A continuous-review inventory model with constant resupply time and defective items

As a result of imperfect production and inspection by suppliers, pilferage, and/or damage in transit, it is common that procurement orders may contain defective items. This article deals with a continuous-review inventory system with Poisson demand arrivals and constant resupply time. Items in resupply lots may not be of perfect quality. The operating characteristics of such a system are analyzed. For purposes of computational savings, an approximation scheme for the operating characteristics is presented. As a result of the approximation, the determination of the optimal ordering policy becomes much simpler. Extensive numerical tests suggest that the approximation scheme is very effective in giving the optimal or near-optimal ordering policies for such a system.     

Scheduling patients in an ambulatory surgical center

This paper presents a deterministic approach to schedule patients in an ambulatory surgical center (ASC) such that the number of postanesthesia care unit nurses at the center is minimized. We formulate the patient scheduling problem as new variants of the no‐wait, two‐stage process shop scheduling problem and present computational complexity results for the new scheduling models. Also, we develop a tabu search‐based heuristic algorithm to solve the patient scheduling problem. Our algorithm is shown to be very effective in finding near optimal schedules on a set of real data from a university hospital's ASC. © 2003 Wiley Periodicals, Inc. Naval Research Logistics, 2003     

Validation of a strategy for harbor defense based on the use of a min‐max algorithm receding horizon control law

We present a validation of a centralized feedback control law for robotic or partially robotic water craft whose task is to defend a harbor from an intruding fleet of water craft. Our work was motivated by the need to provide harbor defenses against hostile, possibly suicidal intruders, preferably using unmanned craft to limit potential casualties. Our feedback control law is a sample‐data receding horizon control law, which requires the solution of a complex max‐min problem at the start of each sample time. In developing this control law, we had to deal with three challenges. The first was to develop a max‐min problem that captures realistically the nature of the defense‐intrusion game. The second was to ensure the solution of this max‐min problem can be accomplished in a small fraction of the sample time that would be needed to control a possibly fast moving craft. The third, to which this article is dedicated, was to validate the effectiveness of our control law first through computer simulations pitting a computer against a computer or a computer against a human, then through the use of model hovercraft in a laboratory, and finally on the Chesapeake Bay, using Yard Patrol boats. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 247–259, 2016     

Military spending and growth: a small open economy stochastic growth model

The paper analyzes the effects of military spending on economic growth in a small open stochastic endogenous growth model involving the supply-side and demand-side effects produced by military spending. We show that a rise in the military spending affects economic growth through four channels, including the crowding-out effect, the spin-off effect, the resource mobilization effect, and the portfolio effect. The net effect which depends on these four channels is ambiguous. Hence, we demonstrate that there exists an optimal defense burden that maximizes the economic growth rate.     

Operating characteristics of a two-echelon inventory system for repairable and consumable items under batch ordering and shipment policy

In this article we have generalized previous models on multiechelon recoverable inventory systems to cover the cases of batch ordering and shipment policy, and when items can either be repaired or condemned. The batch ordering and shipment policy is appropriate when the setup cost for shipment and order and/or the demand rates of the items are relatively high. The operating characteristics of such a system have been studied. Specifically, the probability distribution of backorder levels at the bases are analyzed for different repair-time distributions. An approximation scheme is proposed for this distribution, and is evaluated using extensive simulation results. The results indicate that the scheme is very effective in providing near-optimal stocking levels in such a system.     

