The impotence of conventional arms control: why do international regimes fail when they are most needed?

Amid tensions with the West over Ukraine, Russia pulled out of the Treaty on Conventional Armed Forces in Europe in March 2015. The Russian case is another example of a country disengaging from conventional arms control when relations with other member states deteriorate. This raises an important question: can arms control regimes aimed at preventing conflict survive periods of tension and preserve peace? This article argues no. It demonstrates that the prospect and stability of conventional arms control regimes depend on healthy international relations. In times of tension, governments rely on military institutions for advice and absorb military biases incompatible with arms control. Therefore, these regimes fail when most needed and are impotent as instruments of peace. Beyond conventional arms control, the article hints at the fragility of nuclear agreements such as the 2015 Iran deal and the 2010 New START between the United States and Russia.     

Can Limited Intervention Work? Lessons from Britain’s Success Story in Sierra Leone

ABSTRACT

Following frustrating campaigns in Iraq and Afghanistan, Western interventions are becoming more limited, with troops being deployed for short bursts and residual peace-building tasks being left to others. Although this approach limits exposure for the intervening government, it struggles to achieve meaningful political change. Examining the comparatively successful British intervention in Sierra Leone (2000–02), this article identifies the conditions for effectiveness in these campaigns. It challenges the historiography of the case by framing armed confrontations and raids as enablers of politics rather than ends in themselves; indeed, in both the conduct and study of intervention, politics must reign supreme.     

Transient analysis of multiple-unit reliability systems

A general Markovian model representing several multiple-unit redundant repairable systems is proposed and its transient behavior is studied. Specifically, for multiple-unit reliability system the reliability and availability functions are derived in an explicit form for the transient case. The stationary availability and mean time to system failure are deduced from the main results as special cases.     

Lot sizes under continuous demand: The backorder case

We study a deterministic lot-size problem, in which the demand rate is a (piecewise) continuous function of time and shortages are backordered. The problem is to find the order points and order quantities to minimize the total costs over a finite planning horizon. We show that the optimal order points have an interleaving property, and when the orders are optimally placed, the objective function is convex in the number of orders. By exploiting these properties, an algorithm is developed which solves the problem efficiently. For problems with increasing (decreasing) demand rates and decreasing (increasing) cost rates, monotonicity properties of the optimal order quantities and order intervals are derived.     

Multi-item service constrained (s,S) policies for spare parts logistics systems

Many organizations providing service support for products or families of products must allocate inventory investment among the parts (or, identically, items) that make up those products or families. The allocation decision is crucial in today's competitive environment in which rapid response and low levels of inventory are both required for providing competitive levels of customer service in marketing a firm's products. This is particularly important in high-tech industries, such as computers, military equipment, and consumer appliances. Such rapid response typically implies regional and local distribution points for final products and for spare parts for repairs. In this article we fix attention on a given product or product family at a single location. This single-location problem is the basic building block of multi-echelon inventory systems based on level-by-level decomposition, and our modeling approach is developed with this application in mind. The product consists of field-replaceable units (i.e., parts), which are to be stocked as spares for field service repair. We assume that each part will be stocked at each location according to an (s, S) stocking policy. Moreover, we distinguish two classes of demand at each location: customer (or emergency) demand and normal replenishment demand from lower levels in the multiechelon system. The basic problem of interest is to determine the appropriate policies (s_i S_i) for each part i in the product under consideration. We formulate an approximate cost function and service level constraint, and we present a greedy heuristic algorithm for solving the resulting approximate constrained optimization problem. We present experimental results showing that the heuristics developed have good cost performance relative to optimal. We also discuss extensions to the multiproduct component commonality problem.     

On excess-, current-, and total-life distributions of phase-type renewal processes

Consider a renewal process whose interrenewal-time distribution is phase type with representation (α, T). We show that the (time-dependent) excess-life distribution is phase type with representation (α′, T), where α′ is an appropriately modified initial probability vector. Using this result, we derive the (time-dependent) distributions for the current life and the total life of the phase-type renewal process. They in turn enable us to obtain the equilibrium distributions for the three random variables. These results simplify the computation of the respective distribution functions and consequently enhance the potential use of renewal theory in stochastic modeling—particularly in inventory, queueing, and reliability applications. © 1992 John Wiley & Sons, Inc.     

Some order relations in closed networks of queues with multiserver stations

Consider a closed network of queues of the “product-form” type, where each station has s servers (s ≥ 1 is identical for all stations). We show that the throughput function of the network is Schur concave with respect to the loading of the stations and arrangement increasing with respect to the assignment of server groups. Consequently, different loading/assignment policies can be compared under majorization/arrangement orderings and their relative merits decided according to the yields of throughput. The results can be used to support planning decisions in computer and production systems which are modeled as closed networks of queues.     

Bounds and properties of the expected value of sample information for a project-selection problem

In this article we extend the work of Mehrez and Stulman [5] on the expected value of perfect information (EVPI) to the expected value of sample information (EVSI) for a class of economic problems dealing with the decision to reject or accept an investment project. It is shown that shifting the mean of the underlying a priori distribution of X, the project's monetary value from zero in either direction will decrease the associated EVSI of Y, the random sampled information. A theorem is then presented which gives an upper bound on the EVSI over all distributions of Y, as well as the structure of the posterior mean E[X|Y] for which this upper bound is achieved. Finally, the case where E[X|Y] is linear in Y is discussed and its performance compared with that of the optimal case.     

Optimal maintenance policies for constantly monitored systems

A multistate system is assumed to be constantly monitored; i.e., the state of the system is always known with certainty. Damage to the system accumulates via a continuous-time Markov process. A model of the system including restoration costs and state occupation costs is developed. It is shown that under certain conditions the optimal restoration policy for the system is a control limit rule. A control limit rule is a policy which requires restoration of the system whenever the damage exceeds a certain level. Examples are presented to show that there are several situations in which, perhaps surprisingly, control limit rules are not optimal.     

Linear search with bounded resources

A point is placed at random on the real line according to some known distribution F, and a search is made for this point, beginning at some starting points s on the line, and moving along the line according to some function x(t). The objective of this article is to maximize the probability of finding the point while traveling at most d units. Characterizations of simple optimal searches are found for arbitrary distributions, for continuous distributions with continuous density everywhere (e.g., normal, Cauchy, triangular), and for continuous distributions with density which is continuous on its support (e.g., exponential, uniform). These optimal searches are also shown to be optimal for maximization of the expected number of points found if the points are placed on the line independently from a known distribution F.