Fuzzy Multi-objective Linear Programming Approach

Directory of Open Access Journals (Sweden)

Amna Rehmat

2007-07-01

Full Text Available Traveling salesman problem (TSP is one of the challenging real-life problems, attracting researchers of many fields including Artificial Intelligence, Operations Research, and Algorithm Design and Analysis. The problem has been well studied till now under different headings and has been solved with different approaches including genetic algorithms and linear programming. Conventional linear programming is designed to deal with crisp parameters, but information about real life systems is often available in the form of vague descriptions. Fuzzy methods are designed to handle vague terms, and are most suited to finding optimal solutions to problems with vague parameters. Fuzzy multi-objective linear programming, an amalgamation of fuzzy logic and multi-objective linear programming, deals with flexible aspiration levels or goals and fuzzy constraints with acceptable deviations. In this paper, a methodology, for solving a TSP with imprecise parameters, is deployed using fuzzy multi-objective linear programming. An example of TSP with multiple objectives and vague parameters is discussed.

Investigating Integer Restrictions in Linear Programming

Science.gov (United States)

Edwards, Thomas G.; Chelst, Kenneth R.; Principato, Angela M.; Wilhelm, Thad L.

2015-01-01

Linear programming (LP) is an application of graphing linear systems that appears in many Algebra 2 textbooks. Although not explicitly mentioned in the Common Core State Standards for Mathematics, linear programming blends seamlessly into modeling with mathematics, the fourth Standard for Mathematical Practice (CCSSI 2010, p. 7). In solving a…

The Rendezvous Monitoring Display Capabilities of the Rendezvous and Proximity Operations Program

Science.gov (United States)

Brazzel, Jack; Spehar, Pete; Clark, Fred; Foster, Chris; Eldridge, Erin

2013-01-01

The Rendezvous and Proximity Operations Program (RPOP) is a laptop computer- based relative navigation tool and piloting aid that was developed during the Space Shuttle program. RPOP displays a graphical representation of the relative motion between the target and chaser vehicles in a rendezvous, proximity operations and capture scenario. After being used in over 60 Shuttle rendezvous missions, some of the RPOP display concepts have become recognized as a minimum standard for cockpit displays for monitoring the rendezvous task. To support International Space Station (ISS) based crews in monitoring incoming visiting vehicles, RPOP has been modified to allow crews to compare the Cygnus visiting vehicle s onboard navigated state to processed range measurements from an ISS-based, crew-operated Hand Held Lidar sensor. This paper will discuss the display concepts of RPOP that have proven useful in performing and monitoring rendezvous and proximity operations.

Linear and integer programming made easy

CERN Document Server

Hu, T C

2016-01-01

Linear and integer programming are fundamental toolkits for data and information science and technology, particularly in the context of today’s megatrends toward statistical optimization, machine learning, and big data analytics. Drawn from over 30 years of classroom teaching and applied research experience, this textbook provides a crisp and practical introduction to the basics of linear and integer programming. The authors’ approach is accessible to students from all fields of engineering, including operations research, statistics, machine learning, control system design, scheduling, formal verification, and computer vision. Readers will learn to cast hard combinatorial problems as mathematical programming optimizations, understand how to achieve formulations where the objective and constraints are linear, choose appropriate solution methods, and interpret results appropriately. •Provides a concise introduction to linear and integer programming, appropriate for undergraduates, graduates, a short cours...

PCX, Interior-Point Linear Programming Solver

International Nuclear Information System (INIS)

Czyzyk, J.

2004-01-01

1 - Description of program or function: PCX solves linear programming problems using the Mehrota predictor-corrector interior-point algorithm. PCX can be called as a subroutine or used in stand-alone mode, with data supplied from an MPS file. The software incorporates modules that can be used separately from the linear programming solver, including a pre-solve routine and data structure definitions. 2 - Methods: The Mehrota predictor-corrector method is a primal-dual interior-point method for linear programming. The starting point is determined from a modified least squares heuristic. Linear systems of equations are solved at each interior-point iteration via a sparse Cholesky algorithm native to the code. A pre-solver is incorporated in the code to eliminate inefficiencies in the user's formulation of the problem. 3 - Restriction on the complexity of the problem: There are no size limitations built into the program. The size of problem solved is limited by RAM and swap space on the user's computer

Linear programming using Matlab

CERN Document Server

Ploskas, Nikolaos

2017-01-01

This book offers a theoretical and computational presentation of a variety of linear programming algorithms and methods with an emphasis on the revised simplex method and its components. A theoretical background and mathematical formulation is included for each algorithm as well as comprehensive numerical examples and corresponding MATLAB® code. The MATLAB® implementations presented in this book  are sophisticated and allow users to find solutions to large-scale benchmark linear programs. Each algorithm is followed by a computational study on benchmark problems that analyze the computational behavior of the presented algorithms. As a solid companion to existing algorithmic-specific literature, this book will be useful to researchers, scientists, mathematical programmers, and students with a basic knowledge of linear algebra and calculus.  The clear presentation enables the reader to understand and utilize all components of simplex-type methods, such as presolve techniques, scaling techniques, pivoting ru...

Analysis of the efficiency of the linearization techniques for solving multi-objective linear fractional programming problems by goal programming

Directory of Open Access Journals (Sweden)

Tunjo Perić

2017-01-01

Full Text Available This paper presents and analyzes the applicability of three linearization techniques used for solving multi-objective linear fractional programming problems using the goal programming method. The three linearization techniques are: (1 Taylor’s polynomial linearization approximation, (2 the method of variable change, and (3 a modification of the method of variable change proposed in [20]. All three linearization techniques are presented and analyzed in two variants: (a using the optimal value of the objective functions as the decision makers’ aspirations, and (b the decision makers’ aspirations are given by the decision makers. As the criteria for the analysis we use the efficiency of the obtained solutions and the difficulties the analyst comes upon in preparing the linearization models. To analyze the applicability of the linearization techniques incorporated in the linear goal programming method we use an example of a financial structure optimization problem.

Ranking Forestry Investments With Parametric Linear Programming

Science.gov (United States)

Paul A. Murphy

1976-01-01

Parametric linear programming is introduced as a technique for ranking forestry investments under multiple constraints; it combines the advantages of simple tanking and linear programming as capital budgeting tools.

ALPS - A LINEAR PROGRAM SOLVER

Science.gov (United States)

Viterna, L. A.

1994-01-01

Linear programming is a widely-used engineering and management tool. Scheduling, resource allocation, and production planning are all well-known applications of linear programs (LP's). Most LP's are too large to be solved by hand, so over the decades many computer codes for solving LP's have been developed. ALPS, A Linear Program Solver, is a full-featured LP analysis program. ALPS can solve plain linear programs as well as more complicated mixed integer and pure integer programs. ALPS also contains an efficient solution technique for pure binary (0-1 integer) programs. One of the many weaknesses of LP solvers is the lack of interaction with the user. ALPS is a menu-driven program with no special commands or keywords to learn. In addition, ALPS contains a full-screen editor to enter and maintain the LP formulation. These formulations can be written to and read from plain ASCII files for portability. For those less experienced in LP formulation, ALPS contains a problem "parser" which checks the formulation for errors. ALPS creates fully formatted, readable reports that can be sent to a printer or output file. ALPS is written entirely in IBM's APL2/PC product, Version 1.01. The APL2 workspace containing all the ALPS code can be run on any APL2/PC system (AT or 386). On a 32-bit system, this configuration can take advantage of all extended memory. The user can also examine and modify the ALPS code. The APL2 workspace has also been "packed" to be run on any DOS system (without APL2) as a stand-alone "EXE" file, but has limited memory capacity on a 640K system. A numeric coprocessor (80X87) is optional but recommended. The standard distribution medium for ALPS is a 5.25 inch 360K MS-DOS format diskette. IBM, IBM PC and IBM APL2 are registered trademarks of International Business Machines Corporation. MS-DOS is a registered trademark of Microsoft Corporation.

Linear programming mathematics, theory and algorithms

CERN Document Server

1996-01-01

Linear Programming provides an in-depth look at simplex based as well as the more recent interior point techniques for solving linear programming problems. Starting with a review of the mathematical underpinnings of these approaches, the text provides details of the primal and dual simplex methods with the primal-dual, composite, and steepest edge simplex algorithms. This then is followed by a discussion of interior point techniques, including projective and affine potential reduction, primal and dual affine scaling, and path following algorithms. Also covered is the theory and solution of the linear complementarity problem using both the complementary pivot algorithm and interior point routines. A feature of the book is its early and extensive development and use of duality theory. Audience: The book is written for students in the areas of mathematics, economics, engineering and management science, and professionals who need a sound foundation in the important and dynamic discipline of linear programming.

A New Finite Continuation Algorithm for Linear Programming

DEFF Research Database (Denmark)

Madsen, Kaj; Nielsen, Hans Bruun; Pinar, Mustafa

1996-01-01

We describe a new finite continuation algorithm for linear programming. The dual of the linear programming problem with unit lower and upper bounds is formulated as an $\\ell_1$ minimization problem augmented with the addition of a linear term. This nondifferentiable problem is approximated...... by a smooth problem. It is shown that the minimizers of the smooth problem define a family of piecewise-linear paths as a function of a smoothing parameter. Based on this property, a finite algorithm that traces these paths to arrive at an optimal solution of the linear program is developed. The smooth...

Interior Point Method for Solving Fuzzy Number Linear Programming Problems Using Linear Ranking Function

Directory of Open Access Journals (Sweden)

Yi-hua Zhong

2013-01-01

Full Text Available Recently, various methods have been developed for solving linear programming problems with fuzzy number, such as simplex method and dual simplex method. But their computational complexities are exponential, which is not satisfactory for solving large-scale fuzzy linear programming problems, especially in the engineering field. A new method which can solve large-scale fuzzy number linear programming problems is presented in this paper, which is named a revised interior point method. Its idea is similar to that of interior point method used for solving linear programming problems in crisp environment before, but its feasible direction and step size are chosen by using trapezoidal fuzzy numbers, linear ranking function, fuzzy vector, and their operations, and its end condition is involved in linear ranking function. Their correctness and rationality are proved. Moreover, choice of the initial interior point and some factors influencing the results of this method are also discussed and analyzed. The result of algorithm analysis and example study that shows proper safety factor parameter, accuracy parameter, and initial interior point of this method may reduce iterations and they can be selected easily according to the actual needs. Finally, the method proposed in this paper is an alternative method for solving fuzzy number linear programming problems.

A program package for solving linear optimization problems

International Nuclear Information System (INIS)

Horikami, Kunihiko; Fujimura, Toichiro; Nakahara, Yasuaki

1980-09-01

Seven computer programs for the solution of linear, integer and quadratic programming (four programs for linear programming, one for integer programming and two for quadratic programming) have been prepared and tested on FACOM M200 computer, and auxiliary programs have been written to make it easy to use the optimization program package. The characteristics of each program are explained and the detailed input/output descriptions are given in order to let users know how to use them. (author)

EZLP: An Interactive Computer Program for Solving Linear Programming Problems. Final Report.

Science.gov (United States)

Jarvis, John J.; And Others

Designed for student use in solving linear programming problems, the interactive computer program described (EZLP) permits the student to input the linear programming model in exactly the same manner in which it would be written on paper. This report includes a brief review of the development of EZLP; narrative descriptions of program features,…

Sparsity Prevention Pivoting Method for Linear Programming

DEFF Research Database (Denmark)

Li, Peiqiang; Li, Qiyuan; Li, Canbing

2018-01-01

When the simplex algorithm is used to calculate a linear programming problem, if the matrix is a sparse matrix, it will be possible to lead to many zero-length calculation steps, and even iterative cycle will appear. To deal with the problem, a new pivoting method is proposed in this paper....... The principle of this method is avoided choosing the row which the value of the element in the b vector is zero as the row of the pivot element to make the matrix in linear programming density and ensure that most subsequent steps will improve the value of the objective function. One step following...... this principle is inserted to reselect the pivot element in the existing linear programming algorithm. Both the conditions for inserting this step and the maximum number of allowed insertion steps are determined. In the case study, taking several numbers of linear programming problems as examples, the results...

Sparsity Prevention Pivoting Method for Linear Programming

DEFF Research Database (Denmark)

Li, Peiqiang; Li, Qiyuan; Li, Canbing

2018-01-01

. The principle of this method is avoided choosing the row which the value of the element in the b vector is zero as the row of the pivot element to make the matrix in linear programming density and ensure that most subsequent steps will improve the value of the objective function. One step following......When the simplex algorithm is used to calculate a linear programming problem, if the matrix is a sparse matrix, it will be possible to lead to many zero-length calculation steps, and even iterative cycle will appear. To deal with the problem, a new pivoting method is proposed in this paper...... this principle is inserted to reselect the pivot element in the existing linear programming algorithm. Both the conditions for inserting this step and the maximum number of allowed insertion steps are determined. In the case study, taking several numbers of linear programming problems as examples, the results...

Timetabling an Academic Department with Linear Programming.

Science.gov (United States)

Bezeau, Lawrence M.

This paper describes an approach to faculty timetabling and course scheduling that uses computerized linear programming. After reviewing the literature on linear programming, the paper discusses the process whereby a timetable was created for a department at the University of New Brunswick. Faculty were surveyed with respect to course offerings…

An Approach for Solving Linear Fractional Programming Problems

OpenAIRE

Andrew Oyakhobo Odior

2012-01-01

Linear fractional programming problems are useful tools in production planning, financial and corporate planning, health care and hospital planning and as such have attracted considerable research interest. The paper presents a new approach for solving a fractional linear programming problem in which the objective function is a linear fractional function, while the constraint functions are in the form of linear inequalities. The approach adopted is based mainly upon solving the problem algebr...

An Instructional Note on Linear Programming--A Pedagogically Sound Approach.

Science.gov (United States)

Mitchell, Richard

1998-01-01

Discusses the place of linear programming in college curricula and the advantages of using linear-programming software. Lists important characteristics of computer software used in linear programming for more effective teaching and learning. (ASK)

Portfolio optimization using fuzzy linear programming

Science.gov (United States)

Pandit, Purnima K.

2013-09-01

Portfolio Optimization (PO) is a problem in Finance, in which investor tries to maximize return and minimize risk by carefully choosing different assets. Expected return and risk are the most important parameters with regard to optimal portfolios. In the simple form PO can be modeled as quadratic programming problem which can be put into equivalent linear form. PO problems with the fuzzy parameters can be solved as multi-objective fuzzy linear programming problem. In this paper we give the solution to such problems with an illustrative example.

Joint shape segmentation with linear programming

KAUST Repository

Huang, Qixing; Koltun, Vladlen; Guibas, Leonidas

2011-01-01

program is solved via a linear programming relaxation, using a block coordinate descent procedure that makes the optimization feasible for large databases. We evaluate the presented approach on the Princeton segmentation benchmark and show that joint shape

A Primal-Dual Interior Point-Linear Programming Algorithm for MPC

DEFF Research Database (Denmark)

Edlund, Kristian; Sokoler, Leo Emil; Jørgensen, John Bagterp

2009-01-01

Constrained optimal control problems for linear systems with linear constraints and an objective function consisting of linear and l1-norm terms can be expressed as linear programs. We develop an efficient primal-dual interior point algorithm for solution of such linear programs. The algorithm...

Proximal Alternating Direction Method with Relaxed Proximal Parameters for the Least Squares Covariance Adjustment Problem

Directory of Open Access Journals (Sweden)

Minghua Xu

2014-01-01

Full Text Available We consider the problem of seeking a symmetric positive semidefinite matrix in a closed convex set to approximate a given matrix. This problem may arise in several areas of numerical linear algebra or come from finance industry or statistics and thus has many applications. For solving this class of matrix optimization problems, many methods have been proposed in the literature. The proximal alternating direction method is one of those methods which can be easily applied to solve these matrix optimization problems. Generally, the proximal parameters of the proximal alternating direction method are greater than zero. In this paper, we conclude that the restriction on the proximal parameters can be relaxed for solving this kind of matrix optimization problems. Numerical experiments also show that the proximal alternating direction method with the relaxed proximal parameters is convergent and generally has a better performance than the classical proximal alternating direction method.

A Fuzzy Linear Programming Approach for Aggregate Production Planning

DEFF Research Database (Denmark)

Iris, Cagatay; Cevikcan, Emre

2014-01-01

a mathematical programming framework for aggregate production planning problem under imprecise data environment. After providing background information about APP problem, together with fuzzy linear programming, the fuzzy linear programming model of APP is solved on an illustrative example for different a...

Linear Parametric Sensitivity Analysis of the Constraint Coefficient Matrix in Linear Programs

OpenAIRE

Zuidwijk, Rob

2005-01-01

textabstractSensitivity analysis is used to quantify the impact of changes in the initial data of linear programs on the optimal value. In particular, parametric sensitivity analysis involves a perturbation analysis in which the effects of small changes of some or all of the initial data on an optimal solution are investigated, and the optimal solution is studied on a so-called critical range of the initial data, in which certain properties such as the optimal basis in linear programming are ...

A goal programming procedure for solving fuzzy multiobjective fractional linear programming problems

Directory of Open Access Journals (Sweden)

Tunjo Perić

2014-12-01

Full Text Available This paper presents a modification of Pal, Moitra and Maulik's goal programming procedure for fuzzy multiobjective linear fractional programming problem solving. The proposed modification of the method allows simpler solving of economic multiple objective fractional linear programming (MOFLP problems, enabling the obtained solutions to express the preferences of the decision maker defined by the objective function weights. The proposed method is tested on the production planning example.

Game Theory and its Relationship with Linear Programming Models ...

African Journals Online (AJOL)

Game Theory and its Relationship with Linear Programming Models. ... This paper shows that game theory and linear programming problem are closely related subjects since any computing method devised for ... AJOL African Journals Online.

Linearized Programming of Memristors for Artificial Neuro-Sensor Signal Processing.

Science.gov (United States)

Yang, Changju; Kim, Hyongsuk

2016-08-19

A linearized programming method of memristor-based neural weights is proposed. Memristor is known as an ideal element to implement a neural synapse due to its embedded functions of analog memory and analog multiplication. Its resistance variation with a voltage input is generally a nonlinear function of time. Linearization of memristance variation about time is very important for the easiness of memristor programming. In this paper, a method utilizing an anti-serial architecture for linear programming is proposed. The anti-serial architecture is composed of two memristors with opposite polarities. It linearizes the variation of memristance due to complimentary actions of two memristors. For programming a memristor, additional memristor with opposite polarity is employed. The linearization effect of weight programming of an anti-serial architecture is investigated and memristor bridge synapse which is built with two sets of anti-serial memristor architecture is taken as an application example of the proposed method. Simulations are performed with memristors of both linear drift model and nonlinear model.

Evaluation of film dosemeters by linear programming

International Nuclear Information System (INIS)

Kragh, P.; Nitschke, J.

1992-01-01

An evaluation method for multi-component dosemeters is described which uses linear programming in order to decrease the dependence on energy and direction. The results of this method are more accurate than those obtained with the evaluation methods so far applied in film dosimetry. In addition, systematic errors can be given when evaluating individual measurements. Combined linear programming, as a special case of the presented method, is described taking a film dosemeter of particular type as an example. (orig.) [de

Measuring implementation of a school-based violence prevention program : Fidelity and teachers' responsiveness as predictors of proximal outcomes

NARCIS (Netherlands)

Schultes, Marie Therese; Stefanek, Elisabeth; van de Schoot, Rens; Strohmeier, Dagmar; Spiel, Christiane

2014-01-01

When school-based prevention programs are put into practice, evaluation studies commonly only consider one indicator of program implementation. The present study investigates how two different aspects of program implementation - fidelity and participant responsiveness - jointly influence proximal

Optimization Research of Generation Investment Based on Linear Programming Model

Science.gov (United States)

Wu, Juan; Ge, Xueqian

Linear programming is an important branch of operational research and it is a mathematical method to assist the people to carry out scientific management. GAMS is an advanced simulation and optimization modeling language and it will combine a large number of complex mathematical programming, such as linear programming LP, nonlinear programming NLP, MIP and other mixed-integer programming with the system simulation. In this paper, based on the linear programming model, the optimized investment decision-making of generation is simulated and analyzed. At last, the optimal installed capacity of power plants and the final total cost are got, which provides the rational decision-making basis for optimized investments.

175 Years of Linear Programming

Indian Academy of Sciences (India)

polynomial-time solvability of linear programming, that is, testing if a polyhedron Q E ~ ... Q is rational, i.e. all extreme points and rays of Q are ra- tional vectors or ..... rithrll terminates with an interior solution, a post-processing step is usually ...

Linear System of Equations, Matrix Inversion, and Linear Programming Using MS Excel

Science.gov (United States)

El-Gebeily, M.; Yushau, B.

2008-01-01

In this note, we demonstrate with illustrations two different ways that MS Excel can be used to solve Linear Systems of Equation, Linear Programming Problems, and Matrix Inversion Problems. The advantage of using MS Excel is its availability and transparency (the user is responsible for most of the details of how a problem is solved). Further, we…

A Sawmill Manager Adapts To Change With Linear Programming

Science.gov (United States)

George F. Dutrow; James E. Granskog

1973-01-01

Linear programming provides guidelines for increasing sawmill capacity and flexibility and for determining stumpagepurchasing strategy. The operator of a medium-sized sawmill implemented improvements suggested by linear programming analysis; results indicate a 45 percent increase in revenue and a 36 percent hike in volume processed.

175 Years of Linear Programming

Indian Academy of Sciences (India)

Home; Journals; Resonance – Journal of Science Education; Volume 4; Issue 10. 175 Years of Linear Programming - Max Flow = Min Cut. Vijay Chandru M R Rao. Series Article Volume 4 Issue 10 October 1999 pp 22-39. Fulltext. Click here to view fulltext PDF. Permanent link:

175 Years of Linear Programming

Indian Academy of Sciences (India)

Home; Journals; Resonance – Journal of Science Education; Volume 4; Issue 5. 175 Years of Linear Programming - Pune's Gift. Vijay Chandru M R Rao. Series Article Volume 4 Issue 5 May ... Computer Science and Automation, IISc Bangalore 560012, India. Director, Indian Institute of Management, Bannerghatta Road, ...

A proximal point algorithm with generalized proximal distances to BEPs

OpenAIRE

Bento, G. C.; Neto, J. X. Cruz; Lopes, J. O.; Soares Jr, P. A.; Soubeyran, A.

2014-01-01

We consider a bilevel problem involving two monotone equilibrium bifunctions and we show that this problem can be solved by a proximal point method with generalized proximal distances. We propose a framework for the convergence analysis of the sequences generated by the algorithm. This class of problems is very interesting because it covers mathematical programs and optimization problems under equilibrium constraints. As an application, we consider the problem of the stability and change dyna...

An approach for solving linear fractional programming problems ...

African Journals Online (AJOL)

The paper presents a new approach for solving a fractional linear programming problem in which the objective function is a linear fractional function, while the constraint functions are in the form of linear inequalities. The approach adopted is based mainly upon solving the problem algebraically using the concept of duality ...

Non-linear programming method in optimization of fast reactors

International Nuclear Information System (INIS)

Pavelesku, M.; Dumitresku, Kh.; Adam, S.

1975-01-01

Application of the non-linear programming methods on optimization of nuclear materials distribution in fast reactor is discussed. The programming task composition is made on the basis of the reactor calculation dependent on the fuel distribution strategy. As an illustration of this method application the solution of simple example is given. Solution of the non-linear program is done on the basis of the numerical method SUMT. (I.T.)