Economic design of a two-stage control chart based on both performance and surrogate variables

The traditional approach to economic design of control charts is based on the assumption that a process is monitored using only a performance variable. If, however, the performance variable is costly to measure and a less expensive surrogate variable is available, the process may be more efficiently controlled by using both performance and surrogate variables. In this article we propose a model for economic design of a two-stage control chart which uses a highly correlated surrogate variable together with a performance variable. The process is assumed to be monitored by the surrogate variable until it signals out-of-control behavior, then by the performance variable until it signals out-of-control behavior or maintains in-control signals for a prespecified amount of time, and the two variables are used in alternating fashion. An algorithm based on the direct search method of Hooke and Jeeves [6] is used to find the optimum values of design parameters. The proposed model is applied to the end-closure welding process for nuclear fuel to compute the amount of reduction in cost compared with the current control procedure. © 1999 John Wiley & Sons, Inc. Naval Research Logistics 46: 958–977, 1999     

Decomposition algorithms for the maximum-weight connected graph problem

Given a positive integer R and a weight for each vertex in a graph, the maximum-weight connected graph problem (MCG) is to find a connected subgraph with R vertices that maximizes the sum of their weights. MCG has applications to communication network design and facility expansion. The constrained MCG (CMCG) is MCG with a constraint that one predetermined vertex must be included in the solution. In this paper, we introduce a class of decomposition algorithms for MCG. These algorithms decompose MCG into a number of small CMCGs by adding vertices one at a time and building a partial graph. They differ in the ordering of adding vertices. Proving that finding an ordering that gives the minimum number of CMCGs is NP-complete, we present three heuristic algorithms. Experimental results show that these heuristics are very effective in reducing computation and that different orderings can significantly affect the number of CMCGs to be solved. © 1998 John Wiley & Sons, Inc. Naval Research Logistics 45: 817–837, 1998     

Algorithms for the constrained maximum-weight connected graph problem

Given a positive integer R and a weight for each vertex in a graph, the maximum-weight connected graph (MCG) problem is to find a connected subgraph with R vertices that maximizes the sum of the weights. The MCG problem is strongly NP-complete, and we study a special case of it: the constrained MCG (CMCG) problem, which is the MCG problem with a constraint of having a predetermined vertex included in the solution. We first show that the Steiner tree problem is a special case of the CMCG problem. Then we present three optimization algorithms for the CMCG problem. The first two algorithms deal with special graphs (tree and layered graphs) and employ different dynamic programming techniques, solving the CMCG problem in polynomial times. The third one deals with a general graph and uses a variant of the Balas additive method with an imbedded connectivity test and a pruning method. We also present a heuristic algorithm for the CMCG problem with a general graph and its bound analysis. We combine the two algorithms, heuristic and optimization, and present a practical solution method to the CMCG problem. Computational results are reported and future research issues are discussed. © 1996 John Wiley & Sons, Inc.     

Tests for transient means in simulated time series

We present a family of tests to detect the presence of a transient mean in a simulation process. These tests compare variance estimators from different parts of a simulation run, and are based on the methods of batch means and standardized time series. Our tests can be viewed as natural generalizations of some previously published work. We also include a power analysis of the new tests, as well as some illustrative examples. © 1994 John Wiley & Sons, Inc.     

Inventory rotation policies for slow moving items

In this article we present a stochastic model for determining inventory rotation policies for a retail firm which must stock many hundreds of distinctive items having uncertain heterogeneous sales patterns. The model develops explicit decision rules for determining (1) the length of time that an item should remain in inventory before the decision is made on whether or not to rotate the item out of inventory and (2) the minimum sales level necessary for retaining the item in inventory. Two inventory rotation policies are developed, the first of which maximizes cumulative expected sales over a finite planning horizon and the second of which maximizes cumulative expected profit. We also consider the statistical behavior of items having uncertain, discrete, and heterogeneous sales patterns using a two-period prediction methodology where period 1 is used to accumulate information on individual sales rates and this knowledge is then used, in a Bayesian context, to make sales predictions for period 2. This methodology assumes that over an arbitrary time interval sales for each item are Poisson with unknown but stationary mean sales rates and the mean sales rates are distributed gamma across all items. We also report the application of the model to a retail firm which stocks many hundreds of distinctive unframed poster art titles. The application provides some useful insights into the behavior of the model as well as some interesting aspects pertaining to the implementation of the results in a “real-world” situation.