Risk aversion and optimal forest replanting: A stochastic efficiency study

A new stochastic efficiency analysis approach, called stochastic efficiency with respect to a function (SERF), is applied to analyse optimal tree replanting on an area of recently harvested forest land. SERF partitions a set of risky alternative tree replanting strategies in terms of certainty equivalents (CEs) for a specified range of attitudes to risk. Both the entailed risk and the forest owner’s risk aversion are taken into account. The forest owner’s degree of risk aversion affects both the optimal tree replacement strategy and the reinvestment decision. The degree of risk aversion also needs to be taken into account when designing policy measures to affect forest investment.     

Optimal purchasing policy in a two-component assembly system with different purchasing contracts for each component

This paper considers an assembly system where a firm produces a single product which is assembled using two types of components (component 1 and component 2). The components are provided by individual suppliers (supplier 1 and supplier 2). We assume that the firm makes different procurement contracts with supplier 1 and supplier 2. To supplier 1, the firm specifies the maximum inventory level of component 1 and makes a commitment to purchase the component as long as its inventory level is below this target level. To supplier 2, the firm has the option of purchasing or rejecting component 2 at each instant supplier 2 provides it. Formulating our model as a Markov decision problem, we identify a component 2 purchasing policy which maximizes the firm’s profits subject to the costs of rejecting component 1, holding component 2, and purchasing component 2. We also investigate how the changes in the sales price and cost parameters affect the optimal purchasing policy. Finally, we present numerical study for the optimal performance evaluation.This material is based upon work supported by the Korea Science and Engineering Foundation (KOSEF) through the Northeast Asia e-Logistics Research Center at University of Incheon.     

Optimal control of a finite dam with a sample path constraint

In this paper, we discuss the 2-stage output procedure of a finite dam under the condition that water must be released by a fixed time. From this standpoint, the reservoir model we consider is subject to a sample path constraint and has a more general cost function than the earlier contributions. We analytically derive explicit formulas for the long-run average and the expected total discounted costs for an infinite time span and numerically calculate the optimal control policy. Finally, the optimal policy is compared with one by Zuckerman [1] and the effect of the fixed release time is discussed further.     

Some Solved and Unsolved Remainder Equations

The remainder set A?B of a set of sentences A modulo a set of sentences B is the set of all maximal subsets of A not implying any element of B. A remainder equation is an expression containing remainder sets, such as {A} = B?X, in which at least one set is unknown. Solutions to some classes of remainder equations are reported, and some unsolved problems are listed.     

Optimal budgetary and monetary policies under uncertainty: A stochastic control approach

In this paper, we determine optimal budgetary and monetary policies for Austria using a small macroeconometric model. We use a Keynesian model of the Austrian economy, called FINPOL1, estimated by ordinary least squares, which relates the main objective variables of Austrian economic policies, such as the growth rate of real gross domestic product, the rate of unemployment, the rate of inflation, the balance of payments, and the ratio of the federal budget deficit to GDP, to fiscal and monetary policy instruments, namely expenditures and revenues of the federal budget and money supply. Optimal fiscal and monetary policies are calculated for the model under a quadratic objective function using the algorithm OPTCON for the optimum control of nonlinear stochastic dynamic systems. Several control experiments are performed in order to assess the influence of different kinds of uncertainty on optimal budgetary and monetary policies. Apart from deterministic optimization runs, different assumptions about parameter uncertainties are introduced; the results of these different stochastic optimum control experiments are compared and interpreted.     

A non-linear congestion network model for planning internal movement in the Hajj

A non-linear congestion network model is developed for the Hajj case. The Hajj is one of the World's largest mass movements, according to religious rituals. Every year about two and a half million people gather to perform religious rituals. The objective of the model is to minimize traffic congestion and overcrowding of holy sites. The constraints of the model are religious, spatial and time constraints. The model developed and applied for this case assisted in easing overcrowding and planning for expansions in routes and holy sites. The model is effective in providing quantitative background for general policy decision on the Hajj transportation.     

When greediness fails: examples from stochastic scheduling

The purpose of this paper is to present examples for the sometimes surprisingly different behavior of deterministic and stochastic scheduling problems. In particular, it demonstrates some seemingly counterintuitive properties of optimal scheduling policies for stochastic machine scheduling problems.     

On the convexity of the two-threshold policy for an M/G/1 queue with vacations

In this note, we consider a single server queueing system with server vacations of two types and a two-threshold policy. Under a cost and revenue structure the long-run average cost function is proven to be convex in the lower threshold for a fixed difference between the two thresholds.     

Developing a platform for comparison of hospital admission systems: An illustration

There is an increasing need to develop a platform for comparing hospital admission planning systems due to a shift in the service paradigm in the health sector. The current service concept of hospital admission planning aims at optimising the use of scarce hospital resources without paying much attention to the level of service offered to patients. As patients nowadays do not accept long waiting times for hospital admission, it becomes necessary to consider alternative admission service concepts. Waiting lists have also become a political issue, and alternative concepts have been advocated such as giving all patients an appointment for admission. A simulation model was built to examine the impacts of extreme admission service concepts in a simplified hospital setting. The alternative concepts considered are based on the ‘zero waiting time’ principle (immediate treatment), and the ‘booked admissions’ principle (using an appointment for admission). The results of these admission service concepts are compared with the results of the current concept, based on the ‘maximising resource use’ principle. The paper deals with the development of a framework and tool that allows evaluating different, somehow conflicting, hospital admission planning concepts and the usefulness of such framework and tool for more refined/real-life approaches to hospital admission planning.     

Sequential location—allocation of public facilities in one- and two-dimensional space: Comparison of several policies

The present paper examines the sequential location—allocation problems of public facilities in one- and two-dimensional space under several policies. It is shown that the efficiency loss due to the adoption of a myopic policy is not so large, contrary to common belief, provided that the efficiency can be measured by the total transportation cost of users and by the total capacity of facilities. If the total serving area is sufficiently narrow, then the spatial allocations of optimal solutions in two-dimensional problems can be closely approximated by those in one-dimensional problems.