Analytic central path, sensitivity analysis and parametric linear programming

NARCIS (Netherlands)

A.G. Holder; J.F. Sturm; S. Zhang (Shuzhong)

1998-01-01

textabstractIn this paper we consider properties of the central path and the analytic center of the optimal face in the context of parametric linear programming. We first show that if the right-hand side vector of a standard linear program is perturbed, then the analytic center of the optimal face

Linear program differentiation for single-channel speech separation

DEFF Research Database (Denmark)

Pearlmutter, Barak A.; Olsson, Rasmus Kongsgaard

2006-01-01

Many apparently difficult problems can be solved by reduction to linear programming. Such problems are often subproblems within larger systems. When gradient optimisation of the entire larger system is desired, it is necessary to propagate gradients through the internally-invoked LP solver....... For instance, when an intermediate quantity z is the solution to a linear program involving constraint matrix A, a vector of sensitivities dE/dz will induce sensitivities dE/dA. Here we show how these can be efficiently calculated, when they exist. This allows algorithmic differentiation to be applied...... to algorithms that invoke linear programming solvers as subroutines, as is common when using sparse representations in signal processing. Here we apply it to gradient optimisation of over complete dictionaries for maximally sparse representations of a speech corpus. The dictionaries are employed in a single...

Linear combination of forecasts with numerical adjustment via MINIMAX non-linear programming

Directory of Open Access Journals (Sweden)

Jairo Marlon Corrêa

2016-03-01

Full Text Available This paper proposes a linear combination of forecasts obtained from three forecasting methods (namely, ARIMA, Exponential Smoothing and Artificial Neural Networks whose adaptive weights are determined via a multi-objective non-linear programming problem, which seeks to minimize, simultaneously, the statistics: MAE, MAPE and MSE. The results achieved by the proposed combination are compared with the traditional approach of linear combinations of forecasts, where the optimum adaptive weights are determined only by minimizing the MSE; with the combination method by arithmetic mean; and with individual methods

Very Low-Cost Nutritious Diet Plans Designed by Linear Programming.

Science.gov (United States)

Foytik, Jerry

1981-01-01

Provides procedural details of Linear Programing, developed by the U.S. Department of Agriculture to devise a dietary guide for consumers that minimizes food costs without sacrificing nutritional quality. Compares Linear Programming with the Thrifty Food Plan, which has been a basis for allocating coupons under the Food Stamp Program. (CS)

Portfolio optimization by using linear programing models based on genetic algorithm

Science.gov (United States)

Sukono; Hidayat, Y.; Lesmana, E.; Putra, A. S.; Napitupulu, H.; Supian, S.

2018-01-01

In this paper, we discussed the investment portfolio optimization using linear programming model based on genetic algorithms. It is assumed that the portfolio risk is measured by absolute standard deviation, and each investor has a risk tolerance on the investment portfolio. To complete the investment portfolio optimization problem, the issue is arranged into a linear programming model. Furthermore, determination of the optimum solution for linear programming is done by using a genetic algorithm. As a numerical illustration, we analyze some of the stocks traded on the capital market in Indonesia. Based on the analysis, it is shown that the portfolio optimization performed by genetic algorithm approach produces more optimal efficient portfolio, compared to the portfolio optimization performed by a linear programming algorithm approach. Therefore, genetic algorithms can be considered as an alternative on determining the investment portfolio optimization, particularly using linear programming models.

An easy way to obtain strong duality results in linear, linear semidefinite and linear semi-infinite programming

NARCIS (Netherlands)

Pop, P.C.; Still, Georg J.

1999-01-01

In linear programming it is known that an appropriate non-homogeneous Farkas Lemma leads to a short proof of the strong duality results for a pair of primal and dual programs. By using a corresponding generalized Farkas lemma we give a similar proof of the strong duality results for semidefinite

The simplex method of linear programming

CERN Document Server

Ficken, Frederick A

1961-01-01

This concise but detailed and thorough treatment discusses the rudiments of the well-known simplex method for solving optimization problems in linear programming. Geared toward undergraduate students, the approach offers sufficient material for readers without a strong background in linear algebra. Many different kinds of problems further enrich the presentation. The text begins with examinations of the allocation problem, matrix notation for dual problems, feasibility, and theorems on duality and existence. Subsequent chapters address convex sets and boundedness, the prepared problem and boun

Some Properties of Multiple Parameters Linear Programming

Directory of Open Access Journals (Sweden)

Maoqin Li

2010-01-01

Full Text Available We consider a linear programming problem in which the right-hand side vector depends on multiple parameters. We study the characters of the optimal value function and the critical regions based on the concept of the optimal partition. We show that the domain of the optimal value function f can be decomposed into finitely many subsets with disjoint relative interiors, which is different from the result based on the concept of the optimal basis. And any directional derivative of f at any point can be computed by solving a linear programming problem when only an optimal solution is available at the point.

Some Properties of Multiple Parameters Linear Programming

Directory of Open Access Journals (Sweden)

Yan Hong

2010-01-01

Full Text Available Abstract We consider a linear programming problem in which the right-hand side vector depends on multiple parameters. We study the characters of the optimal value function and the critical regions based on the concept of the optimal partition. We show that the domain of the optimal value function can be decomposed into finitely many subsets with disjoint relative interiors, which is different from the result based on the concept of the optimal basis. And any directional derivative of at any point can be computed by solving a linear programming problem when only an optimal solution is available at the point.

A LINEAR PROGRAMMING ALGORITHM FOR LEAST-COST SCHEDULING

Directory of Open Access Journals (Sweden)

AYMAN H AL-MOMANI

1999-12-01

Full Text Available In this research, some concepts of linear programming and critical path method are reviewed to describe recent modeling structures that have been of great value in analyzing extended planning horizon project time-cost trade-offs problems. A simplified representation of a small project and a linear programming model is formulated to represent this system. Procedures to solve these various problems formulations were cited and the final solution is obtained using LINDO program. The model developed represents many restrictions and management considerations of the project. It could be used by construction managers in a planning stage to explore numerous possible opportunities to the contractor and predict the effect of a decision on the construction to facilitate a preferred operating policy given different management objectives. An implementation using this method is shown to outperform several other techniques and a large class of test problems. Linear programming show that the algorithm is very promising in practice on a wide variety of time-cost trade-offs problems. This method is simple, applicable to a large network, and generates a shorter computational time at low cost, along with an increase in robustness.

Applied Research of Enterprise Cost Control Based on Linear Programming

Directory of Open Access Journals (Sweden)

Yu Shuo

2015-01-01

This paper researches the enterprise cost control through the linear programming model, and analyzes the restriction factors of the labor of enterprise production, raw materials, processing equipment, sales price, and other factors affecting the enterprise income, so as to obtain an enterprise cost control model based on the linear programming. This model can calculate rational production mode in the case of limited resources, and acquire optimal enterprise income. The production guiding program and scheduling arrangement of the enterprise can be obtained through calculation results, so as to provide scientific and effective guidance for the enterprise production. This paper adds the sensitivity analysis in the linear programming model, so as to learn about the stability of the enterprise cost control model based on linear programming through the sensitivity analysis, and verify the rationality of the model, and indicate the direction for the enterprise cost control. The calculation results of the model can provide a certain reference for the enterprise planning in the market economy environment, which have strong reference and practical significance in terms of the enterprise cost control.

Linear trend and climate response of five-needle pines in the western United States related to treeline proximity

Energy Technology Data Exchange (ETDEWEB)

Kipfmueller, K.F. [Minnesota Univ., Minneapolis, MN (United States). Dept. of Geography; Salzer, M.W. [Arizona Univ., Tucson, AZ (United States). Laboratory of Tree-Ring Research

2010-01-15

This study investigated sixty-six 5-needle pine growth chronologies from 1896 to their end years in order to identify potential patterns related to linear trends in ring width. Individual chronology responses to climate were also evaluated by comparing the chronologies with seasonal temperature and precipitation data from 1896 to the present date. Chronologies exhibiting similar patterns of climate response were grouped in order to examine the role of treeline proximity on climate-growth relationships. Ring width measurements for pine sites located in the western United States were obtained from the International Tree Ring Data Bank. Growth indices were compared among all sites in order to assess the relative strength of common signals with increasing distance. Pearson correlations were used to calculate linear trends for each chronology. A cluster analysis of climate response patterns indicated that most chronologies positively associated with temperatures were located near upper treeline and contained significant positive linear trends. The study suggested that 5-needle pine treeline chronologies may be used as predictors in temperature reconstructions. However, care must be taken to determine that collection sites have not been impacted by disturbances such as fire or insect outbreaks. 35 refs., 2 tabs., 5 figs.

Joint shape segmentation with linear programming

KAUST Repository

Huang, Qixing

2011-01-01

We present an approach to segmenting shapes in a heterogenous shape database. Our approach segments the shapes jointly, utilizing features from multiple shapes to improve the segmentation of each. The approach is entirely unsupervised and is based on an integer quadratic programming formulation of the joint segmentation problem. The program optimizes over possible segmentations of individual shapes as well as over possible correspondences between segments from multiple shapes. The integer quadratic program is solved via a linear programming relaxation, using a block coordinate descent procedure that makes the optimization feasible for large databases. We evaluate the presented approach on the Princeton segmentation benchmark and show that joint shape segmentation significantly outperforms single-shape segmentation techniques. © 2011 ACM.

Arc-Search Infeasible Interior-Point Algorithm for Linear Programming

OpenAIRE

Yang, Yaguang

2014-01-01

Mehrotra's algorithm has been the most successful infeasible interior-point algorithm for linear programming since 1990. Most popular interior-point software packages for linear programming are based on Mehrotra's algorithm. This paper proposes an alternative algorithm, arc-search infeasible interior-point algorithm. We will demonstrate, by testing Netlib problems and comparing the test results obtained by arc-search infeasible interior-point algorithm and Mehrotra's algorithm, that the propo...

Linear Programming and Its Application to Pattern Recognition Problems

Science.gov (United States)

Omalley, M. J.

1973-01-01

Linear programming and linear programming like techniques as applied to pattern recognition problems are discussed. Three relatively recent research articles on such applications are summarized. The main results of each paper are described, indicating the theoretical tools needed to obtain them. A synopsis of the author's comments is presented with regard to the applicability or non-applicability of his methods to particular problems, including computational results wherever given.

Object matching using a locally affine invariant and linear programming techniques.

Science.gov (United States)

Li, Hongsheng; Huang, Xiaolei; He, Lei

2013-02-01

In this paper, we introduce a new matching method based on a novel locally affine-invariant geometric constraint and linear programming techniques. To model and solve the matching problem in a linear programming formulation, all geometric constraints should be able to be exactly or approximately reformulated into a linear form. This is a major difficulty for this kind of matching algorithm. We propose a novel locally affine-invariant constraint which can be exactly linearized and requires a lot fewer auxiliary variables than other linear programming-based methods do. The key idea behind it is that each point in the template point set can be exactly represented by an affine combination of its neighboring points, whose weights can be solved easily by least squares. Errors of reconstructing each matched point using such weights are used to penalize the disagreement of geometric relationships between the template points and the matched points. The resulting overall objective function can be solved efficiently by linear programming techniques. Our experimental results on both rigid and nonrigid object matching show the effectiveness of the proposed algorithm.

Automated Mounting of Pole-Shoe Wedges in Linear Wave Power Generators—Using Industrial Robotics and Proximity Sensors

Directory of Open Access Journals (Sweden)

Tobias Kamf

2017-03-01

Full Text Available A system for automatic mounting of high tolerance wedges inside a wave power linear generator is proposed. As for any renewable energy concept utilising numerous smaller generation units, minimising the production cost per unit is vital for commercialization. The linear generator in question uses self-locking wedges, which are challenging to mount using industrial robots due to the high tolerances used, and because of the fact that any angular error remaining after calibration risks damaging the equipment. Using two types of probes, mechanical touch probes and inductive proximity sensors, combined with a flexible robot tool and iterative calibration routines, an automatic mounting system that overcomes the challenges of high tolerance wedge mounting is presented. The system is experimentally verified to work at mounting speeds of up to 50mm/s, and calibration accuracies of 0.25mmand 0.1 ∘ are achieved. The use of a flexible robot tool, able to move freely in one Cartesian plane, was found to be essential for making the system work.

Application of the simplex method of linear programming model to ...

African Journals Online (AJOL)

This work discussed how the simplex method of linear programming could be used to maximize the profit of any business firm using Saclux Paint Company as a case study. It equally elucidated the effect variation in the optimal result obtained from linear programming model, will have on any given firm. It was demonstrated ...

An introduction to fuzzy linear programming problems theory, methods and applications

CERN Document Server

Kaur, Jagdeep

2016-01-01

The book presents a snapshot of the state of the art in the field of fully fuzzy linear programming. The main focus is on showing current methods for finding the fuzzy optimal solution of fully fuzzy linear programming problems in which all the parameters and decision variables are represented by non-negative fuzzy numbers. It presents new methods developed by the authors, as well as existing methods developed by others, and their application to real-world problems, including fuzzy transportation problems. Moreover, it compares the outcomes of the different methods and discusses their advantages/disadvantages. As the first work to collect at one place the most important methods for solving fuzzy linear programming problems, the book represents a useful reference guide for students and researchers, providing them with the necessary theoretical and practical knowledge to deal with linear programming problems under uncertainty.

An efficient method for generalized linear multiplicative programming problem with multiplicative constraints.

Science.gov (United States)

Zhao, Yingfeng; Liu, Sanyang

2016-01-01

We present a practical branch and bound algorithm for globally solving generalized linear multiplicative programming problem with multiplicative constraints. To solve the problem, a relaxation programming problem which is equivalent to a linear programming is proposed by utilizing a new two-phase relaxation technique. In the algorithm, lower and upper bounds are simultaneously obtained by solving some linear relaxation programming problems. Global convergence has been proved and results of some sample examples and a small random experiment show that the proposed algorithm is feasible and efficient.

A Direct Heuristic Algorithm for Linear Programming

Indian Academy of Sciences (India)

Abstract. An (3) mathematically non-iterative heuristic procedure that needs no artificial variable is presented for solving linear programming problems. An optimality test is included. Numerical experiments depict the utility/scope of such a procedure.

Train Repathing in Emergencies Based on Fuzzy Linear Programming

Directory of Open Access Journals (Sweden)

Xuelei Meng

2014-01-01

Full Text Available Train pathing is a typical problem which is to assign the train trips on the sets of rail segments, such as rail tracks and links. This paper focuses on the train pathing problem, determining the paths of the train trips in emergencies. We analyze the influencing factors of train pathing, such as transferring cost, running cost, and social adverse effect cost. With the overall consideration of the segment and station capability constraints, we build the fuzzy linear programming model to solve the train pathing problem. We design the fuzzy membership function to describe the fuzzy coefficients. Furthermore, the contraction-expansion factors are introduced to contract or expand the value ranges of the fuzzy coefficients, coping with the uncertainty of the value range of the fuzzy coefficients. We propose a method based on triangular fuzzy coefficient and transfer the train pathing (fuzzy linear programming model to a determinate linear model to solve the fuzzy linear programming problem. An emergency is supposed based on the real data of the Beijing-Shanghai Railway. The model in this paper was solved and the computation results prove the availability of the model and efficiency of the algorithm.

Train repathing in emergencies based on fuzzy linear programming.

Science.gov (United States)

Meng, Xuelei; Cui, Bingmou

2014-01-01

Train pathing is a typical problem which is to assign the train trips on the sets of rail segments, such as rail tracks and links. This paper focuses on the train pathing problem, determining the paths of the train trips in emergencies. We analyze the influencing factors of train pathing, such as transferring cost, running cost, and social adverse effect cost. With the overall consideration of the segment and station capability constraints, we build the fuzzy linear programming model to solve the train pathing problem. We design the fuzzy membership function to describe the fuzzy coefficients. Furthermore, the contraction-expansion factors are introduced to contract or expand the value ranges of the fuzzy coefficients, coping with the uncertainty of the value range of the fuzzy coefficients. We propose a method based on triangular fuzzy coefficient and transfer the train pathing (fuzzy linear programming model) to a determinate linear model to solve the fuzzy linear programming problem. An emergency is supposed based on the real data of the Beijing-Shanghai Railway. The model in this paper was solved and the computation results prove the availability of the model and efficiency of the algorithm.

Study and program implementation of transient curves' piecewise linearization

International Nuclear Information System (INIS)

Shi Yang; Zu Hongbiao

2014-01-01

Background: Transient curves are essential for the stress analysis of related equipment in nuclear power plant (NPP). The actually operating data or the design transient data of a NPP usually consist of a large number of data points with very short time intervals. To simplify the analysis, transient curves are generally piecewise linearized in advance. Up to now, the piecewise linearization of transient curves is accomplished manually, Purpose: The aim is to develop a method for the piecewise linearization of transient curves, and to implement it by programming. Methods: First of all, the fitting line of a number of data points was obtained by the least square method. The segment of the fitting line is set while the accumulation error of linearization exceeds the preset limit with the increasing number of points. Then the linearization of subsequent data points was begun from the last point of the preceding curve segment to get the next segment in the same way, and continue until the final data point involved. Finally, averaging of junction points is taken for the segment connection. Results: A computer program named PLTC (Piecewise Linearization for Transient Curves) was implemented and verified by the linearization of the standard sine curve and typical transient curves of a NPP. Conclusion: The method and the PLTC program can be well used to the piecewise linearization of transient curves, with improving efficiency and precision. (authors)

Linear Programming for Vocational Education Planning. Interim Report.

Science.gov (United States)

Young, Robert C.; And Others

The purpose of the paper is to define for potential users of vocational education management information systems a quantitative analysis technique and its utilization to facilitate more effective planning of vocational education programs. Defining linear programming (LP) as a management technique used to solve complex resource allocation problems…

The Computer Program LIAR for Beam Dynamics Calculations in Linear Accelerators

International Nuclear Information System (INIS)

Assmann, R.W.; Adolphsen, C.; Bane, K.; Raubenheimer, T.O.; Siemann, R.H.; Thompson, K.

2011-01-01

Linear accelerators are the central components of the proposed next generation of linear colliders. They need to provide acceleration of up to 750 GeV per beam while maintaining very small normalized emittances. Standard simulation programs, mainly developed for storage rings, do not meet the specific requirements for high energy linear accelerators. We present a new program LIAR ('LInear Accelerator Research code') that includes wakefield effects, a 6D coupled beam description, specific optimization algorithms and other advanced features. Its modular structure allows to use and to extend it easily for different purposes. The program is available for UNIX workstations and Windows PC's. It can be applied to a broad range of accelerators. We present examples of simulations for SLC and NLC.

The Use of Linear Programming for Prediction.

Science.gov (United States)

Schnittjer, Carl J.

The purpose of the study was to develop a linear programming model to be used for prediction, test the accuracy of the predictions, and compare the accuracy with that produced by curvilinear multiple regression analysis. (Author)

The RANDOM computer program: A linear congruential random number generator

Science.gov (United States)

Miles, R. F., Jr.

1986-01-01

The RANDOM Computer Program is a FORTRAN program for generating random number sequences and testing linear congruential random number generators (LCGs). The linear congruential form of random number generator is discussed, and the selection of parameters of an LCG for a microcomputer described. This document describes the following: (1) The RANDOM Computer Program; (2) RANDOM.MOD, the computer code needed to implement an LCG in a FORTRAN program; and (3) The RANCYCLE and the ARITH Computer Programs that provide computational assistance in the selection of parameters for an LCG. The RANDOM, RANCYCLE, and ARITH Computer Programs are written in Microsoft FORTRAN for the IBM PC microcomputer and its compatibles. With only minor modifications, the RANDOM Computer Program and its LCG can be run on most micromputers or mainframe computers.

Using linear programming to analyze and optimize stochastic flow lines

DEFF Research Database (Denmark)

Helber, Stefan; Schimmelpfeng, Katja; Stolletz, Raik

2011-01-01

This paper presents a linear programming approach to analyze and optimize flow lines with limited buffer capacities and stochastic processing times. The basic idea is to solve a huge but simple linear program that models an entire simulation run of a multi-stage production process in discrete time...... programming and hence allows us to solve buffer allocation problems. We show under which conditions our method works well by comparing its results to exact values for two-machine models and approximate simulation results for longer lines....

Near-Regular Structure Discovery Using Linear Programming

KAUST Repository

Huang, Qixing; Guibas, Leonidas J.; Mitra, Niloy J.

2014-01-01

as an optimization and efficiently solve it using linear programming techniques. Our optimization has a discrete aspect, that is, the connectivity relationships among the elements, as well as a continuous aspect, namely the locations of the elements of interest. Both

NP-Hardness of optimizing the sum of Rational Linear Functions over an Asymptotic-Linear-Program

OpenAIRE

Chermakani, Deepak Ponvel

2012-01-01

We convert, within polynomial-time and sequential processing, an NP-Complete Problem into a real-variable problem of minimizing a sum of Rational Linear Functions constrained by an Asymptotic-Linear-Program. The coefficients and constants in the real-variable problem are 0, 1, -1, K, or -K, where K is the time parameter that tends to positive infinity. The number of variables, constraints, and rational linear functions in the objective, of the real-variable problem is bounded by a polynomial ...

Linear Parametric Sensitivity Analysis of the Constraint Coefficient Matrix in Linear Programs

NARCIS (Netherlands)

R.A. Zuidwijk (Rob)

2005-01-01

textabstractSensitivity analysis is used to quantify the impact of changes in the initial data of linear programs on the optimal value. In particular, parametric sensitivity analysis involves a perturbation analysis in which the effects of small changes of some or all of the initial data on an

Synthesizing Dynamic Programming Algorithms from Linear Temporal Logic Formulae

Science.gov (United States)

Rosu, Grigore; Havelund, Klaus

2001-01-01

The problem of testing a linear temporal logic (LTL) formula on a finite execution trace of events, generated by an executing program, occurs naturally in runtime analysis of software. We present an algorithm which takes an LTL formula and generates an efficient dynamic programming algorithm. The generated algorithm tests whether the LTL formula is satisfied by a finite trace of events given as input. The generated algorithm runs in linear time, its constant depending on the size of the LTL formula. The memory needed is constant, also depending on the size of the formula.

Program LINEAR (version 79-1): linearize data in the evaluated nuclear data file/version B (ENDF/B) format

International Nuclear Information System (INIS)

Cullen, D.E.

1979-01-01

Program LINEAR converts evaluated cross sections in the ENDF/B format into a tabular form that is subject to linear-linear interpolation in energy and cross section. The code also thins tables of cross sections already in that form (i.e., removes points not needed for linear interpolability). The main advantage of the code is that it allows subsequent codes to consider only linear-linear data. A listing of the source deck is available on request

General guidelines solution for linear programming with fuzzy coefficients

Directory of Open Access Journals (Sweden)

Sergio Gerardo de los Cobos Silva

2013-08-01

Full Text Available This work introduce to the Possibilistic Programming and the Fuzzy Programming as paradigms that allow to resolve problems of linear programming when the coefficients of the model or the restrictions on the same are presented as fuzzy numbers, rather than exact numbers (crisp. This work presents some examples based on [1].

A linear programming approach for placement of applicants to academic programs

OpenAIRE

Kassa, Biniyam Asmare

2013-01-01

This paper reports a linear programming approach for placement of applicants to study programs developed and implemented at the college of Business & Economics, Bahir Dar University, Bahir Dar, Ethiopia. The approach is estimated to significantly streamline the placement decision process at the college by reducing required man hour as well as the time it takes to announce placement decisions. Compared to the previous manual system where only one or two placement criteria were considered, the ...

Non-linear nuclear engineering models as genetic programming application

International Nuclear Information System (INIS)

Domingos, Roberto P.; Schirru, Roberto; Martinez, Aquilino S.

