inspected to decide whether or not to resume production. Unit production and vacation times are independent and identically distributed with general distributions.

We consider distribution systems with a single depot and many retailers each of which faces external demands for a single item that occurs at a specific deterministic demand rate. All stock enters the systems through the depot where it can be stored and then picked up and distributed to the retailers by a fleet of vehicles, combining deliveries into efficient routes. We extend earlier methods for obtaining low complexity lower bounds and heuristics for systems without central stock.

Manufacturing and service organizations routinely face the challenge of scheduling jobs, orders, or individual customers in a schedule that optimizes either (i) an aggregate efficiency measure, (ii) a measure of performance balance, or (iii) some combination of these two objectives. We address these questions for single-machine job scheduling systems with fixed or controllable due dates.

This essay reviews the literature on the role of the financial factors in the Depression, and draws some lessons that have more general relevance for the study of the Depression and for macroeconomics. I argue that much of the recent progress that has been made in understanding some of the most important and puzzling aspects of financial-real links in the Depression followed a paradigm shift in economics.

We consider a production/distribution network represented by a general directed acyclic network. Each node is associated with a specific "product" or item at a given location and/or production stage. An arc (i, j) indicates that item i is used to "produce" item j. External demands may occur at any of the network's nodes. These demands occur continuously at item specific constant rates. Components may be assembled in any given proportions.