On the (S − 1, S) lost sales inventory model with priority demand classes

In this paper an inventory model with several demand classes, prioritised according to importance, is analysed. We consider a lot‐for‐lot or (S ? 1, S) inventory model with lost sales. For each demand class there is a critical stock level at and below which demand from that class is not satisfied from stock on hand. In this way stock is retained to meet demand from higher priority demand classes. A set of such critical levels determines the stocking policy. For Poisson demand and a generally distributed lead time, we derive expressions for the service levels for each demand class and the average total cost per unit time. Efficient solution methods for obtaining optimal policies, with and without service level constraints, are presented. Numerical experiments in which the solution methods are tested demonstrate that significant cost reductions can be achieved by distinguishing between demand classes. © 2002 Wiley Periodicals, Inc. Naval Research Logistics 49: 593–610, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/nav.10032     

Technical note: Traffic intensity estimation

This note examines estimation of the traffic intensity in an M/G/1 queue. We show that the ratio of sample mean service times to the sample mean interarrival times has undesirable sampling properties. To remedy this, two alternative estimators are introduced. © 2009 Wiley Periodicals, Inc. Naval Research Logistics 2009     

Lesotho’s 2015 elections in the context of an ongoing security vacuum

After inconclusive elections in 2012, Lesotho had a coalition government for the first time, made up of three political parties that had a narrow majority in parliament. The new government, however, faced several challenges, some of which were of its own making. The agreement among the three parties was to literally divide the government into three parts, leading to a continuous stalemate in its operation; the most serious consequence was the prorogation of parliament and the resultant attempted coup. The flight of the prime minister to South Africa and his return under a Southern African Development Community (SADC) security detail provided a short-term solution to Lesotho's security crisis. Under Cyril Ramaphosa's mediation, the prorogued parliament was conditionally opened and the election date set for 28 February 2015. However, the security dilemma – whereby the prime minister, who is also minister of defence, has no control over the military – remains. When elections are held, there does not seem to be a guarantee that they will be held in peace; moreover, there are now fears that the losers will not accept the results of the elections because of the security vacuum in Lesotho. This article argues that peace can only be salvaged by enhanced SADC security before, during and after the elections. It argues that the SADC mission should remain beyond the elections to oversee the constitutional changes that are necessary for ensuring long-term stability. On their own, Lesotho politicians are unlikely to be able to work together in order to move the country forward.     

Unmasking silence and impunity: the Zimbabwe Peace Project’s e-activism in a polarised political dispensation

This study is an exploration of the use of technology-mediated interventions by the Zimbabwe Peace Project (ZPP) in checkmating the country’s insidious culture of political violence and impunity. It disentangles the ZPP’s strategies and the composite reactions they triggered from state functionaries and the aligned security apparatus. The ZPP exploited and deployed an Internet-circulated monthly newsletter, bulk short message service (SMS) alerts, smartphones, radio and Facebook to shine a spotlight on injustice. It is argued that the ZPP’s whistle-blowing strategies used against human rights violators were not necessarily intended to secure immediate perpetrator conviction; rather, they were a partial but exigent attempt at using perpetrator exposure to reveal extralegal activities and checkmate the country’s culture of impunity. The ZPP’s cybernetic naming and shaming strategies embarrassed some offenders, as evidenced by the intelligence operatives and the police’s constant harassment and arrests of ZPP-affiliated activists. The state-controlled media compounded this pressure by casting aspersions on the ZPP’s bona fides, labelling it a foreign-funded organisation that was attempting to destabilise the country. Finally, this study is informed by a broad evidentiary base that includes ZPP reports on its e-archive, oral interviews, policy documents and newspaper accounts.     