1997-01-01

This work presents a Genetic Programming paradigm and a nuclear application. A field of Artificial Intelligence, based on the concepts of Species Evolution and Natural Selection, can be understood as a self-programming process where the computer is the main agent responsible for the discovery of a program able to solve a given problem. In the present case, the problem was to find a mathematical expression in symbolic form, able to express the existent relation between equivalent ratio of a fuel cell, the enrichment of fuel elements and the multiplication factor. Such expression would avoid repeatedly reactor physics codes execution for core optimization. The results were compared with those obtained by different techniques such as Neural Networks and Linear Multiple Regression. Genetic Programming has shown to present a performance as good as, and under some features superior to Neural Network and Linear Multiple Regression. (author). 10 refs., 8 figs., 1 tabs

Sensitivity analysis of linear programming problem through a recurrent neural network

Science.gov (United States)

Das, Raja

2017-11-01

In this paper we study the recurrent neural network for solving linear programming problems. To achieve optimality in accuracy and also in computational effort, an algorithm is presented. We investigate the sensitivity analysis of linear programming problem through the neural network. A detailed example is also presented to demonstrate the performance of the recurrent neural network.

FSILP: fuzzy-stochastic-interval linear programming for supporting municipal solid waste management.

Science.gov (United States)

Li, Pu; Chen, Bing

2011-04-01

Although many studies on municipal solid waste management (MSW management) were conducted under uncertain conditions of fuzzy, stochastic, and interval coexistence, the solution to the conventional linear programming problems of integrating fuzzy method with the other two was inefficient. In this study, a fuzzy-stochastic-interval linear programming (FSILP) method is developed by integrating Nguyen's method with conventional linear programming for supporting municipal solid waste management. The Nguyen's method was used to convert the fuzzy and fuzzy-stochastic linear programming problems into the conventional linear programs, by measuring the attainment values of fuzzy numbers and/or fuzzy random variables, as well as superiority and inferiority between triangular fuzzy numbers/triangular fuzzy-stochastic variables. The developed method can effectively tackle uncertainties described in terms of probability density functions, fuzzy membership functions, and discrete intervals. Moreover, the method can also improve upon the conventional interval fuzzy programming and two-stage stochastic programming approaches, with advantageous capabilities that are easily achieved with fewer constraints and significantly reduces consumption time. The developed model was applied to a case study of municipal solid waste management system in a city. The results indicated that reasonable solutions had been generated. The solution can help quantify the relationship between the change of system cost and the uncertainties, which could support further analysis of tradeoffs between the waste management cost and the system failure risk. Copyright © 2010 Elsevier Ltd. All rights reserved.

Generalised Assignment Matrix Methodology in Linear Programming

Science.gov (United States)

Jerome, Lawrence

2012-01-01

Discrete Mathematics instructors and students have long been struggling with various labelling and scanning algorithms for solving many important problems. This paper shows how to solve a wide variety of Discrete Mathematics and OR problems using assignment matrices and linear programming, specifically using Excel Solvers although the same…

ProxImaL: efficient image optimization using proximal algorithms

KAUST Repository

Heide, Felix

2016-07-11

Computational photography systems are becoming increasingly diverse, while computational resources-for example on mobile platforms-are rapidly increasing. As diverse as these camera systems may be, slightly different variants of the underlying image processing tasks, such as demosaicking, deconvolution, denoising, inpainting, image fusion, and alignment, are shared between all of these systems. Formal optimization methods have recently been demonstrated to achieve state-of-the-art quality for many of these applications. Unfortunately, different combinations of natural image priors and optimization algorithms may be optimal for different problems, and implementing and testing each combination is currently a time-consuming and error-prone process. ProxImaL is a domain-specific language and compiler for image optimization problems that makes it easy to experiment with different problem formulations and algorithm choices. The language uses proximal operators as the fundamental building blocks of a variety of linear and nonlinear image formation models and cost functions, advanced image priors, and noise models. The compiler intelligently chooses the best way to translate a problem formulation and choice of optimization algorithm into an efficient solver implementation. In applications to the image processing pipeline, deconvolution in the presence of Poisson-distributed shot noise, and burst denoising, we show that a few lines of ProxImaL code can generate highly efficient solvers that achieve state-of-the-art results. We also show applications to the nonlinear and nonconvex problem of phase retrieval.

Fuzzy linear programming approach for solving transportation

Indian Academy of Sciences (India)

Transportation problem (TP) is an important network structured linear programming problem that arises in several contexts and has deservedly received a great deal of attention in the literature. The central concept in this problem is to find the least total transportation cost of a commodity in order to satisfy demands at ...

Large-scale linear programs in planning and prediction.

Science.gov (United States)

2017-06-01

Large-scale linear programs are at the core of many traffic-related optimization problems in both planning and prediction. Moreover, many of these involve significant uncertainty, and hence are modeled using either chance constraints, or robust optim...

Linear decomposition approach for a class of nonconvex programming problems.

Science.gov (United States)

Shen, Peiping; Wang, Chunfeng

2017-01-01

This paper presents a linear decomposition approach for a class of nonconvex programming problems by dividing the input space into polynomially many grids. It shows that under certain assumptions the original problem can be transformed and decomposed into a polynomial number of equivalent linear programming subproblems. Based on solving a series of liner programming subproblems corresponding to those grid points we can obtain the near-optimal solution of the original problem. Compared to existing results in the literature, the proposed algorithm does not require the assumptions of quasi-concavity and differentiability of the objective function, and it differs significantly giving an interesting approach to solving the problem with a reduced running time.

International program on linear electric motors

Energy Technology Data Exchange (ETDEWEB)

Dawson, G.E.; Eastham, A.R.; Parker, J.H.

1992-05-01

The International Program on Linear Electric Motors (LEM) was initiated for the purposes of commumication and coordination between various centers of expertise in LEM technology in Germany, Japan and Canada. Furthermore, it was intended to provide assessment and support of the planning of technological developments and for dissemination of information to researchers, service operators and policy makers, and to ensure that full advantage can be taken if opportunities for technology transfer occur. In the process, the program was able to provide closer contacts between researchers, to enhance and encourage collaborative research and development, and to facilitate joint ventures in advanced transportation technologies. Work done under the program is documented, and seminar materials presented by Canadian researchers in Italy, and by Italian researchers at Queen's University in Canada are presented. Five separate abstracts have been prepared for the main body of the report and the seminar materials.

Evaluating forest management policies by parametric linear programing

Science.gov (United States)

Daniel I. Navon; Richard J. McConnen

1967-01-01

An analytical and simulation technique, parametric linear programing explores alternative conditions and devises an optimal management plan for each condition. Its application in solving policy-decision problems in the management of forest lands is illustrated in an example.

C-program LINOP for the evaluation of film dosemeters by linear optimization. User manual

International Nuclear Information System (INIS)

Kragh, P.

1995-11-01

Linear programming results in an optimal measuring value for film dosemeters. The Linop program was developed to be used for linear programming. The program permits the evaluation and control of film dosemeters and of all other multi-component dosemeters. This user manual for the Linop program contains the source program, a description of the program and installation and use instructions. The data sets with programs and examples are available upon request. (orig.) [de

A property of assignment type mixed integer linear programming problems

NARCIS (Netherlands)

Benders, J.F.; van Nunen, J.A.E.E.

1982-01-01

In this paper we will proof that rather tight upper bounds can be given for the number of non-unique assignments that are achieved after solving the linear programming relaxation of some types of mixed integer linear assignment problems. Since in these cases the number of splitted assignments is

Comparison of linear, mixed integer and non-linear programming methods in energy system dispatch modelling

DEFF Research Database (Denmark)

Ommen, Torben Schmidt; Markussen, Wiebke Brix; Elmegaard, Brian

2014-01-01

In the paper, three frequently used operation optimisation methods are examined with respect to their impact on operation management of the combined utility technologies for electric power and DH (district heating) of eastern Denmark. The investigation focusses on individual plant operation...... differences and differences between the solution found by each optimisation method. One of the investigated approaches utilises LP (linear programming) for optimisation, one uses LP with binary operation constraints, while the third approach uses NLP (non-linear programming). The LP model is used...... as a benchmark, as this type is frequently used, and has the lowest amount of constraints of the three. A comparison of the optimised operation of a number of units shows significant differences between the three methods. Compared to the reference, the use of binary integer variables, increases operation...

Fundamental solution of the problem of linear programming and method of its determination

Science.gov (United States)

Petrunin, S. V.

1978-01-01

The idea of a fundamental solution to a problem in linear programming is introduced. A method of determining the fundamental solution and of applying this method to the solution of a problem in linear programming is proposed. Numerical examples are cited.

A Spreadsheet-Based, Matrix Formulation Linear Programming Lesson

DEFF Research Database (Denmark)

Harrod, Steven

2009-01-01

The article focuses on the spreadsheet-based, matrix formulation linear programming lesson. According to the article, it makes a higher level of theoretical mathematics approachable by a wide spectrum of students wherein many may not be decision sciences or quantitative methods majors. Moreover...

Controller design approach based on linear programming.

Science.gov (United States)

Tanaka, Ryo; Shibasaki, Hiroki; Ogawa, Hiromitsu; Murakami, Takahiro; Ishida, Yoshihisa

2013-11-01

This study explains and demonstrates the design method for a control system with a load disturbance observer. Observer gains are determined by linear programming (LP) in terms of the Routh-Hurwitz stability criterion and the final-value theorem. In addition, the control model has a feedback structure, and feedback gains are determined to be the linear quadratic regulator. The simulation results confirmed that compared with the conventional method, the output estimated by our proposed method converges to a reference input faster when a load disturbance is added to a control system. In addition, we also confirmed the effectiveness of the proposed method by performing an experiment with a DC motor. © 2013 ISA. Published by ISA. All rights reserved.

Sensitivity Analysis of Linear Programming and Quadratic Programming Algorithms for Control Allocation

Science.gov (United States)

Frost, Susan A.; Bodson, Marc; Acosta, Diana M.

2009-01-01

The Next Generation (NextGen) transport aircraft configurations being investigated as part of the NASA Aeronautics Subsonic Fixed Wing Project have more control surfaces, or control effectors, than existing transport aircraft configurations. Conventional flight control is achieved through two symmetric elevators, two antisymmetric ailerons, and a rudder. The five effectors, reduced to three command variables, produce moments along the three main axes of the aircraft and enable the pilot to control the attitude and flight path of the aircraft. The NextGen aircraft will have additional redundant control effectors to control the three moments, creating a situation where the aircraft is over-actuated and where a simple relationship does not exist anymore between the required effector deflections and the desired moments. NextGen flight controllers will incorporate control allocation algorithms to determine the optimal effector commands and attain the desired moments, taking into account the effector limits. Approaches to solving the problem using linear programming and quadratic programming algorithms have been proposed and tested. It is of great interest to understand their relative advantages and disadvantages and how design parameters may affect their properties. In this paper, we investigate the sensitivity of the effector commands with respect to the desired moments and show on some examples that the solutions provided using the l2 norm of quadratic programming are less sensitive than those using the l1 norm of linear programming.

Spline smoothing of histograms by linear programming

Science.gov (United States)

Bennett, J. O.

1972-01-01

An algorithm for an approximating function to the frequency distribution is obtained from a sample of size n. To obtain the approximating function a histogram is made from the data. Next, Euclidean space approximations to the graph of the histogram using central B-splines as basis elements are obtained by linear programming. The approximating function has area one and is nonnegative.

Shielding considerations for an electron linear accelerator complex for high energy physics and photonics research

International Nuclear Information System (INIS)

Holmes, J.A.; Huntzinger, C.J.

1987-01-01

Radiation shielding considerations for a major high-energy physics and photonics research complex which comprise a 50 MeV electron linear accelerator injector, a 1.0 GeV electron linear accelerator and a 1.3 GeV storage ring are discussed. The facilities will be unique because of the close proximity of personnel to the accelerator beam lines, the need to adapt existing facilities and shielding materials and the application of strict ALARA dose guidelines while providing maximum access and flexibility during a phased construction program

Formulated linear programming problems from game theory and its ...

African Journals Online (AJOL)

Formulated linear programming problems from game theory and its computer implementation using Tora package. ... Game theory, a branch of operations research examines the various concepts of decision ... AJOL African Journals Online.

An algorithm for the solution of dynamic linear programs

Science.gov (United States)

Psiaki, Mark L.

1989-01-01

The algorithm's objective is to efficiently solve Dynamic Linear Programs (DLP) by taking advantage of their special staircase structure. This algorithm constitutes a stepping stone to an improved algorithm for solving Dynamic Quadratic Programs, which, in turn, would make the nonlinear programming method of Successive Quadratic Programs more practical for solving trajectory optimization problems. The ultimate goal is to being trajectory optimization solution speeds into the realm of real-time control. The algorithm exploits the staircase nature of the large constraint matrix of the equality-constrained DLPs encountered when solving inequality-constrained DLPs by an active set approach. A numerically-stable, staircase QL factorization of the staircase constraint matrix is carried out starting from its last rows and columns. The resulting recursion is like the time-varying Riccati equation from multi-stage LQR theory. The resulting factorization increases the efficiency of all of the typical LP solution operations over that of a dense matrix LP code. At the same time numerical stability is ensured. The algorithm also takes advantage of dynamic programming ideas about the cost-to-go by relaxing active pseudo constraints in a backwards sweeping process. This further decreases the cost per update of the LP rank-1 updating procedure, although it may result in more changes of the active set that if pseudo constraints were relaxed in a non-stagewise fashion. The usual stability of closed-loop Linear/Quadratic optimally-controlled systems, if it carries over to strictly linear cost functions, implies that the saving due to reduced factor update effort may outweigh the cost of an increased number of updates. An aerospace example is presented in which a ground-to-ground rocket's distance is maximized. This example demonstrates the applicability of this class of algorithms to aerospace guidance. It also sheds light on the efficacy of the proposed pseudo constraint relaxation

MAGDM linear-programming models with distinct uncertain preference structures.

Science.gov (United States)

Xu, Zeshui S; Chen, Jian

2008-10-01

Group decision making with preference information on alternatives is an interesting and important research topic which has been receiving more and more attention in recent years. The purpose of this paper is to investigate multiple-attribute group decision-making (MAGDM) problems with distinct uncertain preference structures. We develop some linear-programming models for dealing with the MAGDM problems, where the information about attribute weights is incomplete, and the decision makers have their preferences on alternatives. The provided preference information can be represented in the following three distinct uncertain preference structures: 1) interval utility values; 2) interval fuzzy preference relations; and 3) interval multiplicative preference relations. We first establish some linear-programming models based on decision matrix and each of the distinct uncertain preference structures and, then, develop some linear-programming models to integrate all three structures of subjective uncertain preference information provided by the decision makers and the objective information depicted in the decision matrix. Furthermore, we propose a simple and straightforward approach in ranking and selecting the given alternatives. It is worth pointing out that the developed models can also be used to deal with the situations where the three distinct uncertain preference structures are reduced to the traditional ones, i.e., utility values, fuzzy preference relations, and multiplicative preference relations. Finally, we use a practical example to illustrate in detail the calculation process of the developed approach.

An overview of solution methods for multi-objective mixed integer linear programming programs

DEFF Research Database (Denmark)

Andersen, Kim Allan; Stidsen, Thomas Riis

Multiple objective mixed integer linear programming (MOMIP) problems are notoriously hard to solve to optimality, i.e. finding the complete set of non-dominated solutions. We will give an overview of existing methods. Among those are interactive methods, the two phases method and enumeration...... methods. In particular we will discuss the existing branch and bound approaches for solving multiple objective integer programming problems. Despite the fact that branch and bound methods has been applied successfully to integer programming problems with one criterion only a few attempts has been made...

Accommodation of practical constraints by a linear programming jet select. [for Space Shuttle

Science.gov (United States)

Bergmann, E.; Weiler, P.

1983-01-01

An experimental spacecraft control system will be incorporated into the Space Shuttle flight software and exercised during a forthcoming mission to evaluate its performance and handling qualities. The control system incorporates a 'phase space' control law to generate rate change requests and a linear programming jet select to compute jet firings. Posed as a linear programming problem, jet selection must represent the rate change request as a linear combination of jet acceleration vectors where the coefficients are the jet firing times, while minimizing the fuel expended in satisfying that request. This problem is solved in real time using a revised Simplex algorithm. In order to implement the jet selection algorithm in the Shuttle flight control computer, it was modified to accommodate certain practical features of the Shuttle such as limited computer throughput, lengthy firing times, and a large number of control jets. To the authors' knowledge, this is the first such application of linear programming. It was made possible by careful consideration of the jet selection problem in terms of the properties of linear programming and the Simplex algorithm. These modifications to the jet select algorithm may by useful for the design of reaction controlled spacecraft.

DESIGN OF EDUCATIONAL PROBLEMS ON LINEAR PROGRAMMING USING SYSTEMS OF COMPUTER MATHEMATICS

Directory of Open Access Journals (Sweden)

Volodymyr M. Mykhalevych

2013-11-01

Full Text Available From a perspective of the theory of educational problems a problem of substitution in the conditions of ICT use of one discipline by an educational problem of another discipline is represented. Through the example of mathematical problems of linear programming it is showed that a student’s method of operation in the course of an educational problem solving is determinant in the identification of an educational problem in relation to a specific discipline: linear programming, informatics, mathematical modeling, methods of optimization, automatic control theory, calculus etc. It is substantiated the necessity of linear programming educational problems renovation with the purpose of making students free of bulky similar arithmetic calculations and notes which often becomes a barrier to a deeper understanding of key ideas taken as a basis of algorithms used by them.

International program on linear electric motors. CIGGT report No. 92-1

Energy Technology Data Exchange (ETDEWEB)

Dawson, G.E.; Eastham, A.R.; Parker, J.H.

1992-12-31

The International Program for Linear Electric Motors (LEM) was begun in April 1989 to communicate and coordinate activities with centers of expertise in Germany, Canada, and Japan; to provide for the assessment and support of the planning of technological developments and for dissemination of information to researchers, service operators, and policy makers; and to ensure that full advantage can be taken if opportunities for technology transfer occur. This report documents the work done under the program, including standardizing linear induction motor (LIM) design characteristics; test procedures and measurement methods; rating; database for design data; criteria for evaluation of designs; computer programs for modelling performance; and a design study for an agreed application.

Indirect synthesis of multi-degree of freedom transient systems. [linear programming for a kinematically linear system

Science.gov (United States)

Pilkey, W. D.; Chen, Y. H.

1974-01-01

An indirect synthesis method is used in the efficient optimal design of multi-degree of freedom, multi-design element, nonlinear, transient systems. A limiting performance analysis which requires linear programming for a kinematically linear system is presented. The system is selected using system identification methods such that the designed system responds as closely as possible to the limiting performance. The efficiency is a result of the method avoiding the repetitive systems analyses accompanying other numerical optimization methods.

LCPT: a program for finding linear canonical transformations

International Nuclear Information System (INIS)

Char, B.W.; McNamara, B.

1979-01-01

This article describes a MACSYMA program to compute symbolically a canonical linear transformation between coordinate systems. The difficulties in implementation of this canonical small physics problem are also discussed, along with the implications that may be drawn from such difficulties about widespread MACSYMA usage by the community of computational/theoretical physicists

Interior-Point Methods for Linear Programming: A Review

Science.gov (United States)

Singh, J. N.; Singh, D.

2002-01-01

The paper reviews some recent advances in interior-point methods for linear programming and indicates directions in which future progress can be made. Most of the interior-point methods belong to any of three categories: affine-scaling methods, potential reduction methods and central path methods. These methods are discussed together with…

A Linear Programming Model to Optimize Various Objective Functions of a Foundation Type State Support Program.

Science.gov (United States)

Matzke, Orville R.

The purpose of this study was to formulate a linear programming model to simulate a foundation type support program and to apply this model to a state support program for the public elementary and secondary school districts in the State of Iowa. The model was successful in producing optimal solutions to five objective functions proposed for…

An Improved Method for Solving Multiobjective Integer Linear Fractional Programming Problem

Directory of Open Access Journals (Sweden)

Meriem Ait Mehdi

2014-01-01

Full Text Available We describe an improvement of Chergui and Moulaï’s method (2008 that generates the whole efficient set of a multiobjective integer linear fractional program based on the branch and cut concept. The general step of this method consists in optimizing (maximizing without loss of generality one of the fractional objective functions over a subset of the original continuous feasible set; then if necessary, a branching process is carried out until obtaining an integer feasible solution. At this stage, an efficient cut is built from the criteria’s growth directions in order to discard a part of the feasible domain containing only nonefficient solutions. Our contribution concerns firstly the optimization process where a linear program that we define later will be solved at each step rather than a fractional linear program. Secondly, local ideal and nadir points will be used as bounds to prune some branches leading to nonefficient solutions. The computational experiments show that the new method outperforms the old one in all the treated instances.

A Comparison of Traditional Worksheet and Linear Programming Methods for Teaching Manure Application Planning.

Science.gov (United States)

Schmitt, M. A.; And Others

1994-01-01

Compares traditional manure application planning techniques calculated to meet agronomic nutrient needs on a field-by-field basis with plans developed using computer-assisted linear programming optimization methods. Linear programming provided the most economical and environmentally sound manure application strategy. (Contains 15 references.) (MDH)

Planning Student Flow with Linear Programming: A Tunisian Case Study.

Science.gov (United States)

Bezeau, Lawrence

A student flow model in linear programming format, designed to plan the movement of students into secondary and university programs in Tunisia, is described. The purpose of the plan is to determine a sufficient number of graduating students that would flow back into the system as teachers or move into the labor market to meet fixed manpower…

Application of linear programming and perturbation theory in optimization of fuel utilization in a nuclear reactor

International Nuclear Information System (INIS)

Zavaljevski, N.

1985-01-01

Proposed optimization procedure is fast due to application of linear programming. Non-linear constraints which demand iterative application of linear programming are slowing down the calculation. Linearization can be done by different procedures starting from simple empirical rules for fuel in-core management to complicated general perturbation theory with higher order of corrections. A mathematical model was formulated for optimization of improved fuel cycle. A detailed algorithm for determining minimum of fresh fuel at the beginning of each fuel cycle is shown and the problem is linearized by first order perturbation theory and it is optimized by linear programming. Numerical illustration of the proposed method was done for the experimental reactor mostly for saving computer time

A Nutritional Analysis of the Food Basket in BIH: A Linear Programming Approach

Directory of Open Access Journals (Sweden)

Arnaut-Berilo Almira

2017-04-01

Full Text Available This paper presents linear and goal programming optimization models for determining and analyzing the food basket in Bosnia and Herzegovina (BiH in terms of adequate nutritional needs according to World Health Organization (WHO standards and World Bank (WB recommendations. A linear programming (LP model and goal linear programming model (GLP are adequate since price and nutrient contents are linearly related to food weight. The LP model provides information about the minimal value and the structure of the food basket for an average person in BiH based on nutrient needs. GLP models are designed to give us information on minimal deviations from nutrient needs if the budget is fixed. Based on these results, poverty analysis can be performed. The data used for the models consisted of 158 food items from the general consumption of the population of BiH according to COICOP classifications, with average prices in 2015 for these products.

Planning under uncertainty solving large-scale stochastic linear programs

Energy Technology Data Exchange (ETDEWEB)

Infanger, G. [Stanford Univ., CA (United States). Dept. of Operations Research]|[Technische Univ., Vienna (Austria). Inst. fuer Energiewirtschaft

1992-12-01

For many practical problems, solutions obtained from deterministic models are unsatisfactory because they fail to hedge against certain contingencies that may occur in the future. Stochastic models address this shortcoming, but up to recently seemed to be intractable due to their size. Recent advances both in solution algorithms and in computer technology now allow us to solve important and general classes of practical stochastic problems. We show how large-scale stochastic linear programs can be efficiently solved by combining classical decomposition and Monte Carlo (importance) sampling techniques. We discuss the methodology for solving two-stage stochastic linear programs with recourse, present numerical results of large problems with numerous stochastic parameters, show how to efficiently implement the methodology on a parallel multi-computer and derive the theory for solving a general class of multi-stage problems with dependency of the stochastic parameters within a stage and between different stages.

