Hierarchical Approach for Survivable Network Design

A central design challenge facing network planners is how to select a cost-effective network configuration that can provide uninterrupted service despite edge failures. In this paper, we study the Survivable Network Design (SND) problem, a core model underlying the design of such resilient networks that incorporates complex cost and connectivity trade-offs. Given an undirected graph with specified edge costs and (integer) connectivity requirements between pairs of nodes, the SND problem seeks the minimum cost set of edges that interconnects each node pair with at least as many edge-disjoint paths as the connectivity requirement of the nodes. We develop a hierarchical approach for solving the problem that integrates ideas from decomposition, tabu search, randomization, and optimization. The approach decomposes the SND problem into two subproblems, Backbone design and Access design, and uses an iterative multi-stage method for solving the SND problem in a hierarchical fashion. Since both subproblems are NP-hard, we develop effective optimization-based tabu search strategies that balance intensification and diversification to identify near-optimal solutions. To initiate this method, we develop two heuristic procedures that can yield good starting points. We test the combined approach on large-scale SND instances, and empirically assess the quality of the solutions vis-à-vis optimal values or lower bounds. On average, our hierarchical solution approach generates solutions within 2.7% of optimality even for very large problems (that cannot be solved using exact methods), and our results demonstrate that the performance of the method is robust for a variety of problems with different size and connectivity characteristics.

A Decision-Tree-Based Approach to Smoke Spike Detection in a Heavy-Duty Diesel Engine

Smoke spikes occurring during transient engine operation have detrimental health effects and increase fuel consumption by requiring more frequent regeneration of the diesel particulate filter. This paper proposes a decision tree approach to real-time detection of smoke spikes for control and on-board diagnostics purposes. A contemporary, electronically controlled heavy-duty diesel engine was used to investigate the deficiencies of smoke control based on the fuel-to-oxygen-ratio limit. With the aid of transient and steady state data analysis and empirical as well as dimensional modeling, it was shown that the fuel-to-oxygen ratio was not estimated correctly during the turbocharger lag period. This inaccuracy was attributed to the large manifold pressure ratios and low exhaust gas recirculation flows recorded during the turbocharger lag period, which meant that engine control module correlations for the exhaust gas recirculation flow and the volumetric efficiency had to be extrapolated. The engine control module correlations were based on steady state data and it was shown that, unless the turbocharger efficiency is artificially reduced, the large manifold pressure ratios observed during the turbocharger lag period cannot be achieved at steady state. Additionally, the cylinder-to-cylinder variation during this period were shown to be sufficiently significant to make the average fuel-to-oxygen ratio a poor predictor of the transient smoke emissions. The steady state data also showed higher smoke emissions with higher exhaust gas recirculation fractions at constant fuel-to-oxygen-ratio levels. This suggests that, even if the fuel-to-oxygen ratios were to be estimated accurately for each cylinder, they would still be ineffective as smoke limiters. A decision tree trained on snap throttle data and pruned with engineering knowledge was able to use the inaccurate engine control module estimates of the fuel-to-oxygen ratio together with information on the engine control module estimate of the exhaust gas recirculation fraction, the engine speed, and the manifold pressure ratio to predict 94% of all spikes occurring over the Federal Test Procedure cycle. The advantages of this non-parametric approach over other commonly used parametric empirical methods such as regression were described. An application of accurate smoke spike detection in which the injection pressure is increased at points with a high opacity to reduce the cumulative particulate matter emissions substantially with a minimum increase in the cumulative nitrogrn oxide emissions was illustrated with dimensional and empirical modeling.

Human Resource Performance Metrics: Methods & Processes That Demonstrate You Care

Purpose – The purpose of the present analysis is to show that HR systems are not always designed in ways that consider the well-being of employees. In particular, performance metric methods seem to be designed with organizational goals in mind while focusing less on what employees need and desire. Design/methodology/approach – A literature review and multiple case-study method was utilized. Findings – The analysis showed that performance metrics should be revaluated by executives and HR professionals if they seek to develop socially responsible organizational cultures which care about the well-being of employees. Originality/value – The paper exposes the fact that performance appraisal techniques can be rooted in methodologies that ignore or deemphasize the value of employee well-being. The analysis provides a context in which all HR practices can be questioned in relation to meeting the standards of a social justice agenda in the area of corporate social responsibility.

A General Approach Towards the Synthesis of Amido-Functionalized Biodegradable Polyesters

The thesis presented here describes methodologies to produce pendant group functionalized polyesters from amido-functionalized α-hydroxy acids. The synthetic methods used to produce the functionalized α-hydroxy acids are compatible with a wide array of functional groups, making this technique highly versatile. The synthesis of functionalized polyesters was investigated to develop polymers with properties that may improve the capabilities of existing biodegradable polyesters for applications in controlled release pharmaceuticals. Chemically modified a-hydroxy acids were synthesized by reacting glyoxylic acid with a primary or secondary amide. To demonstrate the utility of this reaction, fourstructurally dissimilar amide substituents were examined including 2-pyrrolidione, benzamide, acetamide and acrylamide. The reaction is synthetically simple, provides high yields and is uniquely flexible, functionalized monomer. The compatibility of this procedure with the collection of functional groups mentioned circumvents the need for syntheses. The amido-functionalized monomers were polymerized by two different techniques: melt polycondensation and solution polymerization. Melt polycondensation was conducted by heating the monomer past its melting temperature under reduced pressure. Oligomeric functionalized polyesters (= 800 g/mol) with low PDIs (= 1.05) were obtained by melt polycondensation. Melt polycondensation was not compatible with all of the synthesized monomers. Two of the monomers (containing benzamide and acrylamide functionalities) degraded before the polycondensation reaction occurred. Thermal gravimetric analysis confirmed that a process other than polyesterification was occurring, indicating that some amido-functionalized α-hydroxy acids cannot be synthesized in the melt.Solution polymerization was conducted to polymerize functionalized α-hydroxy acids that were incompatible with melt polycondensation. Several modified Steglich polyesterifications were tested including p-toluenesulfonic acid mediated and scandium (III) triflate catalyzed. Only oligomeric functionalized polyesters were formed bythis method. A number of possible side reactions including the formation of an N-acylurea and a cyclic polymer ring were possible. The utility of this procedure appears to be limited due to the complexity of the reaction and its inability to produce high molecular weight polymer.