A characterization of optimal base‐stock levels for a multistage serial supply chain

In this article, we present a multistage model to optimize inventory control decisions under stochastic demand and continuous review. We first formulate the general problem for continuous stages and use a decomposition solution approach: since it is never optimal to let orders cross, the general problem can be broken into a set of single‐unit subproblems that can be solved in a sequential fashion. These subproblems are optimal control problems for which a differential equation must be solved. This can be done easily by recursively identifying coefficients and performing a line search. The methodology is then extended to a discrete number of stages and allows us to compute the optimal solution in an efficient manner, with a competitive complexity. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 32–46, 2016     

Optimal timing of switches between product sales for sports and entertainment tickets

Like airlines and hotels, sports teams and entertainment venues can benefit from revenue management efforts for their ticket sales. Teams and entertainment venues usually offer bundles of tickets early in their selling horizon and put single‐event tickets on sale at a later date; these organizations must determine the best time to offer individual tickets because both types of ticket sales consume the same fixed inventory. We model the optimal a priori timing decision for a seller with a fixed number of identical tickets to switch from selling the tickets as fixed bundles to individual tickets to maximize the revenue realized before the start of the performance season. We assume that bundle and single‐ticket customers each arrive according to independent, nonhomogeneous Markovian death processes with a linear death rate that can vary over time and that the benefit from selling a ticket in a package is higher than from selling the ticket individually. We characterize the circumstances in which it is optimal for the seller to practice mixed bundling and when the seller should only sell bundles or individual tickets, and we establish comparative statics for the optimal timing decision for the special case of constant customer arrival rates. We extend our analytical results to find the optimal time for offering two groups of tickets with high and low demand. Finally, we apply the timing model to a data set obtained from the sports industry. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2008     

A hybrid method for simulation factor screening

Factor screening is performed to eliminate unimportant factors so that the remaining important factors can be more thoroughly studied in later experiments. Controlled sequential bifurcation (CSB) and controlled sequential factorial design (CSFD) are two new screening methods for discrete‐event simulations. Both methods use hypothesis testing procedures to control the Type I Error and power of the screening results. The scenarios for which each method is most efficient are complementary. This study proposes a two‐stage hybrid approach that combines CSFD and an improved CSB called CSB‐X. In Phase 1, a prescreening procedure will estimate each effect and determine whether CSB‐X or CSFD will be used for further screening. In Phase 2, CSB‐X and CSFD are performed separately based on the assignment of Phase 1. The new method usually has the same error control as CSB‐X and CSFD. The efficiency, on the other hand, is usually much better than either component method. © 2009 Wiley Periodicals, Inc. Naval Research Logistics, 2010     

A continuous review inventory model with compound poisson demand process and stochastic lead time

Using Markov renewal theory, we derive analytic expressions for the expected average cost associated with (s, S) policies for a continuous review inventory model with a compound Poisson demand process and stochastic lead time, under the (restrictive) assumption that only one order can be outstanding.     

A stochastic constrained optimal replacement model

In this paper a stochastically constrained replacement model is formulated. This model determines a sequence of replacement dates such that the total “current account” cost of all future costs and capital expenditures over an infinite time horizon for the n initial incumbent machines is minimized subject to the constraints that an expected number of machines are in a chosen utility class at any point in time. We then indicate one possible solution method for the model.     

A specially structured nonlinear integer resource allocation problem

We present an algorithm for solving a specially structured nonlinear integer resource allocation problem. This problem was motivated by a capacity planning study done at a large Health Maintenance Organization in Texas. Specifically, we focus on a class of nonlinear resource allocation problems that involve the minimization of a convex function over one general convex constraint, a set of block diagonal convex constraints, and bounds on the integer variables. The continuous variable problem is also considered. The continuous problem is solved by taking advantage of the structure of the Karush‐Kuhn‐Tucker (KKT) conditions. This method for solving the continuous problem is then incorporated in a branch and bound algorithm to solve the integer problem. Various reoptimization results, multiplier bounding results, and heuristics are used to improve the efficiency of the algorithms. We show how the algorithms can be extended to obtain a globally optimal solution to the nonconvex version of the problem. We further show that the methods can be applied to problems in production planning and financial optimization. Extensive computational testing of the algorithms is reported for a variety of applications on continuous problems with up to 1,000,000 variables and integer problems with up to 1000 variables. © 2003 Wiley Periodicals, Inc. Naval Research Logistics 50: 770–792, 2003.