No-signaling quantum key distribution: solution by linear programming

Science.gov (United States)

Hwang, Won-Young; Bae, Joonwoo; Killoran, Nathan

2015-02-01

We outline a straightforward approach for obtaining a secret key rate using only no-signaling constraints and linear programming. Assuming an individual attack, we consider all possible joint probabilities. Initially, we study only the case where Eve has binary outcomes, and we impose constraints due to the no-signaling principle and given measurement outcomes. Within the remaining space of joint probabilities, by using linear programming, we get bound on the probability of Eve correctly guessing Bob's bit. We then make use of an inequality that relates this guessing probability to the mutual information between Bob and a more general Eve, who is not binary-restricted. Putting our computed bound together with the Csiszár-Körner formula, we obtain a positive key generation rate. The optimal value of this rate agrees with known results, but was calculated in a more straightforward way, offering the potential of generalization to different scenarios.

Optimal selection for shielding materials by fuzzy linear programming

International Nuclear Information System (INIS)

Kanai, Y.; Miura, N.; Sugasawa, S.

1996-01-01

An application of fuzzy linear programming methods to optimization of a radiation shield is presented. The main purpose of the present study is the choice of materials and the search of the ratio of mixture-component as the first stage of the methodology on optimum shielding design according to individual requirements of nuclear reactor, reprocessing facility, shipping cask installing spent fuel, ect. The characteristic values for the shield optimization may be considered their cost, spatial space, weight and some shielding qualities such as activation rate and total dose rate for neutron and gamma ray (includes secondary gamma ray). This new approach can reduce huge combination calculations for conventional two-valued logic approaches to representative single shielding calculation by group-wised optimization parameters determined in advance. Using the fuzzy linear programming method, possibilities for reducing radiation effects attainable in optimal compositions hydrated, lead- and boron-contained materials are investigated

A MICROCOMPUTER LINEAR PROGRAMMING PACKAGE: AN ALTERNATIVE TO MAINFRAMES

OpenAIRE

Laughlin, David H.

1984-01-01

This paper presents the capabilities and limitations of a microcomputer linear programming package. The solution algorithm is a version of the revised simplex. Rapid problem entry, user ease of operation, sensitivity analyses on objective function and right hand sides are advantages. A problem size of 150 activities and 64 constraints can be solved in present form. Due to problem size, limitations and lack of parametric and integer programming routines, this package is thought to have the mos...

Micosoft Excel Sensitivity Analysis for Linear and Stochastic Program Feed Formulation

Science.gov (United States)

Sensitivity analysis is a part of mathematical programming solutions and is used in making nutritional and economic decisions for a given feed formulation problem. The terms, shadow price and reduced cost, are familiar linear program (LP) terms to feed formulators. Because of the nonlinear nature of...

Linear Programming, the Simplex Algorithm and Simple Polytopes

Directory of Open Access Journals (Sweden)

Das Bhusan

2010-09-01

Full Text Available In the first part of the paper we survey some far reaching applications of the basis facts of linear programming to the combinatorial theory of simple polytopes. In the second part we discuss some recent developments concurring the simplex algorithm. We describe sub-exponential randomized pivot roles and upper bounds on the diameter of graphs of polytopes.

Stability of multi-objective bi-level linear programming problems under fuzziness

Directory of Open Access Journals (Sweden)

Abo-Sinna Mahmoud A.

2013-01-01

Full Text Available This paper deals with multi-objective bi-level linear programming problems under fuzzy environment. In the proposed method, tentative solutions are obtained and evaluated by using the partial information on preference of the decision-makers at each level. The existing results concerning the qualitative analysis of some basic notions in parametric linear programming problems are reformulated to study the stability of multi-objective bi-level linear programming problems. An algorithm for obtaining any subset of the parametric space, which has the same corresponding Pareto optimal solution, is presented. Also, this paper established the model for the supply-demand interaction in the age of electronic commerce (EC. First of all, the study uses the individual objectives of both parties as the foundation of the supply-demand interaction. Subsequently, it divides the interaction, in the age of electronic commerce, into the following two classifications: (i Market transactions, with the primary focus on the supply demand relationship in the marketplace; and (ii Information service, with the primary focus on the provider and the user of information service. By applying the bi-level programming technique of interaction process, the study will develop an analytical process to explain how supply-demand interaction achieves a compromise or why the process fails. Finally, a numerical example of information service is provided for the sake of illustration.

175 Years of Linear Programming - Minimax and Cake Topography

Indian Academy of Sciences (India)

Home; Journals; Resonance – Journal of Science Education; Volume 4; Issue 7. 175 Years of Linear Programming - Minimax and Cake Topography. Vijay Chandru M R Rao. Series Article Volume 4 Issue 7 July 1999 pp 4-13. Fulltext. Click here to view fulltext PDF. Permanent link:

Assembling networks of microbial genomes using linear programming.

Science.gov (United States)

Holloway, Catherine; Beiko, Robert G

2010-11-20

Microbial genomes exhibit complex sets of genetic affinities due to lateral genetic transfer. Assessing the relative contributions of parent-to-offspring inheritance and gene sharing is a vital step in understanding the evolutionary origins and modern-day function of an organism, but recovering and showing these relationships is a challenging problem. We have developed a new approach that uses linear programming to find between-genome relationships, by treating tables of genetic affinities (here, represented by transformed BLAST e-values) as an optimization problem. Validation trials on simulated data demonstrate the effectiveness of the approach in recovering and representing vertical and lateral relationships among genomes. Application of the technique to a set comprising Aquifex aeolicus and 75 other thermophiles showed an important role for large genomes as 'hubs' in the gene sharing network, and suggested that genes are preferentially shared between organisms with similar optimal growth temperatures. We were also able to discover distinct and common genetic contributors to each sequenced representative of genus Pseudomonas. The linear programming approach we have developed can serve as an effective inference tool in its own right, and can be an efficient first step in a more-intensive phylogenomic analysis.

Algorithmic Trading with Developmental and Linear Genetic Programming

Science.gov (United States)

Wilson, Garnett; Banzhaf, Wolfgang

A developmental co-evolutionary genetic programming approach (PAM DGP) and a standard linear genetic programming (LGP) stock trading systemare applied to a number of stocks across market sectors. Both GP techniques were found to be robust to market fluctuations and reactive to opportunities associated with stock price rise and fall, with PAMDGP generating notably greater profit in some stock trend scenarios. Both algorithms were very accurate at buying to achieve profit and selling to protect assets, while exhibiting bothmoderate trading activity and the ability to maximize or minimize investment as appropriate. The content of the trading rules produced by both algorithms are also examined in relation to stock price trend scenarios.

A novel recurrent neural network with finite-time convergence for linear programming.

Science.gov (United States)

Liu, Qingshan; Cao, Jinde; Chen, Guanrong

2010-11-01

In this letter, a novel recurrent neural network based on the gradient method is proposed for solving linear programming problems. Finite-time convergence of the proposed neural network is proved by using the Lyapunov method. Compared with the existing neural networks for linear programming, the proposed neural network is globally convergent to exact optimal solutions in finite time, which is remarkable and rare in the literature of neural networks for optimization. Some numerical examples are given to show the effectiveness and excellent performance of the new recurrent neural network.

Proximity correction of high-dosed frame with PROXECCO

Science.gov (United States)

Eisenmann, Hans; Waas, Thomas; Hartmann, Hans

1994-05-01

Usefulness of electron beam lithography is strongly related to the efficiency and quality of methods used for proximity correction. This paper addresses the above issue by proposing an extension to the new proximity correction program PROXECCO. The combination of a framing step with PROXECCO produces a pattern with a very high edge accuracy and still allows usage of the fast correction procedure. Making a frame with a higher dose imitates a fine resolution correction where the coarse part is disregarded. So after handling the high resolution effect by means of framing, an additional coarse correction is still needed. Higher doses have a higher contribution to the proximity effect. This additional proximity effect is taken into account with the help of the multi-dose input of PROXECCO. The dose of the frame is variable, depending on the deposited energy coming from backscattering of the proximity. Simulation proves the very high edge accuracy of the applied method.

Predicting Performance in Higher Education Using Proximal Predictors

NARCIS (Netherlands)

Niessen, A Susan M; Meijer, Rob R; Tendeiro, Jorge N

2016-01-01

We studied the validity of two methods for predicting academic performance and student-program fit that were proximal to important study criteria. Applicants to an undergraduate psychology program participated in a selection procedure containing a trial-studying test based on a work sample approach,

Development and adjustment of programs for solving systems of linear equations

International Nuclear Information System (INIS)

Fujimura, Toichiro

1978-03-01

Programs for solving the systems of linear equations have been adjusted and developed in expanding the scientific subroutine library SSL. The principal programs adjusted are based on the congruent method, method of product form of the inverse, orthogonal method, Crout's method for sparse system, and acceleration of iterative methods. The programs developed are based on the escalator method, direct parallel residue method and block tridiagonal method for band system. Described are usage of the programs developed and their future improvement. FORTRAN lists with simple examples in tests of the programs are also given. (auth.)

Non-linear nuclear engineering models as genetic programming application; Modelos nao-lineares de engenharia nuclear como aplicacao de programacao genetica

Energy Technology Data Exchange (ETDEWEB)

Domingos, Roberto P.; Schirru, Roberto; Martinez, Aquilino S. [Universidade Federal, Rio de Janeiro, RJ (Brazil). Coordenacao dos Programas de Pos-graduacao de Engenharia

1997-12-01

This work presents a Genetic Programming paradigm and a nuclear application. A field of Artificial Intelligence, based on the concepts of Species Evolution and Natural Selection, can be understood as a self-programming process where the computer is the main agent responsible for the discovery of a program able to solve a given problem. In the present case, the problem was to find a mathematical expression in symbolic form, able to express the existent relation between equivalent ratio of a fuel cell, the enrichment of fuel elements and the multiplication factor. Such expression would avoid repeatedly reactor physics codes execution for core optimization. The results were compared with those obtained by different techniques such as Neural Networks and Linear Multiple Regression. Genetic Programming has shown to present a performance as good as, and under some features superior to Neural Network and Linear Multiple Regression. (author). 10 refs., 8 figs., 1 tabs.

A non-linear programming approach to the computer-aided design of regulators using a linear-quadratic formulation

Science.gov (United States)

Fleming, P.

1985-01-01

A design technique is proposed for linear regulators in which a feedback controller of fixed structure is chosen to minimize an integral quadratic objective function subject to the satisfaction of integral quadratic constraint functions. Application of a non-linear programming algorithm to this mathematically tractable formulation results in an efficient and useful computer-aided design tool. Particular attention is paid to computational efficiency and various recommendations are made. Two design examples illustrate the flexibility of the approach and highlight the special insight afforded to the designer.

Genetic programming over context-free languages with linear constraints for the knapsack problem: first results.

Science.gov (United States)

Bruhn, Peter; Geyer-Schulz, Andreas

2002-01-01

In this paper, we introduce genetic programming over context-free languages with linear constraints for combinatorial optimization, apply this method to several variants of the multidimensional knapsack problem, and discuss its performance relative to Michalewicz's genetic algorithm with penalty functions. With respect to Michalewicz's approach, we demonstrate that genetic programming over context-free languages with linear constraints improves convergence. A final result is that genetic programming over context-free languages with linear constraints is ideally suited to modeling complementarities between items in a knapsack problem: The more complementarities in the problem, the stronger the performance in comparison to its competitors.

Proximity-interference wake-induced vibration at subcritical Re: Mechanism analysis using a linear dynamic model

Science.gov (United States)

Li, Xintao; Zhang, Weiwei; Gao, Chuanqiang

2018-03-01

Wake-induced vibration (WIV) contains rich and complex phenomena due to the flow interference between cylinders. The aim of the present study is to gain physical insight into the intrinsic dynamics of WIV via linear stability analysis (LSA) of the fluid-structure interaction (FSI) system. A reduced-order-model-based linear dynamic model, combined with the direct computational fluid dynamics/computational structural dynamics simulation method, is adopted to investigate WIV in two identical tandem cylinders at low Re. The spacing ratio L/D, with L as the center-to-center distance and D as the diameter of cylinders, is selected as 2.0 to consider the effect of proximity flow interference. Results show that extensive WIV along with the vortex shedding could occur at subcritical Re conditions due to the instability of one coupled mode (i.e., coupled mode I, CM-I) of the FSI system. The eigenfrequency of CM-I transfers smoothly from close to the reduced natural frequency of structure to the eigenfrequency of uncoupled wake mode as the reduced velocity U* increases. Thus, CM-I characterizes as the structure mode (SM) at low U*, while it characterizes as the wake mode (WM) at large U*. Mode conversion of CM-I is the primary cause of the "frequency transition" phenomenon observed in WIV responses. Furthermore, LSA indicates that there exists a critical mass ratio mcr*, below which no upper instability boundary of CM-I exists (Uup p e r *→∞ ). The unbounded instability of CM-I ultimately leads to the "infinite WIV" phenomenon. The neutral stability boundaries for WIV in the (Re, U*) plane are determined through LSA. It is shown that the lowest Re possible for WIV regarding the present configuration is R el o w e s t≈34 . LSA accurately captures the dynamics of WIV at subcritical Re and reveals that it is essentially a fluid-elastic instability problem. This work lays a good foundation for the investigation of WIV at supercritical high Re and gives enlightenment to the

Stochastic linear programming models, theory, and computation

CERN Document Server

Kall, Peter

2011-01-01

This new edition of Stochastic Linear Programming: Models, Theory and Computation has been brought completely up to date, either dealing with or at least referring to new material on models and methods, including DEA with stochastic outputs modeled via constraints on special risk functions (generalizing chance constraints, ICC’s and CVaR constraints), material on Sharpe-ratio, and Asset Liability Management models involving CVaR in a multi-stage setup. To facilitate use as a text, exercises are included throughout the book, and web access is provided to a student version of the authors’ SLP-IOR software. Additionally, the authors have updated the Guide to Available Software, and they have included newer algorithms and modeling systems for SLP. The book is thus suitable as a text for advanced courses in stochastic optimization, and as a reference to the field. From Reviews of the First Edition: "The book presents a comprehensive study of stochastic linear optimization problems and their applications. … T...

SLFP: a stochastic linear fractional programming approach for sustainable waste management.

Science.gov (United States)

Zhu, H; Huang, G H

2011-12-01

A stochastic linear fractional programming (SLFP) approach is developed for supporting sustainable municipal solid waste management under uncertainty. The SLFP method can solve ratio optimization problems associated with random information, where chance-constrained programming is integrated into a linear fractional programming framework. It has advantages in: (1) comparing objectives of two aspects, (2) reflecting system efficiency, (3) dealing with uncertainty expressed as probability distributions, and (4) providing optimal-ratio solutions under different system-reliability conditions. The method is applied to a case study of waste flow allocation within a municipal solid waste (MSW) management system. The obtained solutions are useful for identifying sustainable MSW management schemes with maximized system efficiency under various constraint-violation risks. The results indicate that SLFP can support in-depth analysis of the interrelationships among system efficiency, system cost and system-failure risk. Copyright © 2011 Elsevier Ltd. All rights reserved.

Fitting program for linear regressions according to Mahon (1996)

Energy Technology Data Exchange (ETDEWEB)

2018-01-09

This program takes the users' Input data and fits a linear regression to it using the prescription presented by Mahon (1996). Compared to the commonly used York fit, this method has the correct prescription for measurement error propagation. This software should facilitate the proper fitting of measurements with a simple Interface.

Analysis of Students' Errors on Linear Programming at Secondary ...

African Journals Online (AJOL)

The purpose of this study was to identify secondary school students' errors on linear programming at 'O' level. It is based on the fact that students' errors inform teaching hence an essential tool for any serious mathematics teacher who intends to improve mathematics teaching. The study was guided by a descriptive survey ...

Life cycle cost optimization of biofuel supply chains under uncertainties based on interval linear programming

DEFF Research Database (Denmark)

Ren, Jingzheng; Dong, Liang; Sun, Lu

2015-01-01

in this model, and the price of the resources, the yield of grain and the market demands were regarded as interval numbers instead of constants. An interval linear programming was developed, and a method for solving interval linear programming was presented. An illustrative case was studied by the proposed...

Discounted semi-Markov decision processes : linear programming and policy iteration

NARCIS (Netherlands)

Wessels, J.; van Nunen, J.A.E.E.

1975-01-01

For semi-Markov decision processes with discounted rewards we derive the well known results regarding the structure of optimal strategies (nonrandomized, stationary Markov strategies) and the standard algorithms (linear programming, policy iteration). Our analysis is completely based on a primal

Discounted semi-Markov decision processes : linear programming and policy iteration

NARCIS (Netherlands)

Wessels, J.; van Nunen, J.A.E.E.

1974-01-01

For semi-Markov decision processes with discounted rewards we derive the well known results regarding the structure of optimal strategies (nonrandomized, stationary Markov strategies) and the standard algorithms (linear programming, policy iteration). Our analysis is completely based on a primal

BEAMPATH: a program library for beam dynamics simulation in linear accelerators

International Nuclear Information System (INIS)

Batygin, Y.K.

1992-01-01

A structured programming technique was used to develop software for space charge dominated beams investigation in linear accelerators. The method includes hierarchical program design using program independent modules and a flexible combination of modules to provide a most effective version of structure for every specific case of simulation. A modular program BEAMPATH was developed for 2D and 3D particle-in-cell simulation of beam dynamics in a structure containing RF gaps, radio-frequency quadrupoles (RFQ), multipole lenses, waveguides, bending magnets and solenoids. (author) 5 refs.; 2 figs

Depressionary Effect of Proximity of Residential Properties to Waste ...

African Journals Online (AJOL)

Past studies have researched these impacts using a variety of hedonic models and Marginal Implicit Pricing, however, this study takes a special focus on the resident's perspective based on the linear proximity to waste disposal sites. 260 questionnaires were distributed to residents within 1km to the site and Estate ...

Relaxation Methods for Strictly Convex Regularizations of Piecewise Linear Programs

International Nuclear Information System (INIS)

Kiwiel, K. C.

1998-01-01

We give an algorithm for minimizing the sum of a strictly convex function and a convex piecewise linear function. It extends several dual coordinate ascent methods for large-scale linearly constrained problems that occur in entropy maximization, quadratic programming, and network flows. In particular, it may solve exact penalty versions of such (possibly inconsistent) problems, and subproblems of bundle methods for nondifferentiable optimization. It is simple, can exploit sparsity, and in certain cases is highly parallelizable. Its global convergence is established in the recent framework of B -functions (generalized Bregman functions)

A Partitioning and Bounded Variable Algorithm for Linear Programming

Science.gov (United States)

Sheskin, Theodore J.

2006-01-01

An interesting new partitioning and bounded variable algorithm (PBVA) is proposed for solving linear programming problems. The PBVA is a variant of the simplex algorithm which uses a modified form of the simplex method followed by the dual simplex method for bounded variables. In contrast to the two-phase method and the big M method, the PBVA does…

Optimal traffic control in highway transportation networks using linear programming

KAUST Repository

Li, Yanning; Canepa, Edward S.; Claudel, Christian G.

2014-01-01

of the Hamilton-Jacobi PDE, the problem of controlling the state of the system on a network link in a finite horizon can be posed as a Linear Program. Assuming all intersections in the network are controllable, we show that the optimization approach can

Linear Programming Approaches for Power Savings in Software-defined Networks

NARCIS (Netherlands)

Moghaddam, F.A.; Grosso, P.

2016-01-01

Software-defined networks have been proposed as a viable solution to decrease the power consumption of the networking component in data center networks. Still the question remains on which scheduling algorithms are most suited to achieve this goal. We propose 4 different linear programming

Method for solving fully fuzzy linear programming problems using deviation degree measure

Institute of Scientific and Technical Information of China (English)

Haifang Cheng; Weilai Huang; Jianhu Cai

2013-01-01

A new ful y fuzzy linear programming (FFLP) prob-lem with fuzzy equality constraints is discussed. Using deviation degree measures, the FFLP problem is transformed into a crispδ-parametric linear programming (LP) problem. Giving the value of deviation degree in each constraint, the δ-fuzzy optimal so-lution of the FFLP problem can be obtained by solving this LP problem. An algorithm is also proposed to find a balance-fuzzy optimal solution between two goals in conflict: to improve the va-lues of the objective function and to decrease the values of the deviation degrees. A numerical example is solved to il ustrate the proposed method.

Nutrient density score of typical Indonesian foods and dietary formulation using linear programming.

Science.gov (United States)

Jati, Ignasius Radix A P; Vadivel, Vellingiri; Nöhr, Donatus; Biesalski, Hans Konrad

2012-12-01

The present research aimed to analyse the nutrient density (ND), nutrient adequacy score (NAS) and energy density (ED) of Indonesian foods and to formulate a balanced diet using linear programming. Data on typical Indonesian diets were obtained from the Indonesian Socio-Economic Survey 2008. ND was investigated for 122 Indonesian foods. NAS was calculated for single nutrients such as Fe, Zn and vitamin A. Correlation analysis was performed between ND and ED, as well as between monthly expenditure class and food consumption pattern in Indonesia. Linear programming calculations were performed using the software POM-QM for Windows version 3. Republic of Indonesia, 2008. Public households (n 68 800). Vegetables had the highest ND of the food groups, followed by animal-based foods, fruits and staple foods. Based on NAS, the top ten food items for each food group were identified. Most of the staple foods had high ED and contributed towards daily energy fulfillment, followed by animal-based foods, vegetables and fruits. Commodities with high ND tended to have low ED. Linear programming could be used to formulate a balanced diet. In contrast to staple foods, purchases of fruit, vegetables and animal-based foods increased with the rise of monthly expenditure. People should select food items based on ND and NAS to alleviate micronutrient deficiencies in Indonesia. Dietary formulation calculated using linear programming to achieve RDA levels for micronutrients could be recommended for different age groups of the Indonesian population.

Linear programming algorithms and applications

CERN Document Server

Vajda, S

1981-01-01

This text is based on a course of about 16 hours lectures to students of mathematics, statistics, and/or operational research. It is intended to introduce readers to the very wide range of applicability of linear programming, covering problems of manage­ ment, administration, transportation and a number of other uses which are mentioned in their context. The emphasis is on numerical algorithms, which are illustrated by examples of such modest size that the solutions can be obtained using pen and paper. It is clear that these methods, if applied to larger problems, can also be carried out on automatic (electronic) computers. Commercially available computer packages are, in fact, mainly based on algorithms explained in this book. The author is convinced that the user of these algorithms ought to be knowledgeable about the underlying theory. Therefore this volume is not merely addressed to the practitioner, but also to the mathematician who is interested in relatively new developments in algebraic theory and in...

A mixed integer linear program for an integrated fishery | Hasan ...

African Journals Online (AJOL)

... and labour allocation of quota based integrated fisheries. We demonstrate the workability of our model with a numerical example and sensitivity analysis based on data obtained from one of the major fisheries in New Zealand. Keywords: mixed integer linear program, fishing, trawler scheduling, processing, quotas ORiON: ...

A linear programming approach for placement of applicants to academic programs.

