SHADOW WARS

The Secret War with Iran: The 30-Year Clandestine Struggle Against the World's Most Dangerous Terrorist Power, by Ronen Bergman. Free Press, 2008. 432 pages, $28

Fallout: The True Story of the CIA's Secret War on Nuclear Trafficking, by Catherine Collins and Douglas Frantz. Free Press, 2011. 304 pages, $26.

The Twilight War: The Secret History of America's Thirty-Year War with Iran, by David Crist. Penguin Press, 2012. 638 pages, $36.

Israel vs. Iran: The Shadow War, by Yaakov Katz and Yoaz Hendel. Potomac Books Inc., 2012. 254 pages, $30.

Spies Against Armageddon: Inside Israel's Secret Wars, by Dan Raviv. Levant, 2012. 356 pages, $17.

Confront and Conceal: Obama's Secret Wars and Surprising Use of American Power, by David E. Sanger. Crown Publishers, 2012. 476 pages, $28.     

A Doctrine without Dogma

ABSTRACT

In No Use: Nuclear Weapons and U.S. National Security Policy, Thomas M. Nichols calls for a constructive rethinking about the history of nuclear weapons and the attitudes that have grown up around them. Despite dramatic reductions since the end of the Cold War, the United States still maintains a robust nuclear triad that far exceeds the needs of realistic deterrence in the twenty-first century. Nichols advocates a new strategy of minimum deterrence that includes deep unilateral reductions to the US nuclear arsenal, a no-first-use pledge, withdrawing US tactical nuclear weapons from Europe, and ending extended nuclear deterrence for allies. The weakest part of his argument eschews nuclear retaliation against small nuclear states that attack the United States, opting instead to use only conventional weapons to guarantee regime change. He admits this will entail enormous cost and sacrifice, but cites the “immorality” of retaliating against a smaller power with few targets worthy of nuclear weaponry, which totally ignores the massive underground facilities constructed to shield military facilities in many of these states. Despite this, Nichols's thoughtful approach to post-Cold War deterrence deserves thoughtful consideration.     

Dynamic inventory control with limited capital and short‐term financing

For most firms, especially the small‐ and medium‐sized ones, the operational decisions are affected by their internal capital and ability to obtain external capital. However, the majority of the literature on dynamic inventory control ignores the firm's financial status and financing issues. An important question that arises is: what are the optimal inventory and financing policies for firms with limited internal capital and limited access to external capital? In this article, we study a dynamic inventory control problem where a capital‐constrained firm periodically purchases a product from a supplier and sells it to a market with random demands. In each period, the firm can use its own capital and/or borrow a short‐term loan to purchase the product, with the interest rate being nondecreasing in the loan size. The objective is to maximize the firm's expected terminal wealth at the end of the planning horizon. We show that the optimal inventory policy in each period is an equity‐level‐dependent base‐stock policy, where the equity level is the sum of the firm's capital level and the value of its on‐hand inventory evaluated at the purchasing cost; and the structure of the optimal policy can be characterized by four intervals of the equity level. Our results shed light on the dynamic inventory control for firms with limited capital and short‐term financing capabilities.Copyright © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 184–201, 2014     

Exact expected values of variance estimators for simulation

We formulate exact expressions for the expected values of selected estimators of the variance parameter (that is, the sum of covariances at all lags) of a steady‐state simulation output process. Given in terms of the autocovariance function of the process, these expressions are derived for variance estimators based on the simulation analysis methods of nonoverlapping batch means, overlapping batch means, and standardized time series. Comparing estimator performance in a first‐order autoregressive process and the M/M/1 queue‐waiting‐time process, we find that certain standardized time series estimators outperform their competitors as the sample size becomes large. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

Pricing bridges to cross a river

We consider a pricing problem in directed, uncapacitated networks. Tariffs must be defined by an operator, the leader, for a subset of m arcs, the tariff arcs. Costs of all other arcs in the network are assumed to be given. There are n clients, the followers, and after the tariffs have been determined, the clients route their demands independent of each other on paths with minimal total cost. The problem is to find tariffs that maximize the operator's revenue. Motivated by applications in telecommunication networks, we consider a restricted version of this problem, assuming that each client utilizes at most one of the operator's tariff arcs. The problem is equivalent to pricing bridges that clients can use in order to cross a river. We prove that this problem is APX‐hard. Moreover, we analyze the effect of uniform pricing, proving that it yields both an m approximation and a (1 + lnD)‐approximation. Here, D is upper bounded by the total demand of all clients. In addition, we consider the problem under the additional restriction that the operator must not reject any of the clients. We prove that this problem does not admit approximation algorithms with any reasonable performance guarantee, unless P = NP, and we prove the existence of an n‐approximation algorithm. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

A produce‐to‐stock system with advance demand information and secondary customers

We consider a manufacturer (i.e., a capacitated supplier) that produces to stock and has two classes of customers. The primary customer places orders at regular intervals of time for a random quantity, while the secondary customers request a single item at random times. At a predetermined time the manufacturer receives advance demand information regarding the order size of the primary customer. If the manufacturer is not able to fill the primary customer's demand, there is a penalty. On the other hand, serving the secondary customers results in additional profit; however, the manufacturer can refuse to serve the secondary customers in order to reserve inventory for the primary customer. We characterize the manufacturer's optimal production and stock reservation policies that maximize the manufacturer's discounted profit and the average profit per unit time. We show that these policies are threshold‐type policies, and these thresholds are monotone with respect to the primary customer's order size. Using a numerical study we provide insights into how the value of information is affected by the relative demand size of the primary and secondary customers. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007