A dynamic test platform for evaluating control algorithms for a supercavitating vehicle

The use of supercavitation to enable marine vehicles to travel at extraordinary speeds is a topic of considerable interest. The control of these vehicles poses new challenges not faced with fully wetted vehicles due to a complex interaction between the vehicle and the cavity that it rides in. Some of the existing models make assumptions that may not be valid for a maneuverable vehicle. Furthermore, since there are various models being suggested for planing forces as well as different ways of obtaining fin and cavitator forces, there is a lack of unity among the equations used to calculate the hydrodynamic forces imparted on such a vehicle. Experimental test platforms have been developed at St. Anthony Falls Laboratory to enable testing and validation of control algorithms and hydrodynamic models. Previous efforts have revealed the destabilization of marginal supercavities by control surfaces, especially when a cavity is being maintained with ventilation [1]. Our latest water tunnel test platform is a body of revolution with an actuated cavitator on the model forebody, actuated fins that protrude through the cavity surface, and variable pitch of the model body, all supported by a six-axis force balance. In this paper we will present a brief description of the forces present in our mathematical model of a supercavitating vehicle, and then present the new experimental test platform that will be used to validate, and expand on this model.http://deepblue.lib.umich.edu/bitstream/2027.42/84290/1/CAV2009-final110.pd

Packing While Traveling: Mixed Integer Programming for a Class of Nonlinear Knapsack Problems

Packing and vehicle routing problems play an important role in the area of supply chain management. In this paper, we introduce a non-linear knapsack problem that occurs when packing items along a fixed route and taking into account travel time. We investigate constrained and unconstrained versions of the problem and show that both are NP-hard. In order to solve the problems, we provide a pre-processing scheme as well as exact and approximate mixed integer programming (MIP) solutions. Our experimental results show the effectiveness of the MIP solutions and in particular point out that the approximate MIP approach often leads to near optimal results within far less computation time than the exact approach

Lin-Kernighan Heuristic Adaptations for the Generalized Traveling Salesman Problem

The Lin-Kernighan heuristic is known to be one of the most successful heuristics for the Traveling Salesman Problem (TSP). It has also proven its efficiency in application to some other problems. In this paper we discuss possible adaptations of TSP heuristics for the Generalized Traveling Salesman Problem (GTSP) and focus on the case of the Lin-Kernighan algorithm. At first, we provide an easy-to-understand description of the original Lin-Kernighan heuristic. Then we propose several adaptations, both trivial and complicated. Finally, we conduct a fair competition between all the variations of the Lin-Kernighan adaptation and some other GTSP heuristics. It appears that our adaptation of the Lin-Kernighan algorithm for the GTSP reproduces the success of the original heuristic. Different variations of our adaptation outperform all other heuristics in a wide range of trade-offs between solution quality and running time, making Lin-Kernighan the state-of-the-art GTSP local search.Comment: 25 page

Identification of 2-Aminothiazole-4-Carboxylate Derivatives Active against Mycobacterium tuberculosis H37Rv and the β-Ketoacyl-ACP Synthase mtFabH

Background Tuberculosis (TB) is a disease which kills two million people every year and infects approximately over one-third of the world's population. The difficulty in managing tuberculosis is the prolonged treatment duration, the emergence of drug resistance and co-infection with HIV/AIDS. Tuberculosis control requires new drugs that act at novel drug targets to help combat resistant forms of Mycobacterium tuberculosis and reduce treatment duration. Methodology/Principal Findings Our approach was to modify the naturally occurring and synthetically challenging antibiotic thiolactomycin (TLM) to the more tractable 2-aminothiazole-4-carboxylate scaffold to generate compounds that mimic TLM's novel mode of action. We report here the identification of a series of compounds possessing excellent activity against M. tuberculosis H37Rv and, dissociatively, against the β-ketoacyl synthase enzyme mtFabH which is targeted by TLM. Specifically, methyl 2-amino-5-benzylthiazole-4-carboxylate was found to inhibit M. tuberculosis H37Rv with an MIC of 0.06 µg/ml (240 nM), but showed no activity against mtFabH, whereas methyl 2-(2-bromoacetamido)-5-(3-chlorophenyl)t​hiazole-4-carboxylateinhibited mtFabH with an IC50 of 0.95±0.05 µg/ml (2.43±0.13 µM) but was not active against the whole cell organism. Conclusions/Significance These findings clearly identify the 2-aminothiazole-4-carboxylate scaffold as a promising new template towards the discovery of a new class of anti-tubercular agents

Approximation Algorithms for Covering/Packing Integer Programs

Given matrices A and B and vectors a, b, c and d, all with non-negative entries, we consider the problem of computing min {c.x: x in Z^n_+, Ax > a, Bx < b, x < d}. We give a bicriteria-approximation algorithm that, given epsilon in (0, 1], finds a solution of cost O(ln(m)/epsilon^2) times optimal, meeting the covering constraints (Ax > a) and multiplicity constraints (x < d), and satisfying Bx < (1 + epsilon)b + beta, where beta is the vector of row sums beta_i = sum_j B_ij. Here m denotes the number of rows of A. This gives an O(ln m)-approximation algorithm for CIP -- minimum-cost covering integer programs with multiplicity constraints, i.e., the special case when there are no packing constraints Bx < b. The previous best approximation ratio has been O(ln(max_j sum_i A_ij)) since 1982. CIP contains the set cover problem as a special case, so O(ln m)-approximation is the best possible unless P=NP.Comment: Preliminary version appeared in IEEE Symposium on Foundations of Computer Science (2001). To appear in Journal of Computer and System Science

Computation with Polynomial Equations and Inequalities arising in Combinatorial Optimization

The purpose of this note is to survey a methodology to solve systems of polynomial equations and inequalities. The techniques we discuss use the algebra of multivariate polynomials with coefficients over a field to create large-scale linear algebra or semidefinite programming relaxations of many kinds of feasibility or optimization questions. We are particularly interested in problems arising in combinatorial optimization.Comment: 28 pages, survey pape

Exact Solution Methods for the kk-item Quadratic Knapsack Problem

The purpose of this paper is to solve the 0-1 $k$-item quadratic knapsack problem $(kQKP)$, a problem of maximizing a quadratic function subject to two linear constraints. We propose an exact method based on semidefinite optimization. The semidefinite relaxation used in our approach includes simple rank one constraints, which can be handled efficiently by interior point methods. Furthermore, we strengthen the relaxation by polyhedral constraints and obtain approximate solutions to this semidefinite problem by applying a bundle method. We review other exact solution methods and compare all these approaches by experimenting with instances of various sizes and densities.Comment: 12 page

On the Creation of Acceptable Conjoint Analysis Experimental Designs

Conjoint analysis studies typically utilize orthogonal fractional factorial experimental designs to construct a set of hypothetical stimuli. Occasionally, these designs include environmentally correlated attributes that can lead to stimulus profiles that are not representative of the subject's environment. To date, no one has proposed a remedy well-grounded in statistical theory. This note presents a new methodology utilizing combinatorial optimization procedures for creating modified fractional factorial designs that are as “orthogonal” as possible, which do not contain nonrepresentative stimulus profiles.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/72641/1/j.1540-5915.1991.tb00357.x.pd