Science.gov (United States)

Kassa, Biniyam Asmare

2013-01-01

This paper reports a linear programming approach for placement of applicants to study programs developed and implemented at the college of Business & Economics, Bahir Dar University, Bahir Dar, Ethiopia. The approach is estimated to significantly streamline the placement decision process at the college by reducing required man hour as well as the time it takes to announce placement decisions. Compared to the previous manual system where only one or two placement criteria were considered, the new approach allows the college's management to easily incorporate additional placement criteria, if needed. Comparison of our approach against manually constructed placement decisions based on actual data for the 2012/13 academic year suggested that about 93 percent of the placements from our model concur with the actual placement decisions. For the remaining 7 percent of placements, however, the actual placements made by the manual system display inconsistencies of decisions judged against the very criteria intended to guide placement decisions by the college's program management office. Overall, the new approach proves to be a significant improvement over the manual system in terms of efficiency of the placement process and the quality of placement decisions.

adapta~k>n -11 of the surrogate memods for linear programming ...

African Journals Online (AJOL)

2005-08-02

Aug 2, 2005 ... inequality problem is made uj~ of the primal and dual optimal solutions for the given primal ... KEYWORDS: Linear Programming, Duality Theory, Surrogate Methods. ..... replaces x and the process IS repeated with the new x.

Detection method of proximal caries using line profile in digital intra-oral radiography

Energy Technology Data Exchange (ETDEWEB)

Choi, Yong Suk; Kim, Gyu Tae; Hwang, Eui Hwan; Lee, Min Ja; Choi, Sam Jin; Park, Hun Kuk [Department of Oral and Maxillofacial Radiology, School of Dentistry and Institute of Oral Biology, Kyung Hee University, Seoul (Korea, Republic of); Park, Jeong Hoon [Department of Biomedical Engineering, College of Medicine, Kyung Hee University, Seoul (Korea, Republic of)

2009-12-15

The purpose of this study was to investigate how to detect proximal caries using line profile and validate linear measurements of proximal caries lesions by basic digital manipulation of radiographic images. The X-ray images of control group (15) and caries teeth (15) from patients were used. For each image, the line profile at the proximal caries-susceptible zone was calculated. To evaluate the contrast as a function of line profile to detect proximal caries, a difference coefficient (D) that indicates the relative difference between caries and sound dentin or intact enamel was measured. Mean values of D were 0.0354 {+-} 0.0155 in non-caries and 0.2632 {+-} 0.0982 in caries (p<0.001). The mean values of caries group were higher than non-caries group and there was correlation between proximal dental caries and D. It is demonstrated that the mean value of D from caries group was higher than that of control group. From the result, values of D possess great potentiality as a new detection parameter for proximal dental caries.

Detection method of proximal caries using line profile in digital intra-oral radiography

International Nuclear Information System (INIS)

Choi, Yong Suk; Kim, Gyu Tae; Hwang, Eui Hwan; Lee, Min Ja; Choi, Sam Jin; Park, Hun Kuk; Park, Jeong Hoon

2009-01-01

The purpose of this study was to investigate how to detect proximal caries using line profile and validate linear measurements of proximal caries lesions by basic digital manipulation of radiographic images. The X-ray images of control group (15) and caries teeth (15) from patients were used. For each image, the line profile at the proximal caries-susceptible zone was calculated. To evaluate the contrast as a function of line profile to detect proximal caries, a difference coefficient (D) that indicates the relative difference between caries and sound dentin or intact enamel was measured. Mean values of D were 0.0354 ± 0.0155 in non-caries and 0.2632 ± 0.0982 in caries (p<0.001). The mean values of caries group were higher than non-caries group and there was correlation between proximal dental caries and D. It is demonstrated that the mean value of D from caries group was higher than that of control group. From the result, values of D possess great potentiality as a new detection parameter for proximal dental caries.

The use of linear programming in optimization of HDR implant dose distributions

International Nuclear Information System (INIS)

Jozsef, Gabor; Streeter, Oscar E.; Astrahan, Melvin A.

2003-01-01

The introduction of high dose rate brachytherapy enabled optimization of dose distributions to be used on a routine basis. The objective of optimization is to homogenize the dose distribution within the implant while simultaneously satisfying dose constraints on certain points. This is accomplished by varying the time the source dwells at different locations. As the dose at any point is a linear function of the dwell times, a linear programming approach seems to be a natural choice. The dose constraints are inherently linear inequalities. Homogeneity requirements are linearized by minimizing the maximum deviation of the doses at points inside the implant from a prescribed dose. The revised simplex method was applied for the solution of this linear programming problem. In the homogenization process the possible source locations were chosen as optimization points. To avoid the problem of the singular value of the dose at a source location from the source itself we define the 'self-contribution' as the dose at a small distance from the source. The effect of varying this distance is discussed. Test cases were optimized for planar, biplanar and cylindrical implants. A semi-irregular, fan-like implant with diverging needles was also investigated. Mean central dose calculation based on 3D Delaunay-triangulation of the source locations was used to evaluate the dose distributions. The optimization method resulted in homogeneous distributions (for brachytherapy). Additional dose constraints--when applied--were satisfied. The method is flexible enough to include other linear constraints such as the inclusion of the centroids of the Delaunay-triangulation for homogenization, or limiting the maximum allowable dwell time

Reduced-Size Integer Linear Programming Models for String Selection Problems: Application to the Farthest String Problem.

Science.gov (United States)

Zörnig, Peter

2015-08-01

We present integer programming models for some variants of the farthest string problem. The number of variables and constraints is substantially less than that of the integer linear programming models known in the literature. Moreover, the solution of the linear programming-relaxation contains only a small proportion of noninteger values, which considerably simplifies the rounding process. Numerical tests have shown excellent results, especially when a small set of long sequences is given.

User's Guide to the Weighted-Multiple-Linear Regression Program (WREG version 1.0)

Science.gov (United States)

Eng, Ken; Chen, Yin-Yu; Kiang, Julie.E.

2009-01-01

Streamflow is not measured at every location in a stream network. Yet hydrologists, State and local agencies, and the general public still seek to know streamflow characteristics, such as mean annual flow or flood flows with different exceedance probabilities, at ungaged basins. The goals of this guide are to introduce and familiarize the user with the weighted multiple-linear regression (WREG) program, and to also provide the theoretical background for program features. The program is intended to be used to develop a regional estimation equation for streamflow characteristics that can be applied at an ungaged basin, or to improve the corresponding estimate at continuous-record streamflow gages with short records. The regional estimation equation results from a multiple-linear regression that relates the observable basin characteristics, such as drainage area, to streamflow characteristics.

Proximal Tubular Injury in Medullary Rays Is an Early Sign of Acute Tacrolimus Nephrotoxicity

Directory of Open Access Journals (Sweden)

Diane Cosner

2015-01-01

Full Text Available Tacrolimus (FK506 is one of the principal immunosuppressive agents used after solid organ transplantations to prevent allograft rejection. Chronic renal injury induced by tacrolimus is characterized by linear fibrosis in the medullary rays; however, the early morphologic findings of acute tacrolimus nephrotoxicity are not well characterized. Kidney injury molecule-1 (KIM-1 is a specific injury biomarker that has been proven to be useful in the diagnosis of mild to severe acute tubular injury on renal biopsies. This study was motivated by a patient with acute kidney injury associated with elevated serum tacrolimus levels in whom KIM-1 staining was present only in proximal tubules located in the medullary rays in the setting of otherwise normal light, immunofluorescent, and electron microscopy. We subsequently evaluated KIM-1 expression in 45 protocol and 39 indicated renal transplant biopsies to determine whether higher serum levels of tacrolimus were associated with acute segment specific injury to the proximal tubule, as reflected by KIM-1 staining in the proximal tubules of the cortical medullary rays. The data suggest that tacrolimus toxicity preferentially affects proximal tubules in medullary rays and that this targeted injury is a precursor lesion for the linear fibrosis seen in chronic tacrolimus toxicity.

A Comparison of Linear and Systems Thinking Approaches for Program Evaluation Illustrated Using the Indiana Interdisciplinary GK-12

Science.gov (United States)

Dyehouse, Melissa; Bennett, Deborah; Harbor, Jon; Childress, Amy; Dark, Melissa

2009-01-01

Logic models are based on linear relationships between program resources, activities, and outcomes, and have been used widely to support both program development and evaluation. While useful in describing some programs, the linear nature of the logic model makes it difficult to capture the complex relationships within larger, multifaceted…

Linear programming based on neural networks for radiotherapy treatment planning

International Nuclear Information System (INIS)

Xingen Wu; Limin Luo

2000-01-01

In this paper, we propose a neural network model for linear programming that is designed to optimize radiotherapy treatment planning (RTP). This kind of neural network can be easily implemented by using a kind of 'neural' electronic system in order to obtain an optimization solution in real time. We first give an introduction to the RTP problem and construct a non-constraint objective function for the neural network model. We adopt a gradient algorithm to minimize the objective function and design the structure of the neural network for RTP. Compared to traditional linear programming methods, this neural network model can reduce the time needed for convergence, the size of problems (i.e., the number of variables to be searched) and the number of extra slack and surplus variables needed. We obtained a set of optimized beam weights that result in a better dose distribution as compared to that obtained using the simplex algorithm under the same initial condition. The example presented in this paper shows that this model is feasible in three-dimensional RTP. (author)

Correlation analysis of alveolar bone loss in buccal/palatal and proximal surfaces in rats

Directory of Open Access Journals (Sweden)

Carolina Barrera de Azambuja

2012-12-01

Full Text Available The aim was to correlate alveolar bone loss in the buccal/palatal and the mesial/distal surfaces of upper molars in rats. Thirty-three, 60-day-old, male Wistar rats were divided in two groups, one treated with alcohol and the other not treated with alcohol. All rats received silk ligatures on the right upper second molars for 4 weeks. The rats were then euthanized and their maxillae were split and defleshed with sodium hypochlorite (9%. The cemento-enamel junction (CEJ was stained with 1% methylene blue and the alveolar bone loss in the buccal/palatal surfaces was measured linearly in 5 points on standardized digital photographs. Measurement of the proximal sites was performed by sectioning the hemimaxillae, restaining the CEJ and measuring the alveolar bone loss linearly in 3 points. A calibrated and blinded examiner performed all the measurements. Intraclass Correlation Coefficient revealed values of 0.96 and 0.89 for buccal/lingual and proximal surfaces, respectively. The Pearson Correlation Coefficient (r between measurements in buccal/palatal and proximal surfaces was 0.35 and 0.05 for the group treated with alcohol, with and without ligatures, respectively. The best correlations between buccal/palatal and proximal surfaces were observed in animals not treated with alcohol, in sites both with and without ligatures (r = 0.59 and 0.65, respectively. A positive correlation was found between alveolar bone loss in buccal/palatal and proximal surfaces. The correlation is stronger in animals that were not treated with alcohol, in sites without ligatures. Areas with and without ligature-induced periodontal destruction allow detection of alveolar bone loss in buccal/palatal and proximal surfaces.

Robust Control Design via Linear Programming

Science.gov (United States)

Keel, L. H.; Bhattacharyya, S. P.

1998-01-01

This paper deals with the problem of synthesizing or designing a feedback controller of fixed dynamic order. The closed loop specifications considered here are given in terms of a target performance vector representing a desired set of closed loop transfer functions connecting various signals. In general these point targets are unattainable with a fixed order controller. By enlarging the target from a fixed point set to an interval set the solvability conditions with a fixed order controller are relaxed and a solution is more easily enabled. Results from the parametric robust control literature can be used to design the interval target family so that the performance deterioration is acceptable, even when plant uncertainty is present. It is shown that it is possible to devise a computationally simple linear programming approach that attempts to meet the desired closed loop specifications.

The shape of the hominoid proximal femur: a geometric morphometric analysis

Science.gov (United States)

Harmon, Elizabeth H

2007-01-01

As part of the hip joint, the proximal femur is an integral locomotor component. Although a link between locomotion and the morphology of some aspects of the proximal femur has been identified, inclusive shapes of this element have not been compared among behaviourally heterogeneous hominoids. Previous analyses have partitioned complex proximal femoral morphology into discrete features (e.g. head, neck, greater trochanter) to facilitate conventional linear measurements. In this study, three-dimensional geometric morphometrics are used to examine the shape of the proximal femur in hominoids to determine whether femoral shape co-varies with locomotor category. Fourteen landmarks are recorded on adult femora of Homo, Pan, Gorilla, Pongo and Hylobates. Generalized Procrustes analysis (GPA) is used to adjust for position, orientation and scale among landmark configurations. Principal components analysis is used to collapse and compare variation in residuals from GPA, and thin-plate spline analysis is used to visualize shape change among taxa. The results indicate that knucklewalking African apes are similar to one another in femoral shape, whereas the more suspensory Asian apes diverge from the African ape pattern. The shape of the human and orangutan proximal femur converge, a result that is best explained in terms of the distinct requirements for locomotion in each group. These findings suggest that the shape of the proximal femur is brought about primarily by locomotor behaviour. PMID:17310545

A linear programming model of diet choice of free-living beavers

NARCIS (Netherlands)

Nolet, BA; VanderVeer, PJ; Evers, EGJ; Ottenheim, MM

1995-01-01

Linear programming has been remarkably successful in predicting the diet choice of generalist herbivores. We used this technique to test the diet choice of free-living beavers (Castor fiber) in the Biesbosch (The Netherlands) under different Foraging goals, i.e. maximization of intake of energy,

Waste management under multiple complexities: Inexact piecewise-linearization-based fuzzy flexible programming

International Nuclear Information System (INIS)

Sun Wei; Huang, Guo H.; Lv Ying; Li Gongchen

2012-01-01

Highlights: ► Inexact piecewise-linearization-based fuzzy flexible programming is proposed. ► It’s the first application to waste management under multiple complexities. ► It tackles nonlinear economies-of-scale effects in interval-parameter constraints. ► It estimates costs more accurately than the linear-regression-based model. ► Uncertainties are decreased and more satisfactory interval solutions are obtained. - Abstract: To tackle nonlinear economies-of-scale (EOS) effects in interval-parameter constraints for a representative waste management problem, an inexact piecewise-linearization-based fuzzy flexible programming (IPFP) model is developed. In IPFP, interval parameters for waste amounts and transportation/operation costs can be quantified; aspiration levels for net system costs, as well as tolerance intervals for both capacities of waste treatment facilities and waste generation rates can be reflected; and the nonlinear EOS effects transformed from objective function to constraints can be approximated. An interactive algorithm is proposed for solving the IPFP model, which in nature is an interval-parameter mixed-integer quadratically constrained programming model. To demonstrate the IPFP’s advantages, two alternative models are developed to compare their performances. One is a conventional linear-regression-based inexact fuzzy programming model (IPFP2) and the other is an IPFP model with all right-hand-sides of fussy constraints being the corresponding interval numbers (IPFP3). The comparison results between IPFP and IPFP2 indicate that the optimized waste amounts would have the similar patterns in both models. However, when dealing with EOS effects in constraints, the IPFP2 may underestimate the net system costs while the IPFP can estimate the costs more accurately. The comparison results between IPFP and IPFP3 indicate that their solutions would be significantly different. The decreased system uncertainties in IPFP’s solutions demonstrate

Introduction to linear programming: Coalitional game experiments

Energy Technology Data Exchange (ETDEWEB)

Lucas, W.

1994-12-31

Many solution notions in the multiperson cooperative games (in characteristic function form) make use of linear programming (LP). The popular concept of the {open_quotes}core{close_quotes} of a coalitional game is a special type of LP. It can be introduced in a very simple and quite exciting manner by means of a group experiment. A total of fifty dollars will be given to three randomly selected attendees who will take part in an experiment during this talk, presuming they behave in a Pareto optimal manner. Furthermore, the dual of the particular LP for the core gives rise to the idea of {open_quotes}balanced sets{close_quotes} which is an interesting combinatorial structure in its own right.

The fastclime Package for Linear Programming and Large-Scale Precision Matrix Estimation in R.

Science.gov (United States)

Pang, Haotian; Liu, Han; Vanderbei, Robert

2014-02-01

We develop an R package fastclime for solving a family of regularized linear programming (LP) problems. Our package efficiently implements the parametric simplex algorithm, which provides a scalable and sophisticated tool for solving large-scale linear programs. As an illustrative example, one use of our LP solver is to implement an important sparse precision matrix estimation method called CLIME (Constrained L 1 Minimization Estimator). Compared with existing packages for this problem such as clime and flare, our package has three advantages: (1) it efficiently calculates the full piecewise-linear regularization path; (2) it provides an accurate dual certificate as stopping criterion; (3) it is completely coded in C and is highly portable. This package is designed to be useful to statisticians and machine learning researchers for solving a wide range of problems.

[Accuracy of computer aided measurement for detecting dental proximal caries lesions in images of cone-beam computed tomography].

Science.gov (United States)

Zhang, Z L; Li, J P; Li, G; Ma, X C

2017-02-09

Objective: To establish and validate a computer program used to aid the detection of dental proximal caries in the images cone beam computed tomography (CBCT) images. Methods: According to the characteristics of caries lesions in X-ray images, a computer aided detection program for proximal caries was established with Matlab and Visual C++. The whole process for caries lesion detection included image import and preprocessing, measuring average gray value of air area, choosing region of interest and calculating gray value, defining the caries areas. The program was used to examine 90 proximal surfaces from 45 extracted human teeth collected from Peking University School and Hospital of Stomatology. The teeth were then scanned with a CBCT scanner (Promax 3D). The proximal surfaces of the teeth were respectively detected by caries detection program and scored by human observer for the extent of lesions with 6-level-scale. With histologic examination serving as the reference standard, the caries detection program and the human observer performances were assessed with receiver operating characteristic (ROC) curves. Student t -test was used to analyze the areas under the ROC curves (AUC) for the differences between caries detection program and human observer. Spearman correlation coefficient was used to analyze the detection accuracy of caries depth. Results: For the diagnosis of proximal caries in CBCT images, the AUC values of human observers and caries detection program were 0.632 and 0.703, respectively. There was a statistically significant difference between the AUC values ( P= 0.023). The correlation between program performance and gold standard (correlation coefficient r (s)=0.525) was higher than that of observer performance and gold standard ( r (s)=0.457) and there was a statistically significant difference between the correlation coefficients ( P= 0.000). Conclusions: The program that automatically detects dental proximal caries lesions could improve the

Computer Program For Linear Algebra

Science.gov (United States)

Krogh, F. T.; Hanson, R. J.

1987-01-01

Collection of routines provided for basic vector operations. Basic Linear Algebra Subprogram (BLAS) library is collection from FORTRAN-callable routines for employing standard techniques to perform basic operations of numerical linear algebra.

Linear programming to build food-based dietary guidelines: Romanian food baskets

DEFF Research Database (Denmark)

Parlesak, Alexandr; Robertson, Aileen; Hondru, Gabriela

approach using linear programming methodology to design national dietary recommendations which aim to prevent both NCDs and micronutrient deficiencies and still be affordable by low income groups. This new approach is applied within the context of food availability in Romania in 2014. Eating the same food...... every day is unrealistic and too monotonous to be maintained, so this novel approach is used to select a wide range of diverse foods that can be recommended for a period of up to, for example, one month. The following are the key findings of this report. • The simplest version of the Romanian food.......65 lei (~€ 4.46) for a day. • Key nutrients, primarily vitamin D, calcium, potassium and iron, were found to control the overall price. • The least expensive basket (one day’s rations) is monotonous and the linear programming approach is used to select a wide range of foods that can be recommended...

Fuzzy linear programming based optimal fuel scheduling incorporating blending/transloading facilities

Energy Technology Data Exchange (ETDEWEB)

Djukanovic, M.; Babic, B.; Milosevic, B. [Electrical Engineering Inst. Nikola Tesla, Belgrade (Yugoslavia); Sobajic, D.J. [EPRI, Palo Alto, CA (United States). Power System Control; Pao, Y.H. [Case Western Reserve Univ., Cleveland, OH (United States)]|[AI WARE, Inc., Cleveland, OH (United States)

1996-05-01

In this paper the blending/transloading facilities are modeled using an interactive fuzzy linear programming (FLP), in order to allow the decision-maker to solve the problem of uncertainty of input information within the fuel scheduling optimization. An interactive decision-making process is formulated in which decision-maker can learn to recognize good solutions by considering all possibilities of fuzziness. The application of the fuzzy formulation is accompanied by a careful examination of the definition of fuzziness, appropriateness of the membership function and interpretation of results. The proposed concept provides a decision support system with integration-oriented features, whereby the decision-maker can learn to recognize the relative importance of factors in the specific domain of optimal fuel scheduling (OFS) problem. The formulation of a fuzzy linear programming problem to obtain a reasonable nonfuzzy solution under consideration of the ambiguity of parameters, represented by fuzzy numbers, is introduced. An additional advantage of the FLP formulation is its ability to deal with multi-objective problems.

Polymorphic Uncertain Linear Programming for Generalized Production Planning Problems

Directory of Open Access Journals (Sweden)

Xinbo Zhang

2014-01-01

Full Text Available A polymorphic uncertain linear programming (PULP model is constructed to formulate a class of generalized production planning problems. In accordance with the practical environment, some factors such as the consumption of raw material, the limitation of resource and the demand of product are incorporated into the model as parameters of interval and fuzzy subsets, respectively. Based on the theory of fuzzy interval program and the modified possibility degree for the order of interval numbers, a deterministic equivalent formulation for this model is derived such that a robust solution for the uncertain optimization problem is obtained. Case study indicates that the constructed model and the proposed solution are useful to search for an optimal production plan for the polymorphic uncertain generalized production planning problems.

APPLYING ROBUST RANKING METHOD IN TWO PHASE FUZZY OPTIMIZATION LINEAR PROGRAMMING PROBLEMS (FOLPP

Directory of Open Access Journals (Sweden)

Monalisha Pattnaik

2014-12-01

Full Text Available Background: This paper explores the solutions to the fuzzy optimization linear program problems (FOLPP where some parameters are fuzzy numbers. In practice, there are many problems in which all decision parameters are fuzzy numbers, and such problems are usually solved by either probabilistic programming or multi-objective programming methods. Methods: In this paper, using the concept of comparison of fuzzy numbers, a very effective method is introduced for solving these problems. This paper extends linear programming based problem in fuzzy environment. With the problem assumptions, the optimal solution can still be theoretically solved using the two phase simplex based method in fuzzy environment. To handle the fuzzy decision variables can be initially generated and then solved and improved sequentially using the fuzzy decision approach by introducing robust ranking technique. Results and conclusions: The model is illustrated with an application and a post optimal analysis approach is obtained. The proposed procedure was programmed with MATLAB (R2009a version software for plotting the four dimensional slice diagram to the application. Finally, numerical example is presented to illustrate the effectiveness of the theoretical results, and to gain additional managerial insights. 

Updating Linear Schedules with Lowest Cost: a Linear Programming Model

Science.gov (United States)

Biruk, Sławomir; Jaśkowski, Piotr; Czarnigowska, Agata

2017-10-01

Many civil engineering projects involve sets of tasks repeated in a predefined sequence in a number of work areas along a particular route. A useful graphical representation of schedules of such projects is time-distance diagrams that clearly show what process is conducted at a particular point of time and in particular location. With repetitive tasks, the quality of project performance is conditioned by the ability of the planner to optimize workflow by synchronizing the works and resources, which usually means that resources are planned to be continuously utilized. However, construction processes are prone to risks, and a fully synchronized schedule may expire if a disturbance (bad weather, machine failure etc.) affects even one task. In such cases, works need to be rescheduled, and another optimal schedule should be built for the changed circumstances. This typically means that, to meet the fixed completion date, durations of operations have to be reduced. A number of measures are possible to achieve such reduction: working overtime, employing more resources or relocating resources from less to more critical tasks, but they all come at a considerable cost and affect the whole project. The paper investigates the problem of selecting the measures that reduce durations of tasks of a linear project so that the cost of these measures is kept to the minimum and proposes an algorithm that could be applied to find optimal solutions as the need to reschedule arises. Considering that civil engineering projects, such as road building, usually involve less process types than construction projects, the complexity of scheduling problems is lower, and precise optimization algorithms can be applied. Therefore, the authors put forward a linear programming model of the problem and illustrate its principle of operation with an example.

