A continuous-review inventory system with lost sales and variable lead time

Using a system-point (SP) method of level crossings, we derive the stationary distribution of the inventory level (stock on hand) in a continuous-review inventory system with compound Poisson demand, Erlang as well as hyperexponentially distributed lead times, and lost sales. This distribution is then used to formulate long-run average cost functions with/without a service level constraint. Some numerical results are also presented, and compared with the Hadley and Whitin heuristic. © 1998 John Wiley & Sons, Inc. Naval Research Logistics 45: 259–278, 1998     

Note: Optimal allocation of resources to nodes of series systems with respect to failure-rate ordering

Allocation of spare components in a system in order to optimize the lifetime of the system with respect to a suitable criterion is of considerable interest in reliability, engineering, industry, and defense. We consider the problem of allocation of K active spares to a series system of independent and identical components in order to optimize the failure-rate function of the system. © 1997 John Wiley & Sons, Inc.     

Using stochastic programming to solve an outpatient appointment scheduling problem with random service and arrival times

We study a stochastic outpatient appointment scheduling problem (SOASP) in which we need to design a schedule and an adaptive rescheduling (i.e., resequencing or declining) policy for a set of patients. Each patient has a known type and associated probability distributions of random service duration and random arrival time. Finding a provably optimal solution to this problem requires solving a multistage stochastic mixed‐integer program (MSMIP) with a schedule optimization problem solved at each stage, determining the optimal rescheduling policy over the various random service durations and arrival times. In recognition that this MSMIP is intractable, we first consider a two‐stage model (TSM) that relaxes the nonanticipativity constraints of MSMIP and so yields a lower bound. Second, we derive a set of valid inequalities to strengthen and improve the solvability of the TSM formulation. Third, we obtain an upper bound for the MSMIP by solving the TSM under the feasible (and easily implementable) appointment order (AO) policy, which requires that patients are served in the order of their scheduled appointments, independent of their actual arrival times. Fourth, we propose a Monte Carlo approach to evaluate the relative gap between the MSMIP upper and lower bounds. Finally, in a series of numerical experiments, we show that these two bounds are very close in a wide range of SOASP instances, demonstrating the near‐optimality of the AO policy. We also identify parameter settings that result in a large gap in between these two bounds. Accordingly, we propose an alternative policy based on neighbor‐swapping. We demonstrate that this alternative policy leads to a much tighter upper bound and significantly shrinks the gap.     

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.     

Damage modeling of ballistic penetration and impact behavior of concrete panel under low and high velocities

This work presents a numerical simulation of ballistic penetration and high velocity impact behavior of plain and reinforced concrete panels. This paper is divided into two parts. The first part consists of numerical modeling of reinforced concrete panel penetrated with a spherical projectile using concrete damage plasticity (CDP) model, while the second part focuses on the comparison of CDP model and Johnson-Holmquist-2 (JH-2) damage model and their ability to describe the behavior of concrete panel under impact loads. The first and second concrete panels have dimensions of 1500 mm × 1500 mm × 150 mm and 675 mm × 675 mm × 200 mm, respectively, and are meshed using 8-node hexahedron solid elements. The impact object used in the first part is a spherical projectile of 150 mm diameter, while in the second part steel projectile of a length of 152 mm is modeled as rigid element. Failure and scabbing characteristics are studied in the first part. In the second part, the com-parison results are presented as damage contours, kinetic energy of projectile and internal energy of the concrete. The results revealed a severe fracture of the panel and high kinetic energy of the projectile using CDP model comparing to the JH-2 model. In addition, the internal energy of concrete using CDP model was found to be less comparing to the JH-2 model.     

Decision support model for effects estimation and proportionality assessment for targeting in cyber operations

Cyber operations are relatively a new phenomenon of the last two decades.During that period,they have increased in number,complexity,and agility,while their design and development have been processes well kept under secrecy.As a consequence,limited data(sets)regarding these incidents are available.Although various academic and practitioner public communities addressed some of the key points and dilemmas that surround cyber operations(such as attack,target identification and selection,and collateral damage),still methodologies and models are needed in order to plan,execute,and assess them in a responsibly and legally compliant way.Based on these facts,it is the aim of this article to propose a model that i))estimates and classifies the effects of cyber operations,and ii)assesses proportionality in order to support targeting decisions in cyber operations.In order to do that,a multi-layered fuzzy model was designed and implemented by analysing real and virtual realistic cyber operations combined with interviews and focus groups with technical-military experts.The proposed model was evaluated on two cyber operations use cases in a focus group with four technical-military experts.Both the design and the results of the evaluation are revealed in this article.     

WHO IS THE ENEMY?

We examine who benefits when there is a strong leader in place, and who benefits when a situation lacks a proper leader. There are fractious terrorist groups who seek to serve the same people in common cause against a common enemy. The groups compete for rents obtained from the public by engaging in actions against the common enemy. We determine the leadership structure under which each group is better off, as well as the circumstance that the common enemy prefers. We are able to state simple and general conditions for each group and the common enemy to benefit.