An n-step, 2-variable search algorithm for the component placement problem

The component placement problem is a specialization of the quadratic assignment problem that has been extensively studied for a decade and which is of considerable practical value. Recently, interest in component placement algorithms has risen primarily as a result of increased activity in the field of computer-aided design automation. This paper deals with the methodology of component placement and is based on the results of considerable operational experience. A tutorial presentation of tree search placement algorithms is provided, and an improved placement procedure is described which is demonstrated to be effective in generating near optimal solutions to the component placement problem. These solutions are completely reproducible and are obtained at an acceptable expenditure of computational resources. An additional objective is an assessment of performance of the class of near optimal algorithms. In particular, the question- how close to optimal are the near optimal solutions- is examined.     

An economic model for planning strategic mobility posture

This paper describes a linear programming model used to perform cost-effectiveness analysis to determine the requirements for military strategic mobility resources. Expenditures for three classes of economic alternatives are considered: purchase of transportation resources; prepositioning of material; and augmentation of port facilities. The mix of economic alternatives that maximizes the effectiveness of the resultant transportation system is determined for a given investment level. By repeating the analysis for several levels of investment, a cost-effectiveness tradeoff curve can be developed.     

The Hungarian method for the assignment problem

This paper has been presented with the Best Paper Award. It will appear in print in Volume 52, No. 1, February 2005.     

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.     

Experimental investigation for machinability aspects of graphene oxide/carbon fiber reinforced polymer nanocomposites and predictive modeling using hybrid approach

This article explores the drilling behavior of polymer nanocomposites reinforced by Graphene oxide/Carbon fiber using a hybrid method of Grey theory and Principal component analysis (GR-PCA). An online digital dynamometer was employed for the evaluation of Thrust Force and Torque. The image processing technique computes the delamination. Response surface methodology (RSM) considers the parameters, namely, drilling speed (S), feed rate (F), Graphene Oxide wt.% (G) in designing the experimentation array. Principal component analysis (PCA) was used to tackle the response priority weight during the combination of multiple functions. Analysis of variance (ANOVA) scrutinized the influence of parameters and intended the regression models to predict the response. GR-PCA evaluated the optimal parametric setting and remarked that feed rate acts as the most predominant factor. The higher feed rate and wt.% of G is responsible for surface damages like fiber pull-out, fiber fracture and cracks. A significant improvement in drilling responses has been obtained and also validates through confirmatory test and microstructure investigations.     

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.