A new methodological development for solving linear bilevel integer programming problems in hybrid fuzzy environment

Directory of Open Access Journals (Sweden)

Animesh Biswas

2016-04-01

Full Text Available This paper deals with fuzzy goal programming approach to solve fuzzy linear bilevel integer programming problems with fuzzy probabilistic constraints following Pareto distribution and Frechet distribution. In the proposed approach a new chance constrained programming methodology is developed from the view point of managing those probabilistic constraints in a hybrid fuzzy environment. A method of defuzzification of fuzzy numbers using ?-cut has been adopted to reduce the problem into a linear bilevel integer programming problem. The individual optimal value of the objective of each DM is found in isolation to construct the fuzzy membership goals. Finally, fuzzy goal programming approach is used to achieve maximum degree of each of the membership goals by minimizing under deviational variables in the decision making environment. To demonstrate the efficiency of the proposed approach, a numerical example is provided.

LINEAR2007, Linear-Linear Interpolation of ENDF Format Cross-Sections

International Nuclear Information System (INIS)

2007-01-01

1 - Description of program or function: LINEAR converts evaluated cross sections in the ENDF/B format into a tabular form that is subject to linear-linear interpolation in energy and cross section. The code also thins tables of cross sections already in that form. Codes used subsequently need thus to consider only linear-linear data. IAEA1311/15: This version include the updates up to January 30, 2007. Changes in ENDF/B-VII Format and procedures, as well as the evaluations themselves, make it impossible for versions of the ENDF/B pre-processing codes earlier than PREPRO 2007 (2007 Version) to accurately process current ENDF/B-VII evaluations. The present code can handle all existing ENDF/B-VI evaluations through release 8, which will be the last release of ENDF/B-VI. Modifications from previous versions: - Linear VERS. 2007-1 (JAN. 2007): checked against all ENDF/B-VII; increased page size from 60,000 to 600,000 points 2 - Method of solution: Each section of data is considered separately. Each section of File 3, 23, and 27 data consists of a table of cross section versus energy with any of five interpolation laws. LINEAR will replace each section with a new table of energy versus cross section data in which the interpolation law is always linear in energy and cross section. The histogram (constant cross section between two energies) interpolation law is converted to linear-linear by substituting two points for each initial point. The linear-linear is not altered. For the log-linear, linear-log and log- log laws, the cross section data are converted to linear by an interval halving algorithm. Each interval is divided in half until the value at the middle of the interval can be approximated by linear-linear interpolation to within a given accuracy. The LINEAR program uses a multipoint fractional error thinning algorithm to minimize the size of each cross section table

Secret Message Decryption: Group Consulting Projects Using Matrices and Linear Programming

Science.gov (United States)

Gurski, Katharine F.

2009-01-01

We describe two short group projects for finite mathematics students that incorporate matrices and linear programming into fictional consulting requests presented as a letter to the students. The students are required to use mathematics to decrypt secret messages in one project involving matrix multiplication and inversion. The second project…

Optimal local dimming for LED-backlit LCD displays via linear programming

DEFF Research Database (Denmark)

Shu, Xiao; Wu, Xiaolin; Forchhammer, Søren

2012-01-01

and the attenuations of LCD pixels. The objective is to minimize the distortion in luminance reproduction due to the leakage of LCD and the coarse granularity of the LED lights. The optimization problem is formulated as one of linear programming, and both exact and approximate algorithms are proposed. Simulation...

Optimization of production planning in Czech agricultural co-operative via linear programming

Directory of Open Access Journals (Sweden)

Jitka Janová

2009-01-01

Full Text Available The production planning is one of the key managerial decisions in agricultural business, which must be done periodically every year. Correct decision must cover the agriculture demands of planting the crops such as crop rotation restrictions or water resource scarcity, while the decision maker aims to plan the crop design in most profitable way in sense of maximizing the total profit from the crop yield. This decision problem represents the optimization of crop design and can be treated by the me­thods of linear programming which begun to be extensively used in agriculture production planning in USA during 50’s. There is ongoing research of mathematical programming applications in agriculture worldwide, but the results are not easily transferable to other localities due to the specific local restrictions in each country. In Czech Republic the farmers use for production planning mainly their expert knowledge and past experience. However, the mathematical programming approach enables find the true optimal solution of the problem, which especially in the problems with a great number of constraints is not easy to find intuitively. One of the possible barriers for using the general decision support systems (which are based on mathematical programming methods for agriculture production planning in Czech Republic is its expensiveness. The small farmer can not afford to buy the expensive software or to employ a mathematical programming specialist. The aim of this paper is to present a user friendly linear programming model of the typical agricultural production planning problem in Czech Republic which can be solved via software tools commonly available in any farm (e.g. EXCEL. The linear programming model covering the restrictions on total costs, crop rotation, thresholds for the total area sowed by particular crops, total amount of manure and the need of feed crops is developed. The model is applied in real-world problem of Czech agriculture

The Linear Programming to evaluate the performance of Oral Health in Primary Care.

Science.gov (United States)

Colussi, Claudia Flemming; Calvo, Maria Cristina Marino; Freitas, Sergio Fernando Torres de

2013-01-01

To show the use of Linear Programming to evaluate the performance of Oral Health in Primary Care. This study used data from 19 municipalities of Santa Catarina city that participated of the state evaluation in 2009 and have more than 50,000 habitants. A total of 40 indicators were evaluated, calculated using the Microsoft Excel 2007, and converted to the interval [0, 1] in ascending order (one indicating the best situation and zero indicating the worst situation). Applying the Linear Programming technique municipalities were assessed and compared among them according to performance curve named "quality estimated frontier". Municipalities included in the frontier were classified as excellent. Indicators were gathered, and became synthetic indicators. The majority of municipalities not included in the quality frontier (values different of 1.0) had lower values than 0.5, indicating poor performance. The model applied to the municipalities of Santa Catarina city assessed municipal management and local priorities rather than the goals imposed by pre-defined parameters. In the final analysis three municipalities were included in the "perceived quality frontier". The Linear Programming technique allowed to identify gaps that must be addressed by city managers to enhance actions taken. It also enabled to observe each municipal performance and compare results among similar municipalities.

AN APPLICATION FOR EFFICIENT TELECOMMUNICATION NETWORKS PROVISIONING USING LINEAR PROGRAMMING

Directory of Open Access Journals (Sweden)

Maria Augusta Soares Machado

2015-03-01

Full Text Available This paper presents a practical proposition for the application of the Linear Programming quantitative method in order to assist planning and control of customer circuit delivery activities in telecommunications companies working with the corporative market. Based upon data provided for by a telecom company operating in Brazil, the Linear Programming method was employed for one of the classical problems of determining the optimum mix of production quantities for a set of five products of that company: Private Telephone Network, Internet Network, Intranet Network, Low Speed Data Network, and High Speed Data Network, in face of several limitations of the productive resources, seeking to maximize the company’s monthly revenue. By fitting the production data available into a primary model, observation was made as to what number of monthly activations for each product would be mostly optimized in order to achieve maximum revenues in the company. The final delivery of a complete network was not observed but the delivery of the circuits that make it up, and this was a limiting factor for the study herein, which, however, brings an innovative proposition for the planning of private telecommunications network provisioning.

A Study of Joint Cost Inclusion in Linear Programming Optimization

Directory of Open Access Journals (Sweden)

P. Armaos

2013-08-01

Full Text Available The concept of Structural Optimization has been a topic or research over the past century. Linear Programming Optimization has proved being the most reliable method of structural optimization. Global advances in linear programming optimization have been recently powered by University of Sheffield researchers, to include joint cost, self-weight and buckling considerations. A joint cost inclusion scopes to reduce the number of joints existing in an optimized structural solution, transforming it to a practically viable solution. The topic of the current paper is to investigate the effects of joint cost inclusion, as this is currently implemented in the optimization code. An extended literature review on this subject was conducted prior to familiarization with small scale optimization software. Using IntelliFORM software, a structured series of problems were set and analyzed. The joint cost tests examined benchmark problems and their consequent changes in the member topology, as the design domain was expanding. The findings of the analyses were remarkable and are being commented further on. The distinct topologies of solutions created by optimization processes are also recognized. Finally an alternative strategy of penalizing joints is presented.

Solving non-linear Horn clauses using a linear Horn clause solver

DEFF Research Database (Denmark)

Kafle, Bishoksan; Gallagher, John Patrick; Ganty, Pierre

2016-01-01

In this paper we show that checking satisfiability of a set of non-linear Horn clauses (also called a non-linear Horn clause program) can be achieved using a solver for linear Horn clauses. We achieve this by interleaving a program transformation with a satisfiability checker for linear Horn...... clauses (also called a solver for linear Horn clauses). The program transformation is based on the notion of tree dimension, which we apply to a set of non-linear clauses, yielding a set whose derivation trees have bounded dimension. Such a set of clauses can be linearised. The main algorithm...... dimension. We constructed a prototype implementation of this approach and performed some experiments on a set of verification problems, which shows some promise....

Visual, Algebraic and Mixed Strategies in Visually Presented Linear Programming Problems.

Science.gov (United States)

Shama, Gilli; Dreyfus, Tommy

1994-01-01

Identified and classified solution strategies of (n=49) 10th-grade students who were presented with linear programming problems in a predominantly visual setting in the form of a computerized game. Visual strategies were developed more frequently than either algebraic or mixed strategies. Appendix includes questionnaires. (Contains 11 references.)…

Fuzzy Multi Objective Linear Programming Problem with Imprecise Aspiration Level and Parameters

Directory of Open Access Journals (Sweden)

Zahra Shahraki

2015-07-01

Full Text Available This paper considers the multi-objective linear programming problems with fuzzygoal for each of the objective functions and constraints. Most existing works deal withlinear membership functions for fuzzy goals. In this paper, exponential membershipfunction is used.

Broadband demonstrations of true-time delay using linear sideband chirped programming and optical coherent transients

International Nuclear Information System (INIS)

Reibel, R.R.; Barber, Z.W.; Fischer, J.A.; Tian, M.; Babbitt, W.R.

2004-01-01

Linear sideband chirped (LSC) programming is introduced as a means of configuring spatial-spectral holographic gratings for optical coherent transient processors. Similar to linear frequency chirped programming, LSC programming allows the use of broadband integrated electro-optic phase modulators to produce chirps instead of using elaborate broadband chirped lasers. This approach has several advantages including the ability to use a stabilized laser for the optical carrier as well as stable, reproducible chirped optical signals when the modulator is driven digitally. Using LSC programming, we experimentally demonstrate broadband true-time delay as a proof of principle for the optical control of phased array radars. Here both cw phase modulated and binary phase shift keyed probe signals are true-time delayed with bandwidths of 1 GHz and delay resolutions better than 60 ps

Linear programming models and methods of matrix games with payoffs of triangular fuzzy numbers

CERN Document Server

Li, Deng-Feng

2016-01-01

This book addresses two-person zero-sum finite games in which the payoffs in any situation are expressed with fuzzy numbers. The purpose of this book is to develop a suite of effective and efficient linear programming models and methods for solving matrix games with payoffs in fuzzy numbers. Divided into six chapters, it discusses the concepts of solutions of matrix games with payoffs of intervals, along with their linear programming models and methods. Furthermore, it is directly relevant to the research field of matrix games under uncertain economic management. The book offers a valuable resource for readers involved in theoretical research and practical applications from a range of different fields including game theory, operational research, management science, fuzzy mathematical programming, fuzzy mathematics, industrial engineering, business and social economics. .

A versatile program for the calculation of linear accelerator room shielding.

Science.gov (United States)

Hassan, Zeinab El-Taher; Farag, Nehad M; Elshemey, Wael M

2018-03-22

This work aims at designing a computer program to calculate the necessary amount of shielding for a given or proposed linear accelerator room design in radiotherapy. The program (Shield Calculation in Radiotherapy, SCR) has been developed using Microsoft Visual Basic. It applies the treatment room shielding calculations of NCRP report no. 151 to calculate proper shielding thicknesses for a given linear accelerator treatment room design. The program is composed of six main user-friendly interfaces. The first enables the user to upload their choice of treatment room design and to measure the distances required for shielding calculations. The second interface enables the user to calculate the primary barrier thickness in case of three-dimensional conventional radiotherapy (3D-CRT), intensity modulated radiotherapy (IMRT) and total body irradiation (TBI). The third interface calculates the required secondary barrier thickness due to both scattered and leakage radiation. The fourth and fifth interfaces provide a means to calculate the photon dose equivalent for low and high energy radiation, respectively, in door and maze areas. The sixth interface enables the user to calculate the skyshine radiation for photons and neutrons. The SCR program has been successfully validated, precisely reproducing all of the calculated examples presented in NCRP report no. 151 in a simple and fast manner. Moreover, it easily performed the same calculations for a test design that was also calculated manually, and produced the same results. The program includes a new and important feature that is the ability to calculate required treatment room thickness in case of IMRT and TBI. It is characterised by simplicity, precision, data saving, printing and retrieval, in addition to providing a means for uploading and testing any proposed treatment room shielding design. The SCR program provides comprehensive, simple, fast and accurate room shielding calculations in radiotherapy.

Wavelet-linear genetic programming: A new approach for modeling monthly streamflow

Science.gov (United States)

Ravansalar, Masoud; Rajaee, Taher; Kisi, Ozgur

2017-06-01

The streamflows are important and effective factors in stream ecosystems and its accurate prediction is an essential and important issue in water resources and environmental engineering systems. A hybrid wavelet-linear genetic programming (WLGP) model, which includes a discrete wavelet transform (DWT) and a linear genetic programming (LGP) to predict the monthly streamflow (Q) in two gauging stations, Pataveh and Shahmokhtar, on the Beshar River at the Yasuj, Iran were used in this study. In the proposed WLGP model, the wavelet analysis was linked to the LGP model where the original time series of streamflow were decomposed into the sub-time series comprising wavelet coefficients. The results were compared with the single LGP, artificial neural network (ANN), a hybrid wavelet-ANN (WANN) and Multi Linear Regression (MLR) models. The comparisons were done by some of the commonly utilized relevant physical statistics. The Nash coefficients (E) were found as 0.877 and 0.817 for the WLGP model, for the Pataveh and Shahmokhtar stations, respectively. The comparison of the results showed that the WLGP model could significantly increase the streamflow prediction accuracy in both stations. Since, the results demonstrate a closer approximation of the peak streamflow values by the WLGP model, this model could be utilized for the simulation of cumulative streamflow data prediction in one month ahead.

Development of demand functions and their inclusion in linear programming forecasting models

International Nuclear Information System (INIS)

Chamberlin, J.H.

1976-05-01

The purpose of the paper is to present a method for including demand directly within a linear programming model, and to use this method to analyze the effect of the Liquid Metal Fast Breeder Reactor upon the nuclear energy system

Proximal Humerus

NARCIS (Netherlands)

Diercks, Ron L.; Bain, Gregory; Itoi, Eiji; Di Giacomo, Giovanni; Sugaya, Hiroyuki

2015-01-01

This chapter describes the bony structures of the proximal humerus. The proximal humerus is often regarded as consisting of four parts, which assists in understanding function and, more specially, describes the essential parts in reconstruction after fracture or in joint replacement. These are the

The application of the fall-vector method in decomposition schemes for the solution of integer linear programming problems

International Nuclear Information System (INIS)

Sergienko, I.V.; Golodnikov, A.N.

1984-01-01

This article applies the methods of decompositions, which are used to solve continuous linear problems, to integer and partially integer problems. The fall-vector method is used to solve the obtained coordinate problems. An algorithm of the fall-vector is described. The Kornai-Liptak decomposition principle is used to reduce the integer linear programming problem to integer linear programming problems of a smaller dimension and to a discrete coordinate problem with simple constraints

Research and evaluation of the effectiveness of e-learning in the case of linear programming

Directory of Open Access Journals (Sweden)

Ljiljana Miletić

2016-04-01

Full Text Available The paper evaluates the effectiveness of the e-learning approach to linear programming. The goal was to investigate how proper use of information and communication technologies (ICT and interactive learning helps to improve high school students’ understanding, learning and retention of advanced non-curriculum material. The hypothesis was that ICT and e-learning is helpful in teaching linear programming methods. In the first phase of the research, a module of lessons for linear programming (LP was created using the software package Loomen Moodle and other interactive software packages such as Geogebra. In the second phase, the LP module was taught as a short course to two groups of high school students. These two groups of students were second-grade students in a Croatian high school. In Class 1, the module was taught using ICT and e-learning, while the module was taught using classical methods in Class 2. The action research methodology was an integral part in delivering the course to both student groups. The sample student groups were carefully selected to ensure that differences in background knowledge and learning potential were statistically negligible. Relevant data was collected while delivering the course. Statistical analysis of the collected data showed that the student group using the e-learning method produced better results than the group using a classical learning method. These findings support previous results on the effectiveness of e-learning, and also establish a specific approach to e-learning in linear programming.

Residential proximity to major roads and placenta/birth weight ratio.

Science.gov (United States)

Yorifuji, Takashi; Naruse, Hiroo; Kashima, Saori; Murakoshi, Takeshi; Tsuda, Toshihide; Doi, Hiroyuki; Kawachi, Ichiro

2012-01-01

Exposure to air pollution has been demonstrated to increase the risk of preterm birth and low birth weight. We examined whether proximity to major roads (as a marker of exposure to air pollution) is associated with increased placenta/birth weight ratio (as a biomarker of the placental transport function). Data on parental characteristics and birth outcomes were extracted from the database maintained by a major hospital in Shizuoka Prefecture, Japan. We restricted the analysis to mothers who delivered liveborn single births from 1997 to 2008 (n = 14,189). Using geocoded residential information, each birth was classified according to proximity to major roads. We examined the association between proximity to major roads and the placenta/birth weight ratio, using multiple linear regression. Proximity to major roads was associated with higher placenta/birth weight ratio. After adjusting for potential confounders, living within 200 m of a major road increased the ratio by 0.48% (95% CI = 0.15 to 0. 80). In addition, proximity to major roads was associated with lower placenta weight and birth weight. These observed associations were stronger among participants living closer to major roads. Exposure to traffic-related air pollution is associated with higher placenta/birth weight ratio. Impaired placental oxygen and nutrient transport function might be a mechanism for explaining the observed association between air pollution and low birth weight as well as preterm birth. Copyright © 2011 Elsevier B.V. All rights reserved.

Association Between Physical Activity and Proximity to Physical Activity Resources Among Low-Income, Midlife Women

OpenAIRE

Jilcott, Stephanie B; Evenson, Kelly R; Laraia, Barbara A; Ammerman, Alice S

2006-01-01

Introduction The association between levels of physical activity and perceived and objectively measured proximity to physical activity resources is unclear. Clarification is important so that future programs can intervene upon the measure with the greatest association. We examined correlations between perceived and objectively measured proximity to physical activity resources and then examined associations between both measures of proximity and objectively measured physical activity. Methods ...

LIAR -- A new program for the modeling and simulation of linear accelerators with high gradients and small emittances

International Nuclear Information System (INIS)

Assmann, R.; Adolphsen, C.; Bane, K.; Raubenheimer, T.O.; Siemann, R.; Thompson, K.

1996-09-01

Linear accelerators are the central components of the proposed next generation of linear colliders. They need to provide acceleration of up to 750 GeV per beam while maintaining very small normalized emittances. Standard simulation programs, mainly developed for storage rings, do not meet the specific requirements for high energy linear accelerators. The authors present a new program LIAR (LInear Accelerator Research code) that includes wakefield effects, a 4D coupled beam description, specific optimization algorithms and other advanced features. Its modular structure allows to use and to extend it easily for different purposes. They present examples of simulations for SLC and NLC

Optimization of radioactive waste management system by application of multiobjective linear programming

International Nuclear Information System (INIS)

Shimizu, Yoshiaki

1981-01-01

A mathematical procedure is proposed to make a radioactive waste management plan comprehensively. Since such planning is relevant to some different goals in management, decision making has to be formulated as a multiobjective optimization problem. A mathematical programming method was introduced to make a decision through an interactive manner which enables us to assess the preference of decision maker step by step among the conflicting objectives. The reference system taken as an example is the radioactive waste management system at the Research Reactor Institute of Kyoto University (KUR). Its linear model was built based on the experience in the actual management at KUR. The best-compromise model was then formulated as a multiobjective linear programming by the aid of the computational analysis through a conventional optimization. It was shown from the numerical results that the proposed approach could provide some useful informations to make an actual management plan. (author)

Mixed integer linear programming model for dynamic supplier selection problem considering discounts

Directory of Open Access Journals (Sweden)

Adi Wicaksono Purnawan

2018-01-01

Full Text Available Supplier selection is one of the most important elements in supply chain management. This function involves evaluation of many factors such as, material costs, transportation costs, quality, delays, supplier capacity, storage capacity and others. Each of these factors varies with time, therefore, supplier identified for one period is not necessarily be same for the next period to supply the same product. So, mixed integer linear programming (MILP was developed to overcome the dynamic supplier selection problem (DSSP. In this paper, a mixed integer linear programming model is built to solve the lot-sizing problem with multiple suppliers, multiple periods, multiple products and quantity discounts. The buyer has to make a decision for some products which will be supplied by some suppliers for some periods cosidering by discount. To validate the MILP model with randomly generated data. The model is solved by Lingo 16.

Refining and end use study of coal liquids II - linear programming analysis

Energy Technology Data Exchange (ETDEWEB)

Lowe, C.; Tam, S.

1995-12-31

A DOE-funded study is underway to determine the optimum refinery processing schemes for producing transportation fuels that will meet CAAA regulations from direct and indirect coal liquids. The study consists of three major parts: pilot plant testing of critical upgrading processes, linear programming analysis of different processing schemes, and engine emission testing of final products. Currently, fractions of a direct coal liquid produced form bituminous coal are being tested in sequence of pilot plant upgrading processes. This work is discussed in a separate paper. The linear programming model, which is the subject of this paper, has been completed for the petroleum refinery and is being modified to handle coal liquids based on the pilot plant test results. Preliminary coal liquid evaluation studies indicate that, if a refinery expansion scenario is adopted, then the marginal value of the coal liquid (over the base petroleum crude) is $3-4/bbl.

Mehar Methods for Fuzzy Optimal Solution and Sensitivity Analysis of Fuzzy Linear Programming with Symmetric Trapezoidal Fuzzy Numbers

Directory of Open Access Journals (Sweden)

Sukhpreet Kaur Sidhu

2014-01-01

Full Text Available The drawbacks of the existing methods to obtain the fuzzy optimal solution of such linear programming problems, in which coefficients of the constraints are represented by real numbers and all the other parameters as well as variables are represented by symmetric trapezoidal fuzzy numbers, are pointed out, and to resolve these drawbacks, a new method (named as Mehar method is proposed for the same linear programming problems. Also, with the help of proposed Mehar method, a new method, much easy as compared to the existing methods, is proposed to deal with the sensitivity analysis of the same type of linear programming problems.

Sub-regional linear programming models in land use analysis: a case study of the Neguev settlement, Costa Rica.

NARCIS (Netherlands)

Schipper, R.A.; Stoorvogel, J.J.; Jansen, D.M.

1995-01-01

The paper deals with linear programming as a tool for land use analysis at the sub-regional level. A linear programming model of a case study area, the Neguev settlement in the Atlantic zone of Costa Rica, is presented. The matrix of the model includes five submatrices each encompassing a different

Towards lexicographic multi-objective linear programming using grossone methodology

Science.gov (United States)

Cococcioni, Marco; Pappalardo, Massimo; Sergeyev, Yaroslav D.

