Scheduling with tool changes to minimize total completion time: A study of heuristics and their performance

The machine scheduling literature does not consider the issue of tool change. The parallel literature on tool management addresses this issue but assumes that the change is due only to part mix. In practice, however, a tool change is caused most frequently by tool wear. That is why we consider here the problem of scheduling a set of jobs on a single CNC machine where the cutting tool is subject to wear; our objective is to minimize the total completion time. We first describe the problem and discuss its peculiarities. After briefly reviewing available theoretical results, we then go on to provide a mixed 0–1 linear programming model for the exact solution of the problem; this is useful in solving problem instances with up to 20 jobs and has been used in our computational study. As our main contribution, we next propose a number of heuristic algorithms based on simple dispatch rules and generic search. We then discuss the results of a computational study where the performance of the various heuristics is tested; we note that the well‐known SPT rule remains good when the tool change time is small but deteriorates as this time increases and further that the proposed algorithms promise significant improvement over the SPT rule. © 2002 Wiley Periodicals, Inc. Naval Research Logistics, 2003     

Health Insurance,Health Conditions,and Veteran Health Care Utilization

Abstract

The utilization of health care services by veterans has received much attention in recent years. However, the impact of the large array of factors affecting the veterans’ demand for health care services remains understudied. These factors include individual socio-demographic and economic characteristics, the availability of various sources of health insurance, and the prevalence of medical conditions. We use public data to analyze how veterans’ utilization of health care services varies with these factors. We also analyze how the reliance on VA services varies when alternative sources of health insurance are available to veterans. Based on the estimated relationships, we use a micro-simulation model to forecast future health care utilization, both inside and outside of VA.     

Light weight HTPB-clay nanocomposites(HCN)with enhanced ablation performance as inhibition materials for composite propellant

In the present study,organically modified Montmorillonite clay with polar moiety,the Cloisite 30B,is used for preparation of Hydroxyl terminated polybutadiene(HTPB)-clay nanocomposites(HCN)by dispersion of nanoclay in polymer matrix under high shear mixing.The nanocomposites thus prepared are evaluated in composite propellants as inhibitor material for their functional utility.Several inhibition formulations containing 5 wt％-15 wt％of nanoclay,with or without the conventional filler Sb2O3,were prepared.All these formulations were evaluated for their physical,mechanical,thermal,and ablative properties.Ablation rate and density of the compositions containing Cloisite 30B is around 23％and 5％lower respectively in comparison of the base composition.Strain capability of these compositions is twofold higher than that of base composition.These compositions have also been evaluated for their smoke generation tendency by measuring infra red(IR)attenuation in the wavelength range 1.3 μm-5.6 μm and 8 μm-13 μm and thereby compared with the base composition.The corresponding results confirmed that the compositions containing Cloisite 30B as filler have much lower IR attenuation than compositions with conventional filler,Sb2O3.Replacement of 5％Sb2O3 by nanoclay showed 8％reduction in IR attenuation rate which further reduced to 16％on replacement of 15％of Sb2O3.Interfacial bonding of HCN based inhibitors is also comparable or even better than conventional inhibitors.Precisely,the nanoclay composites with Cloisite 30B as filler exhibit all desirable properties of an inhibitor.     

Lagrangian solution of maximum dispersion problems

We address the so‐called maximum dispersion problems where the objective is to maximize the sum or the minimum of interelement distances amongst a subset chosen from a given set. The problems arise in a variety of contexts including the location of obnoxious facilities, the selection of diverse groups, and the identification of dense subgraphs. They are known to be computationally difficult. In this paper, we propose a Lagrangian approach toward their solution and report the results of an extensive computational experimentation. Our results show that our Lagrangian approach is reasonably fast, that it yields heuristic solutions which provide good lower bounds on the optimum solution values for both the sum and the minimum problems, and further that it produces decent upper bounds in the case of the sum problem. For the sum problem, the results also show that the Lagrangian heuristic compares favorably against several existing heuristics. © 2000 John Wiley & Sons, Inc. Naval Research Logistics 47: 97–114, 2000