Mechanical properties and thermal conductivity of pristine andfunctionalized carbon nanotube reinforced metallic glass composites:A molecular dynamics approach

This work uses the molecular dynamics approach to study the effects of functionalization of carbon nanotubes (CNTs) on the mechanical properties of Cu64Zr36 metallic glass (MG). Three types of functional groups, carboxylic, vinyl and ester were used. The effect of CNT volume fraction (Vf) and the number of functional groups attached to CNT, on the mechanical properties and thermal conductivity of CNT-MG composites was analysed using Biovia Materials Studio. At lower values of Vf (from 0 to 5％), the per-centage increase in Young's modulus was approximately 66％. As the value of Vf was increased further (from 5 to 12％), the rate of increase in Young's modulus was reduced to 16％. The thermal conductivity was found to increase from 1.52 W/mK at Vf=0％to 5.88 W/mK at Vf=12％, thus giving an increase of approximately 286％. Functionalization of SWCNT reduced the thermal conductivity of the SWCNT-MG composites.     

DIVERGING NUCLEAR PATHWAYS IN SOUTH ASIA

Eating Grass: The Making of the Pakistani Bomb, by Feroz Hassan Khan. Stanford University Press, 2012. 544 pages, $29.95.

Managing India's Nuclear Forces, by Verghese Koithara. Brookings Institution Press, 2012. 304 pages, $59.95.     

India's Pursuit Of Ballistic Missile Defense

This article analyzes India's efforts to deploy a Ballistic Missile Program (BMD). The article has three objectives. First, it argues that scientific-bureaucratic factors and India's incapacity to deter Pakistan's use of terrorist proxies have driven its quest for BMD. Second, the article also evaluates the current state of India's two-tiered missile defense shield. In spite of various claims on the part of India's defense science establishment, the paper estimates that India still lacks a deployable BMD system and is still far from developing an effective strategy of deterrence-through-denial. Third, the article analyzes the implications of the development of India's BMD system for nuclear stability in South Asia. The article shows how India's BMD capacities, however limited, have indirectly exacerbated the security concerns of India's regional rival, Pakistan.     

SPARRING ON THE SUBCONTINENT

South Asian Security and International Nuclear Order: Creating a Robust Indo-Pakistani Nuclear Arms Control Regime, by Mario Esteban Carranza. Ashgate, 2009. 208 pages, $99.95.     

India and Pakistan: Bargaining in the Shadow of Nuclear War

Based on the experience of the Cold War, some scholars hoped that the introduction of nuclear weapons into South Asia would promote peace between India and Pakistan. Instead, nuclear weapons made Pakistan less fearful of India's conventional military forces, and therefore help explain recent conflicts between them. Moreover, US expressions of concern about the possibility of inadvertent nuclear war in South Asia may have provided an incentive to both sides to be intransigent in order to elicit US intervention.     

A refined deterministic linear program for the network revenue management problem with customer choice behavior

We present a new deterministic linear program for the network revenue management problem with customer choice behavior. The novel aspect of our linear program is that it naturally generates bid prices that depend on how much time is left until the time of departure. Similar to the earlier linear program used by van Ryzin and Liu (2004), the optimal objective value of our linear program provides an upper bound on the optimal total expected revenue over the planning horizon. In addition, the percent gap between the optimal objective value of our linear program and the optimal total expected revenue diminishes in an asymptotic regime where the leg capacities and the number of time periods in the planning horizon increase linearly with the same rate. Computational experiments indicate that when compared with the linear program that appears in the existing literature, our linear program can provide tighter upper bounds, and the control policies that are based on our linear program can obtain higher total expected revenues. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008     

A stochastic approximation algorithm to compute bid prices for joint capacity allocation and overbooking over an airline network

In this article, we develop a stochastic approximation algorithm to find good bid price policies for the joint capacity allocation and overbooking problem over an airline network. Our approach is based on visualizing the total expected profit as a function of the bid prices and searching for a good set of bid prices by using the stochastic gradients of the total expected profit function. We show that the total expected profit function that we use is differentiable with respect to the bid prices and derive a simple expression that can be used to compute its stochastic gradients. We show that the iterates of our stochastic approximation algorithm converge to a stationary point of the total expected profit function with probability 1. Our computational experiments indicate that the bid prices computed by our approach perform significantly better than those computed by standard benchmark strategies and the performance of our approach is relatively insensitive to the frequency with which we recompute the bid prices over the planning horizon. © 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011     

Evergreening and operational risk under price competition

“Evergreening” is a strategy wherein an innovative pharmaceutical firm introduces an upgrade of its current product when the patent on this product expires. The upgrade is introduced with a new patent and is designed to counter competition from generic manufacturers that seek to imitate the firm's existing product. However, this process is fraught with uncertainty because the upgrade is subject to stringent guidelines and faces approval risk. Thus, an incumbent firm has to make an upfront production capacity investment without clarity on whether the upgrade will reach the market. This uncertainty may also affect the capacity investment of a competing manufacturer who introduces a generic version of the incumbent's existing product but whose market demand depends on the success or failure of the upgrade. We analyze a game where capacity investment occurs before uncertainty resolution and firms compete on prices thereafter. Capacity considerations that arise due to demand uncertainty introduce new factors into the evergreening decision. Equilibrium analysis reveals that the upgrade's estimated approval probability needs to exceed a threshold for the incumbent to invest in evergreening. This threshold for evergreening increases as the intensity of competition in the generic market increases. If evergreening is optimal, the incumbent's capacity investment is either decreasing or nonmonotonic with respect to low end market competition depending on whether the level of product improvement in the upgrade is low or high. If the entrant faces a capacity constraint, then the probability threshold for evergreening is higher than the case where the entrant is not capacity constrained. Finally, by incorporating the risk‐return trade‐off that the incumbent faces in terms of the level of product improvement versus the upgrade success probability, we can characterize policy for a regulator. We show that the introduction of capacity considerations may maximize market coverage and/or social surplus at incremental levels of product improvement in the upgrade. This is contrary to the prevalent view of regulators who seek to curtail evergreening involving incremental product improvement. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 71–89, 2016     

Approximate dynamic programming methods for an inventory allocation problem under uncertainty

We propose two approximate dynamic programming methods to optimize the distribution operations of a company manufacturing a certain product at multiple production plants and shipping it to different customer locations for sale. We begin by formulating the problem as a dynamic program. Our first approximate dynamic programming method uses a linear approximation of the value function and computes the parameters of this approximation by using the linear programming representation of the dynamic program. Our second method relaxes the constraints that link the decisions for different production plants. Consequently, the dynamic program decomposes by the production plants. Computational experiments show that the proposed methods are computationally attractive, and in particular, the second method performs significantly better than standard benchmarks. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2006