2016-10-01

Lexicographic Multi-Objective Linear Programming (LMOLP) problems can be solved in two ways: preemptive and nonpreemptive. The preemptive approach requires the solution of a series of LP problems, with changing constraints (each time the next objective is added, a new constraint appears). The nonpreemptive approach is based on a scalarization of the multiple objectives into a single-objective linear function by a weighted combination of the given objectives. It requires the specification of a set of weights, which is not straightforward and can be time consuming. In this work we present both mathematical and software ingredients necessary to solve LMOLP problems using a recently introduced computational methodology (allowing one to work numerically with infinities and infinitesimals) based on the concept of grossone. The ultimate goal of such an attempt is an implementation of a simplex-like algorithm, able to solve the original LMOLP problem by solving only one single-objective problem and without the need to specify finite weights. The expected advantages are therefore obvious.

A Homogeneous and Self-Dual Interior-Point Linear Programming Algorithm for Economic Model Predictive Control

DEFF Research Database (Denmark)

Sokoler, Leo Emil; Frison, Gianluca; Skajaa, Anders

2015-01-01

We develop an efficient homogeneous and self-dual interior-point method (IPM) for the linear programs arising in economic model predictive control of constrained linear systems with linear objective functions. The algorithm is based on a Riccati iteration procedure, which is adapted to the linear...... system of equations solved in homogeneous and self-dual IPMs. Fast convergence is further achieved using a warm-start strategy. We implement the algorithm in MATLAB and C. Its performance is tested using a conceptual power management case study. Closed loop simulations show that 1) the proposed algorithm...

Topics in computational linear optimization

DEFF Research Database (Denmark)

Hultberg, Tim Helge

2000-01-01

Linear optimization has been an active area of research ever since the pioneering work of G. Dantzig more than 50 years ago. This research has produced a long sequence of practical as well as theoretical improvements of the solution techniques avilable for solving linear optimization problems...... of high quality solvers and the use of algebraic modelling systems to handle the communication between the modeller and the solver. This dissertation features four topics in computational linear optimization: A) automatic reformulation of mixed 0/1 linear programs, B) direct solution of sparse unsymmetric...... systems of linear equations, C) reduction of linear programs and D) integration of algebraic modelling of linear optimization problems in C++. Each of these topics is treated in a separate paper included in this dissertation. The efficiency of solving mixed 0-1 linear programs by linear programming based...

The effect of workload constraints in linear programming models for production planning

NARCIS (Netherlands)

Jansen, M.M.; Kok, de A.G.; Adan, I.J.B.F.

2011-01-01

Linear programming (LP) models for production planning incorporate a model of the manufacturing system that is necessarily deterministic. Although these deterministic models are the current state-of-the-art, it should be recognized that they are used in an environment that is inherently stochastic.

Visualizing measurement for 3D smooth density distributions by means of linear programming

International Nuclear Information System (INIS)

Tayama, Norio; Yang, Xue-dong

1994-01-01

This paper is concerned with a theoretical possibility of a new visualizing measurement method based on an optimum 3D reconstruction from a few selected projections. A theory of optimum 3D reconstruction by a linear programming is discussed, utilizing a few projections for sampled 3D smooth-density-distribution model which satisfies the condition of the 3D sampling theorem. First by use of the sampling theorem, it is shown that we can set up simultaneous simple equations which corresponds to the case of the parallel beams. Then we solve the simultaneous simple equations by means of linear programming algorithm, and we can get an optimum 3D density distribution images with minimum error in the reconstruction. The results of computer simulation with the algorithm are presented. (author)

A scalable parallel algorithm for multiple objective linear programs

Science.gov (United States)

Wiecek, Malgorzata M.; Zhang, Hong

1994-01-01

This paper presents an ADBASE-based parallel algorithm for solving multiple objective linear programs (MOLP's). Job balance, speedup and scalability are of primary interest in evaluating efficiency of the new algorithm. Implementation results on Intel iPSC/2 and Paragon multiprocessors show that the algorithm significantly speeds up the process of solving MOLP's, which is understood as generating all or some efficient extreme points and unbounded efficient edges. The algorithm gives specially good results for large and very large problems. Motivation and justification for solving such large MOLP's are also included.

IESIP - AN IMPROVED EXPLORATORY SEARCH TECHNIQUE FOR PURE INTEGER LINEAR PROGRAMMING PROBLEMS

Science.gov (United States)

Fogle, F. R.

1994-01-01

IESIP, an Improved Exploratory Search Technique for Pure Integer Linear Programming Problems, addresses the problem of optimizing an objective function of one or more variables subject to a set of confining functions or constraints by a method called discrete optimization or integer programming. Integer programming is based on a specific form of the general linear programming problem in which all variables in the objective function and all variables in the constraints are integers. While more difficult, integer programming is required for accuracy when modeling systems with small numbers of components such as the distribution of goods, machine scheduling, and production scheduling. IESIP establishes a new methodology for solving pure integer programming problems by utilizing a modified version of the univariate exploratory move developed by Robert Hooke and T.A. Jeeves. IESIP also takes some of its technique from the greedy procedure and the idea of unit neighborhoods. A rounding scheme uses the continuous solution found by traditional methods (simplex or other suitable technique) and creates a feasible integer starting point. The Hook and Jeeves exploratory search is modified to accommodate integers and constraints and is then employed to determine an optimal integer solution from the feasible starting solution. The user-friendly IESIP allows for rapid solution of problems up to 10 variables in size (limited by DOS allocation). Sample problems compare IESIP solutions with the traditional branch-and-bound approach. IESIP is written in Borland's TURBO Pascal for IBM PC series computers and compatibles running DOS. Source code and an executable are provided. The main memory requirement for execution is 25K. This program is available on a 5.25 inch 360K MS DOS format diskette. IESIP was developed in 1990. IBM is a trademark of International Business Machines. TURBO Pascal is registered by Borland International.

Multiobjective fuzzy stochastic linear programming problems with inexact probability distribution

Energy Technology Data Exchange (ETDEWEB)

Hamadameen, Abdulqader Othman [Optimization, Department of Mathematical Sciences, Faculty of Science, UTM (Malaysia); Zainuddin, Zaitul Marlizawati [Department of Mathematical Sciences, Faculty of Science, UTM (Malaysia)

2014-06-19

This study deals with multiobjective fuzzy stochastic linear programming problems with uncertainty probability distribution which are defined as fuzzy assertions by ambiguous experts. The problem formulation has been presented and the two solutions strategies are; the fuzzy transformation via ranking function and the stochastic transformation when α{sup –}. cut technique and linguistic hedges are used in the uncertainty probability distribution. The development of Sen’s method is employed to find a compromise solution, supported by illustrative numerical example.

Theory of the superconducting proximity effect below the transition temperature

International Nuclear Information System (INIS)

Silvert, W.

1975-01-01

The form of the low-temperature theory of the superconducting proximity effect depends on whether the non-linear terms are assumed to depend only on the local value of the gap or on its average value over some finite range. The local assumption leads to smaller values of the gap and to unphysical results at low temperatures. The effect of non-locality is significant even in the Ginsburg-Landau regime. (author)

Politics, proximity and the pipeline: Mapping public attitudes toward Keystone XL

International Nuclear Information System (INIS)

Gravelle, Timothy B.; Lachapelle, Erick

2015-01-01

The politics of oil pipelines have become increasingly salient in American politics in recent years. In particular, debates about economic benefits, energy security and environmental impact have been provoked by the proposed Keystone XL pipeline expansion intended to take bitumen from northern Alberta in Canada to refineries on the Gulf Coast in Texas. Drawing on data from recent surveys conducted by the Pew Research Center, this article asks a series of questions. What levels of support for (and opposition to) the pipeline exist among the American public? What are the roles of political factors (such as party identification and ideology), economic attitudes, environmental attitudes and proximity to the proposed pipeline route in shaping attitudes toward the pipeline? And how do political factors and proximity to the pipeline interact? We find that partisanship and ideology drive attitudes toward the Keystone XL pipeline, and that the effect of ideology is attenuated by proximity to the proposed route. The policy implications of these findings for energy infrastructure siting controversies are discussed. -- Highlights: •Americans are divided on the Keystone XL energy pipeline. •Attitudes toward Keystone XL are driven by political party identification and ideology. •Attitudes toward the pipeline are also shaped by attitudes toward the economy and global warming. •The effect of proximity on attitudes toward Keystone XL is non-linear. •Spatial proximity to the pipeline attenuates the effect of ideology

Chromosome structures: reduction of certain problems with unequal gene content and gene paralogs to integer linear programming.

Science.gov (United States)

Lyubetsky, Vassily; Gershgorin, Roman; Gorbunov, Konstantin

2017-12-06

Chromosome structure is a very limited model of the genome including the information about its chromosomes such as their linear or circular organization, the order of genes on them, and the DNA strand encoding a gene. Gene lengths, nucleotide composition, and intergenic regions are ignored. Although highly incomplete, such structure can be used in many cases, e.g., to reconstruct phylogeny and evolutionary events, to identify gene synteny, regulatory elements and promoters (considering highly conserved elements), etc. Three problems are considered; all assume unequal gene content and the presence of gene paralogs. The distance problem is to determine the minimum number of operations required to transform one chromosome structure into another and the corresponding transformation itself including the identification of paralogs in two structures. We use the DCJ model which is one of the most studied combinatorial rearrangement models. Double-, sesqui-, and single-operations as well as deletion and insertion of a chromosome region are considered in the model; the single ones comprise cut and join. In the reconstruction problem, a phylogenetic tree with chromosome structures in the leaves is given. It is necessary to assign the structures to inner nodes of the tree to minimize the sum of distances between terminal structures of each edge and to identify the mutual paralogs in a fairly large set of structures. A linear algorithm is known for the distance problem without paralogs, while the presence of paralogs makes it NP-hard. If paralogs are allowed but the insertion and deletion operations are missing (and special constraints are imposed), the reduction of the distance problem to integer linear programming is known. Apparently, the reconstruction problem is NP-hard even in the absence of paralogs. The problem of contigs is to find the optimal arrangements for each given set of contigs, which also includes the mutual identification of paralogs. We proved that these

Optimization of refinery product blending by using linear programming

International Nuclear Information System (INIS)

Ristikj, Julija; Tripcheva-Trajkovska, Loreta; Rikaloski, Ice; Markovska, Liljana

1999-01-01

The product slate of a simple refinery consists mainly of liquefied petroleum gas, leaded and unleaded gasoline, jet fuel, diesel fuel, extra light heating oil and fuel oil. The quality of the oil products (fuels) for sale has to comply with the adopted standards for liquid fuels, and the produced quantities have to be comply with the market needs. The oil products are manufactured by blending two or more different fractions which quantities and physical-chemical properties depend on the crude oil type, the way and conditions of processing, and at the same time the fractions are used to blend one or more products. It is in producer's interest to do the blending in an optimal way, namely, to satisfy the requirements for the oil products quality and quantity with a maximal usage of the available fractions and, of course, with a maximal profit out of the sold products. This could be accomplished by applying linear programming, that is by using a linear model for oil products blending optimization. (Author)

How to Use Linear Programming for Information System Performances Optimization

Directory of Open Access Journals (Sweden)

Hell Marko

2014-09-01

Full Text Available Background: Organisations nowadays operate in a very dynamic environment, and therefore, their ability of continuously adjusting the strategic plan to the new conditions is a must for achieving their strategic objectives. BSC is a well-known methodology for measuring performances enabling organizations to learn how well they are doing. In this paper, “BSC for IS” will be proposed in order to measure the IS impact on the achievement of organizations’ business goals. Objectives: The objective of this paper is to present the original procedure which is used to enhance the BSC methodology in planning the optimal targets of IS performances value in order to maximize the organization's effectiveness. Methods/Approach: The method used in this paper is the quantitative methodology - linear programming. In the case study, linear programming is used for optimizing organization’s strategic performance. Results: Results are shown on the example of a case study national park. An optimal performance value for the strategic objective has been calculated, as well as an optimal performance value for each DO (derived objective. Results are calculated in Excel, using Solver Add-in. Conclusions: The presentation of methodology through the case study of a national park shows that this methodology, though it requires a high level of formalisation, provides a very transparent performance calculation.

Fault detection and initial state verification by linear programming for a class of Petri nets

Science.gov (United States)

Rachell, Traxon; Meyer, David G.

1992-01-01

The authors present an algorithmic approach to determining when the marking of a LSMG (live safe marked graph) or a LSFC (live safe free choice) net is in the set of live safe markings M. Hence, once the marking of a net is determined to be in M, then if at some time thereafter the marking of this net is determined not to be in M, this indicates a fault. It is shown how linear programming can be used to determine if m is an element of M. The worst-case computational complexity of each algorithm is bounded by the number of linear programs necessary to compute.

Optimal traffic control in highway transportation networks using linear programming

KAUST Repository

Li, Yanning

2014-06-01

This article presents a framework for the optimal control of boundary flows on transportation networks. The state of the system is modeled by a first order scalar conservation law (Lighthill-Whitham-Richards PDE). Based on an equivalent formulation of the Hamilton-Jacobi PDE, the problem of controlling the state of the system on a network link in a finite horizon can be posed as a Linear Program. Assuming all intersections in the network are controllable, we show that the optimization approach can be extended to an arbitrary transportation network, preserving linear constraints. Unlike previously investigated transportation network control schemes, this framework leverages the intrinsic properties of the Halmilton-Jacobi equation, and does not require any discretization or boolean variables on the link. Hence this framework is very computational efficient and provides the globally optimal solution. The feasibility of this framework is illustrated by an on-ramp metering control example.

Solving the Fully Fuzzy Bilevel Linear Programming Problem through Deviation Degree Measures and a Ranking Function Method

OpenAIRE

Aihong Ren

2016-01-01

This paper is concerned with a class of fully fuzzy bilevel linear programming problems where all the coefficients and decision variables of both objective functions and the constraints are fuzzy numbers. A new approach based on deviation degree measures and a ranking function method is proposed to solve these problems. We first introduce concepts of the feasible region and the fuzzy optimal solution of a fully fuzzy bilevel linear programming problem. In order to obtain a fuzzy optimal solut...

Meissner effect in clean proximity-contact N-S double layer

International Nuclear Information System (INIS)

Higashitani, S.; Nagai, K.

1994-01-01

The Meissner effect in proximity-contact normal-superconducting (N-S) double layers is discussed in the clean limit. We obtain the quasi-classical Green's function linear in the vector potential such that satisfies the boundary conditions at the layer ends and also at the N-S interface with a finite reflection coefficient R. We find that, when there is no pairing interaction in the normal layer, the diamagnetic current in the normal layer is constant in space, consequently the magnetic field decreases linearly in the normal layer. To compare our theory with experiments, we calculate the screening length and find a good agreement in the temperature dependence with the experiments in the Au-Nb system. (orig.)

Association between proximity to major roads and sputum cell counts

Science.gov (United States)

Wallace, Julie; D’silva, Liesel; Brannan, John; Hargreave, Frederick E; Kanaroglou, Pavlos; Nair, Parameswaran

2011-01-01

BACKGROUND: Air pollution caused by motor vehicle emissions has been associated with exacerbations of obstructive airway diseases; however, the nature of the resulting bronchitis has not been quantified. OBJECTIVE: To examine whether proximity to major roads or highways is associated with an increase in sputum neutrophils or eosinophils, and to evaluate the effect of proximity to roads on spirometry and exacerbations in patients with asthma. METHODS: A retrospective study of 485 sputum cell counts from patients attending a tertiary chest clinic in Hamilton, Ontario, identified eosinophilic or neutrophilic bronchitis. Patients’ residences were geocoded to the street network of Hamilton using geographic information system software. Associations among bronchitis, lung function, and proximity to major roads and highways were examined using multinomial logistic and multivariate linear regression analyses adjusted for patient age, smoking status and corticosteroid medications. RESULTS: Patients living within 1000 m of highways showed an increased risk of bronchitis (OR 3.8 [95% CI 1.0 to 13.7]; Proad were at increased risk for an asthma exacerbation (OR 1.9 [95% CI 1.5 to 15.5]; Proad was associated with neutrophilic bronchitis, an increased risk of asthma diagnosis, asthma exacerbations and lower lung function. PMID:21369545

A flexible dual-mode proximity sensor based on cooperative sensing for robot skin applications

Science.gov (United States)

Huang, Ying; Cai, Xia; Kan, Wenqing; Qiu, Shihua; Guo, Xiaohui; Liu, Caixia; Liu, Ping

2017-08-01

A flexible dual-mode proximity sensor has been designed and implemented, which is capable of combining capacitive-resistive detection in this paper. The capacitive type proximity sensor detecting is defined as mode-C, and the resistive type proximity sensor detecting is defined as mode-R. The characteristics of the proximity sensor are as follows: (1) the theoretical mode is developed which indicates that this proximity sensor can reflect proximity information accurately; (2) both sensing modes are vertically integrated into a sandwich-like chip with an 8 mm × 12 mm unit area. The thickness of a mode-R sensing material (graphene nanoplatelets) and mode-C dielectric (the mixture of carbon black and silicone rubber) is 1 mm and 2.5 mm, respectively; (3) for mode-R, the linearity of temperature-resistance curve can achieve 0.998 in the temperature range from 25°C to 65°C. And for mode-C, various materials can be successfully detected with fast response and high reversibility. Meanwhile, the study compensated the influence of object temperature to ensure mode-C properly works. A cooperative sensing test shows that R-C dual modes sense effectively which can enlarge the sensing distance compared with the single mode proximity sensor. The fabrication of this sensor is convenient, and the integrity of a flexible sandwich-like structure based on dual modes is beneficial to form arrays, which is suitable to be used in skin-like sensing applications.

Solving a class of generalized fractional programming problems using the feasibility of linear programs.

Science.gov (United States)

Shen, Peiping; Zhang, Tongli; Wang, Chunfeng

2017-01-01

This article presents a new approximation algorithm for globally solving a class of generalized fractional programming problems (P) whose objective functions are defined as an appropriate composition of ratios of affine functions. To solve this problem, the algorithm solves an equivalent optimization problem (Q) via an exploration of a suitably defined nonuniform grid. The main work of the algorithm involves checking the feasibility of linear programs associated with the interesting grid points. It is proved that the proposed algorithm is a fully polynomial time approximation scheme as the ratio terms are fixed in the objective function to problem (P), based on the computational complexity result. In contrast to existing results in literature, the algorithm does not require the assumptions on quasi-concavity or low-rank of the objective function to problem (P). Numerical results are given to illustrate the feasibility and effectiveness of the proposed algorithm.

A linear program for assessing the assignment and scheduling of radioactive wastes for disposal to sea

International Nuclear Information System (INIS)

Hutchinson, W.

1983-04-01

The report takes the form of a user guide to a computer program using linear programming techniques to aid the assignment and scheduling of radioactive wastes for disposal to sea. The program is aimed at the identification of 'optimum' amounts of each waste stream for disposal to sea without violating specific constraints values and/or fairness parameters. (author)

An Interval-Parameter Fuzzy Linear Programming with Stochastic Vertices Model for Water Resources Management under Uncertainty

Directory of Open Access Journals (Sweden)

Yan Han

2013-01-01

Full Text Available An interval-parameter fuzzy linear programming with stochastic vertices (IFLPSV method is developed for water resources management under uncertainty by coupling interval-parameter fuzzy linear programming (IFLP with stochastic programming (SP. As an extension of existing interval parameter fuzzy linear programming, the developed IFLPSV approach has advantages in dealing with dual uncertainty optimization problems, which uncertainty presents as interval parameter with stochastic vertices in both of the objective functions and constraints. The developed IFLPSV method improves upon the IFLP method by allowing dual uncertainty parameters to be incorporated into the optimization processes. A hybrid intelligent algorithm based on genetic algorithm and artificial neural network is used to solve the developed model. The developed method is then applied to water resources allocation in Beijing city of China in 2020, where water resources shortage is a challenging issue. The results indicate that reasonable solutions have been obtained, which are helpful and useful for decision makers. Although the amount of water supply from Guanting and Miyun reservoirs is declining with rainfall reduction, water supply from the South-to-North Water Transfer project will have important impact on water supply structure of Beijing city, particularly in dry year and extraordinary dry year.

A Unique Technique to get Kaprekar Iteration in Linear Programming Problem

Science.gov (United States)

Sumathi, P.; Preethy, V.

2018-04-01

This paper explores about a frivolous number popularly known as Kaprekar constant and Kaprekar numbers. A large number of courses and the different classroom capacities with difference in study periods make the assignment between classrooms and courses complicated. An approach of getting the minimum value of number of iterations to reach the Kaprekar constant for four digit numbers and maximum value is also obtained through linear programming techniques.

LPmerge: an R package for merging genetic maps by linear programming.

Science.gov (United States)

Endelman, Jeffrey B; Plomion, Christophe

2014-06-01

Consensus genetic maps constructed from multiple populations are an important resource for both basic and applied research, including genome-wide association analysis, genome sequence assembly and studies of evolution. The LPmerge software uses linear programming to efficiently minimize the mean absolute error between the consensus map and the linkage maps from each population. This minimization is performed subject to linear inequality constraints that ensure the ordering of the markers in the linkage maps is preserved. When marker order is inconsistent between linkage maps, a minimum set of ordinal constraints is deleted to resolve the conflicts. LPmerge is on CRAN at http://cran.r-project.org/web/packages/LPmerge. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

The MARX Modulator Development Program for the International Linear Collider

International Nuclear Information System (INIS)

Leyh, G.E.

2006-01-01

The International Linear Collider (ILC) Marx Modulator Development Program at SLAC is working towards developing a full-scale ILC Marx ''Reference Design'' modulator prototype, with the goal of significantly reducing the size and cost of the ILC modulator while improving overall modulator efficiency and availability. The ILC Reference Design prototype will provide a proof-of-concept model to industry in advance of Phase II SBIR funding, and also allow operation of the new 10MW L-Band Klystron prototypes immediately upon their arrival at SLAC

Marginal cost of electricity conservation: an application of linear program

International Nuclear Information System (INIS)

Silveira, A.M. da; Hollanda, J.B. de

1987-01-01

This paper is addressed ti the planning of electricity industry when the use of energetically efficient appliances (conservation) is financed by the utilities. It is based on the Linear Programming Model proposed by Masse and Boiteaux for planning of conventional energy sources, where one unity of electricity (Kw/Kw h) saved is treated as if it were a generator of equivalent size. In spite of the formal simplicity of the models it can support interesting concessions on the subject of a electrical energy conservation policy. (author)

Life cycle cost optimization of biofuel supply chains under uncertainties based on interval linear programming.

Science.gov (United States)

Ren, Jingzheng; Dong, Liang; Sun, Lu; Goodsite, Michael Evan; Tan, Shiyu; Dong, Lichun

2015-01-01

The aim of this work was to develop a model for optimizing the life cycle cost of biofuel supply chain under uncertainties. Multiple agriculture zones, multiple transportation modes for the transport of grain and biofuel, multiple biofuel plants, and multiple market centers were considered in this model, and the price of the resources, the yield of grain and the market demands were regarded as interval numbers instead of constants. An interval linear programming was developed, and a method for solving interval linear programming was presented. An illustrative case was studied by the proposed model, and the results showed that the proposed model is feasible for designing biofuel supply chain under uncertainties. Copyright © 2015 Elsevier Ltd. All rights reserved.

A primal-dual exterior point algorithm for linear programming problems

Directory of Open Access Journals (Sweden)

Samaras Nikolaos

2009-01-01

Full Text Available The aim of this paper is to present a new simplex type algorithm for the Linear Programming Problem. The Primal - Dual method is a Simplex - type pivoting algorithm that generates two paths in order to converge to the optimal solution. The first path is primal feasible while the second one is dual feasible for the original problem. Specifically, we use a three-phase-implementation. The first two phases construct the required primal and dual feasible solutions, using the Primal Simplex algorithm. Finally, in the third phase the Primal - Dual algorithm is applied. Moreover, a computational study has been carried out, using randomly generated sparse optimal linear problems, to compare its computational efficiency with the Primal Simplex algorithm and also with MATLAB's Interior Point Method implementation. The algorithm appears to be very promising since it clearly shows its superiority to the Primal Simplex algorithm as well as its robustness over the IPM algorithm.

Portfolio selection problem: a comparison of fuzzy goal programming and linear physical programming

Directory of Open Access Journals (Sweden)

Fusun Kucukbay

2016-04-01

Full Text Available Investors have limited budget and they try to maximize their return with minimum risk. Therefore this study aims to deal with the portfolio selection problem. In the study two criteria are considered which are expected return, and risk. In this respect, linear physical programming (LPP technique is applied on Bist 100 stocks to be able to find out the optimum portfolio. The analysis covers the period April 2009- March 2015. This period is divided into two; April 2009-March 2014 and April 2014 – March 2015. April 2009-March 2014 period is used as data to find an optimal solution. April 2014-March 2015 period is used to test the real performance of portfolios. The performance of the obtained portfolio is compared with that obtained from fuzzy goal programming (FGP. Then the performances of both method, LPP and FGP are compared with BIST 100 in terms of their Sharpe Indexes. The findings reveal that LPP for portfolio selection problem is a good alternative to FGP.

Optimal placement of capacitors in a radial network using conic and mixed integer linear programming

Energy Technology Data Exchange (ETDEWEB)

Jabr, R.A. [Electrical, Computer and Communication Engineering Department, Notre Dame University, P.O. Box: 72, Zouk Mikhael, Zouk Mosbeh (Lebanon)

2008-06-15

This paper considers the problem of optimally placing fixed and switched type capacitors in a radial distribution network. The aim of this problem is to minimize the costs associated with capacitor banks, peak power, and energy losses whilst satisfying a pre-specified set of physical and technical constraints. The proposed solution is obtained using a two-phase approach. In phase-I, the problem is formulated as a conic program in which all nodes are candidates for placement of capacitor banks whose sizes are considered as continuous variables. A global solution of the phase-I problem is obtained using an interior-point based conic programming solver. Phase-II seeks a practical optimal solution by considering capacitor sizes as discrete variables. The problem in this phase is formulated as a mixed integer linear program based on minimizing the L1-norm of deviations from the phase-I state variable values. The solution to the phase-II problem is obtained using a mixed integer linear programming solver. The proposed method is validated via extensive comparisons with previously published results. (author)

Fuzzy chance constrained linear programming model for scrap charge optimization in steel production

DEFF Research Database (Denmark)

Rong, Aiying; Lahdelma, Risto

2008-01-01

the uncertainty based on fuzzy set theory and constrain the failure risk based on a possibility measure. Consequently, the scrap charge optimization problem is modeled as a fuzzy chance constrained linear programming problem. Since the constraints of the model mainly address the specification of the product...

A new neural network model for solving random interval linear programming problems.

Science.gov (United States)

Arjmandzadeh, Ziba; Safi, Mohammadreza; Nazemi, Alireza

2017-05-01

This paper presents a neural network model for solving random interval linear programming problems. The original problem involving random interval variable coefficients is first transformed into an equivalent convex second order cone programming problem. A neural network model is then constructed for solving the obtained convex second order cone problem. Employing Lyapunov function approach, it is also shown that the proposed neural network model is stable in the sense of Lyapunov and it is globally convergent to an exact satisfactory solution of the original problem. Several illustrative examples are solved in support of this technique. Copyright © 2017 Elsevier Ltd. All rights reserved.

Solving the Fully Fuzzy Bilevel Linear Programming Problem through Deviation Degree Measures and a Ranking Function Method

Directory of Open Access Journals (Sweden)

Aihong Ren

2016-01-01

Full Text Available This paper is concerned with a class of fully fuzzy bilevel linear programming problems where all the coefficients and decision variables of both objective functions and the constraints are fuzzy numbers. A new approach based on deviation degree measures and a ranking function method is proposed to solve these problems. We first introduce concepts of the feasible region and the fuzzy optimal solution of a fully fuzzy bilevel linear programming problem. In order to obtain a fuzzy optimal solution of the problem, we apply deviation degree measures to deal with the fuzzy constraints and use a ranking function method of fuzzy numbers to rank the upper and lower level fuzzy objective functions. Then the fully fuzzy bilevel linear programming problem can be transformed into a deterministic bilevel programming problem. Considering the overall balance between improving objective function values and decreasing allowed deviation degrees, the computational procedure for finding a fuzzy optimal solution is proposed. Finally, a numerical example is provided to illustrate the proposed approach. The results indicate that the proposed approach gives a better optimal solution in comparison with the existing method.

Computed-tomographic and conventional linear-tomographic evaluation of tracheobronchial lesions for laser photoresection

International Nuclear Information System (INIS)

Pearlberg, J.L.; Sandler, M.A.; Kvale, P.; Beute, G.H.; Madrazo, B.L.

1985-01-01

Laser therapy is a new modality for treatment of airway lesions. The authors examined 18 patients prior to laser photoresection of tracheobronchial lesions. Thirteen had cancers involving the distal trachea, carina, and/or proximal bronchi; five had benign lesions of the middle or proximal trachea. Each patient was examined by conventional linear tomography (CLT) and computed tomography (CT). CT was valuable in patients who had lesions of the distal trachea, carina, and/or proximal bronchi. Its particular usefulness, and its advantage relative to CLT, consisted in its ability to delineate vascular structures adjacent to the planned area of photoresection. Neither CLT nor CT was helpful in evaluation of benign lesions of the proximal trachea

A penalization approach to linear programming duality with application to capacity constrained transport

OpenAIRE

Korman, Jonathan; McCann, Robert J.; Seis, Christian

2013-01-01

A new approach to linear programming duality is proposed which relies on quadratic penalization, so that the relation between solutions to the penalized primal and dual problems becomes affine. This yields a new proof of Levin's duality theorem for capacity-constrained optimal transport as an infinite-dimensional application.

An Interactive Method to Solve Infeasibility in Linear Programming Test Assembling Models

Science.gov (United States)

Huitzing, Hiddo A.

2004-01-01

In optimal assembly of tests from item banks, linear programming (LP) models have proved to be very useful. Assembly by hand has become nearly impossible, but these LP techniques are able to find the best solutions, given the demands and needs of the test to be assembled and the specifics of the item bank from which it is assembled. However,…

Optimal blood glucose control in diabetes mellitus treatment using dynamic programming based on Ackerman’s linear model

Science.gov (United States)

Pradanti, Paskalia; Hartono

2018-03-01

Determination of insulin injection dose in diabetes mellitus treatment can be considered as an optimal control problem. This article is aimed to simulate optimal blood glucose control for patient with diabetes mellitus. The blood glucose regulation of diabetic patient is represented by Ackerman’s Linear Model. This problem is then solved using dynamic programming method. The desired blood glucose level is obtained by minimizing the performance index in Lagrange form. The results show that dynamic programming based on Ackerman’s Linear Model is quite good to solve the problem.

GASPACHO: a generic automatic solver using proximal algorithms for convex huge optimization problems

Science.gov (United States)

Goossens, Bart; Luong, Hiêp; Philips, Wilfried

2017-08-01

Many inverse problems (e.g., demosaicking, deblurring, denoising, image fusion, HDR synthesis) share various similarities: degradation operators are often modeled by a specific data fitting function while image prior knowledge (e.g., sparsity) is incorporated by additional regularization terms. In this paper, we investigate automatic algorithmic techniques for evaluating proximal operators. These algorithmic techniques also enable efficient calculation of adjoints from linear operators in a general matrix-free setting. In particular, we study the simultaneous-direction method of multipliers (SDMM) and the parallel proximal algorithm (PPXA) solvers and show that the automatically derived implementations are well suited for both single-GPU and multi-GPU processing. We demonstrate this approach for an Electron Microscopy (EM) deconvolution problem.

A comparison between linear and non-linear analysis of flexible pavements

Energy Technology Data Exchange (ETDEWEB)

Soleymani, H.R.; Berthelot, C.F.; Bergan, A.T. [Saskatchewan Univ., Saskatoon, SK (Canada). Dept. of Mechanical Engineering

1995-12-31

Computer pavement analysis programs, which are based on mathematical simulation models, were compared. The programs included in the study were: ELSYM5, an Elastic Linear (EL) pavement analysis program, MICH-PAVE, a Finite Element Non-Linear (FENL) and Finite Element Linear (FEL) pavement analysis program. To perform the analysis different tire pressures, pavement material properties and asphalt layer thicknesses were selected. Evaluation criteria used in the analysis were tensile strain in bottom of the asphalt layer, vertical compressive strain at the top of the subgrade and surface displacement. Results showed that FENL methods predicted more strain and surface deflection than the FEL and EL analysis methods. Analyzing pavements with FEL does not offer many advantages over the EL method. Differences in predicted strains between the three methods of analysis in some cases was found to be close to 100% It was suggested that these programs require more calibration and validation both theoretically and empirically to accurately correlate with field observations. 19 refs., 4 tabs., 9 figs.

A novel approach based on preference-based index for interval bilevel linear programming problem

OpenAIRE

Aihong Ren; Yuping Wang; Xingsi Xue

2017-01-01

This paper proposes a new methodology for solving the interval bilevel linear programming problem in which all coefficients of both objective functions and constraints are considered as interval numbers. In order to keep as much uncertainty of the original constraint region as possible, the original problem is first converted into an interval bilevel programming problem with interval coefficients in both objective functions only through normal variation of interval number and chance-constrain...

Proximity credentials: A survey

International Nuclear Information System (INIS)

Wright, L.J.

1987-04-01

Credentials as a means of identifying individuals have traditionally been a photo badge and more recently, the coded credential. Another type of badge, the proximity credential, is making inroads in the personnel identification field. This badge can be read from a distance instead of being veiewed by a guard or inserted into a reading device. This report reviews proximity credentials, identifies the companies marketing or developing proximity credentials, and describes their respective credentials. 3 tabs

Many-body localization proximity effects in platforms of coupled spins and bosons

Science.gov (United States)

Marino, J.; Nandkishore, R. M.

2018-02-01

We discuss the onset of many-body localization in a one-dimensional system composed of a XXZ quantum spin chain and a Bose-Hubbard model linearly coupled together. We consider two complementary setups, depending whether spatial disorder is initially imprinted on spins or on bosons; in both cases, we explore the conditions for the disordered portion of the system to localize by proximity of the other clean half. Assuming that the dynamics of one of the two parts develops on shorter time scales than the other, we can adiabatically eliminate the fast degrees of freedom, and derive an effective Hamiltonian for the system's remainder using projection operator techniques. Performing a locator expansion on the strength of the many-body interaction term or on the hopping amplitude of the effective Hamiltonian thus derived, we present results on the stability of the many-body localized phases induced by proximity effect. We also briefly comment on the feasibility of the proposed model through modern quantum optics architectures, with the long-term perspective to realize experimentally, in composite open systems, Anderson or many-body localization proximity effects.

Averaging and Linear Programming in Some Singularly Perturbed Problems of Optimal Control

Energy Technology Data Exchange (ETDEWEB)

Gaitsgory, Vladimir, E-mail: vladimir.gaitsgory@mq.edu.au [Macquarie University, Department of Mathematics (Australia); Rossomakhine, Sergey, E-mail: serguei.rossomakhine@flinders.edu.au [Flinders University, Flinders Mathematical Sciences Laboratory, School of Computer Science, Engineering and Mathematics (Australia)

2015-04-15

The paper aims at the development of an apparatus for analysis and construction of near optimal solutions of singularly perturbed (SP) optimal controls problems (that is, problems of optimal control of SP systems) considered on the infinite time horizon. We mostly focus on problems with time discounting criteria but a possibility of the extension of results to periodic optimization problems is discussed as well. Our consideration is based on earlier results on averaging of SP control systems and on linear programming formulations of optimal control problems. The idea that we exploit is to first asymptotically approximate a given problem of optimal control of the SP system by a certain averaged optimal control problem, then reformulate this averaged problem as an infinite-dimensional linear programming (LP) problem, and then approximate the latter by semi-infinite LP problems. We show that the optimal solution of these semi-infinite LP problems and their duals (that can be found with the help of a modification of an available LP software) allow one to construct near optimal controls of the SP system. We demonstrate the construction with two numerical examples.

Linear programming phase unwrapping for dual-wavelength digital holography.

Science.gov (United States)

Wang, Zhaomin; Jiao, Jiannan; Qu, Weijuan; Yang, Fang; Li, Hongru; Tian, Ailing; Asundi, Anand

2017-01-20

A linear programming phase unwrapping method in dual-wavelength digital holography is proposed and verified experimentally. The proposed method uses the square of height difference as a convergence standard and theoretically gives the boundary condition in a searching process. A simulation was performed by unwrapping step structures at different levels of Gaussian noise. As a result, our method is capable of recovering the discontinuities accurately. It is robust and straightforward. In the experiment, a microelectromechanical systems sample and a cylindrical lens were measured separately. The testing results were in good agreement with true values. Moreover, the proposed method is applicable not only in digital holography but also in other dual-wavelength interferometric techniques.

Interacting effects of uniform flow, plane shear, and near-wall proximity on the heat and mass transfer of respiratory aerosols

Energy Technology Data Exchange (ETDEWEB)

Worth Longest, P. [Virginia Commonwealth University, Richmond, VA (United States). Dept. of Mechanical Engineering; Kleinstreuer, C. [North Carolina State University, Raleigh, NC (United States). Dept. of Mechanical and Aerospace Engineering

2004-10-01

Individual and interacting effects of uniform flow, plane shear, and near-wall proximity on spherical droplet heat and mass transfer have been assessed for low Reynolds number conditions beyond the creeping flow regime. Validated resolved volume simulations were used to compute heat and mass transfer surface gradients of two-dimensional axisymmetric droplets and three-dimensional spherical droplets near planar wall boundaries for conditions consistent with inhalable aerosols (5 {<=} d {<=} 300 {mu}m) in the upper respiratory tract. Results indicate that planar shear significantly impacts droplet heat and mass transfer for shear-based Reynolds numbers greater than 1, which occur for near-wall respiratory aerosols with diameters in excess of 50 {mu}m. Wall proximity is shown to significantly enhance heat and mass transfer due to conduction and diffusion at separation distances less than five particle diameters and for small Reynolds numbers. For the Reynolds number conditions of interest, significant non-linear effects arise due to the concurrent interaction of uniform flow and shear such that linear superposition of Sherwood or Nusselt number terms is not allowable. Based on the validated numeric simulations, multivariable Sherwood and Nusselt number correlations are provided to account for individual flow characteristics and concurrent non-linear interactions of uniform flow, planar shear, and near-wall proximity. These heat and mass transfer correlations can be applied to effectively compute condensation and evaporation rates of potentially toxic or therapeutic aerosols in the upper respiratory tract, where non-uniform flow and wall proximity are expected to significantly affect droplet transport, deposition, and vapor formation. (author)

A Linear Programming Approach to Routing Control in Networks of Constrained Nonlinear Positive Systems with Concave Flow Rates

Science.gov (United States)

Arneson, Heather M.; Dousse, Nicholas; Langbort, Cedric

2014-01-01

We consider control design for positive compartmental systems in which each compartment's outflow rate is described by a concave function of the amount of material in the compartment.We address the problem of determining the routing of material between compartments to satisfy time-varying state constraints while ensuring that material reaches its intended destination over a finite time horizon. We give sufficient conditions for the existence of a time-varying state-dependent routing strategy which ensures that the closed-loop system satisfies basic network properties of positivity, conservation and interconnection while ensuring that capacity constraints are satisfied, when possible, or adjusted if a solution cannot be found. These conditions are formulated as a linear programming problem. Instances of this linear programming problem can be solved iteratively to generate a solution to the finite horizon routing problem. Results are given for the application of this control design method to an example problem. Key words: linear programming; control of networks; positive systems; controller constraints and structure.

Nutrient profiling can help identify foods of good nutritional quality for their price: a validation study with linear programming.

Science.gov (United States)

Maillot, Matthieu; Ferguson, Elaine L; Drewnowski, Adam; Darmon, Nicole

2008-06-01

Nutrient profiling ranks foods based on their nutrient content. They may help identify foods with a good nutritional quality for their price. This hypothesis was tested using diet modeling with linear programming. Analyses were undertaken using food intake data from the nationally representative French INCA (enquête Individuelle et Nationale sur les Consommations Alimentaires) survey and its associated food composition and price database. For each food, a nutrient profile score was defined as the ratio between the previously published nutrient density score (NDS) and the limited nutrient score (LIM); a nutritional quality for price indicator was developed and calculated from the relationship between its NDS:LIM and energy cost (in euro/100 kcal). We developed linear programming models to design diets that fulfilled increasing levels of nutritional constraints at a minimal cost. The median NDS:LIM values of foods selected in modeled diets increased as the levels of nutritional constraints increased (P = 0.005). In addition, the proportion of foods with a good nutritional quality for price indicator was higher (P linear programming and the nutrient profiling approaches indicates that nutrient profiling can help identify foods of good nutritional quality for their price. Linear programming is a useful tool for testing nutrient profiling systems and validating the concept of nutrient profiling.

A recurrent neural network for solving bilevel linear programming problem.

Science.gov (United States)

He, Xing; Li, Chuandong; Huang, Tingwen; Li, Chaojie; Huang, Junjian

2014-04-01

In this brief, based on the method of penalty functions, a recurrent neural network (NN) modeled by means of a differential inclusion is proposed for solving the bilevel linear programming problem (BLPP). Compared with the existing NNs for BLPP, the model has the least number of state variables and simple structure. Using nonsmooth analysis, the theory of differential inclusions, and Lyapunov-like method, the equilibrium point sequence of the proposed NNs can approximately converge to an optimal solution of BLPP under certain conditions. Finally, the numerical simulations of a supply chain distribution model have shown excellent performance of the proposed recurrent NNs.

Correction of heterogeneities in the issue compositions in the construction plans optimized in radiotherapy using linear programming

International Nuclear Information System (INIS)

Viana, Rodrigo Sartorelo S.; Lima, Ernesto A.B.F.; Florentino, Helenice de Oliveira; Fonseca, Paulo Roberto da; Homem, Thiago Pedro Donadon

2009-01-01

Linear programming models are widely found in the literature addressing various aspects involved in the creation of optimized planning for radiotherapy. However, most mathematical formulations does not incorporate certain factors that are of extreme importance for the formulation of a real planning like the attenuation of the beam of radiation and heterogeneity in the composition of tissue irradiated. In this context are proposed in this paper some modifications in the formulation of a linear programming problem with the objective of making the simulation closer to the real planning for radiotherapy and thus enable a more reliable and comprehensive planning requirements. (author)

Explicit/multi-parametric model predictive control (MPC) of linear discrete-time systems by dynamic and multi-parametric programming

KAUST Repository

Kouramas, K.I.; Faí sca, N.P.; Panos, C.; Pistikopoulos, E.N.

2011-01-01

This work presents a new algorithm for solving the explicit/multi- parametric model predictive control (or mp-MPC) problem for linear, time-invariant discrete-time systems, based on dynamic programming and multi-parametric programming techniques

A study of the use of linear programming techniques to improve the performance in design optimization problems

Science.gov (United States)

Young, Katherine C.; Sobieszczanski-Sobieski, Jaroslaw

1988-01-01

This project has two objectives. The first is to determine whether linear programming techniques can improve performance when handling design optimization problems with a large number of design variables and constraints relative to the feasible directions algorithm. The second purpose is to determine whether using the Kreisselmeier-Steinhauser (KS) function to replace the constraints with one constraint will reduce the cost of total optimization. Comparisons are made using solutions obtained with linear and non-linear methods. The results indicate that there is no cost saving using the linear method or in using the KS function to replace constraints.

Near-Regular Structure Discovery Using Linear Programming

KAUST Repository

Huang, Qixing

2014-06-02

Near-regular structures are common in manmade and natural objects. Algorithmic detection of such regularity greatly facilitates our understanding of shape structures, leads to compact encoding of input geometries, and enables efficient generation and manipulation of complex patterns on both acquired and synthesized objects. Such regularity manifests itself both in the repetition of certain geometric elements, as well as in the structured arrangement of the elements. We cast the regularity detection problem as an optimization and efficiently solve it using linear programming techniques. Our optimization has a discrete aspect, that is, the connectivity relationships among the elements, as well as a continuous aspect, namely the locations of the elements of interest. Both these aspects are captured by our near-regular structure extraction framework, which alternates between discrete and continuous optimizations. We demonstrate the effectiveness of our framework on a variety of problems including near-regular structure extraction, structure-preserving pattern manipulation, and markerless correspondence detection. Robustness results with respect to geometric and topological noise are presented on synthesized, real-world, and also benchmark datasets. © 2014 ACM.

A linear programming approach to characterizing norm bounded uncertainty from experimental data

Science.gov (United States)

Scheid, R. E.; Bayard, D. S.; Yam, Y.

1991-01-01

The linear programming spectral overbounding and factorization (LPSOF) algorithm, an algorithm for finding a minimum phase transfer function of specified order whose magnitude tightly overbounds a specified nonparametric function of frequency, is introduced. This method has direct application to transforming nonparametric uncertainty bounds (available from system identification experiments) into parametric representations required for modern robust control design software (i.e., a minimum-phase transfer function multiplied by a norm-bounded perturbation).

Mass Optimization of Battery/Supercapacitors Hybrid Systems Based on a Linear Programming Approach

Science.gov (United States)

Fleury, Benoit; Labbe, Julien

2014-08-01

The objective of this paper is to show that, on a specific launcher-type mission profile, a 40% gain of mass is expected using a battery/supercapacitors active hybridization instead of a single battery solution. This result is based on the use of a linear programming optimization approach to perform the mass optimization of the hybrid power supply solution.

Automated design and optimization of flexible booster autopilots via linear programming, volume 1

Science.gov (United States)

Hauser, F. D.

1972-01-01

A nonlinear programming technique was developed for the automated design and optimization of autopilots for large flexible launch vehicles. This technique, which resulted in the COEBRA program, uses the iterative application of linear programming. The method deals directly with the three main requirements of booster autopilot design: to provide (1) good response to guidance commands; (2) response to external disturbances (e.g. wind) to minimize structural bending moment loads and trajectory dispersions; and (3) stability with specified tolerances on the vehicle and flight control system parameters. The method is applicable to very high order systems (30th and greater per flight condition). Examples are provided that demonstrate the successful application of the employed algorithm to the design of autopilots for both single and multiple flight conditions.

Mixed Integer Linear Programming model for Crude Palm Oil Supply Chain Planning

Science.gov (United States)

Sembiring, Pasukat; Mawengkang, Herman; Sadyadharma, Hendaru; Bu'ulolo, F.; Fajriana

2018-01-01

The production process of crude palm oil (CPO) can be defined as the milling process of raw materials, called fresh fruit bunch (FFB) into end products palm oil. The process usually through a series of steps producing and consuming intermediate products. The CPO milling industry considered in this paper does not have oil palm plantation, therefore the FFB are supplied by several public oil palm plantations. Due to the limited availability of FFB, then it is necessary to choose from which plantations would be appropriate. This paper proposes a mixed integer linear programming model the supply chain integrated problem, which include waste processing. The mathematical programming model is solved using neighborhood search approach.

An improved multiple linear regression and data analysis computer program package

Science.gov (United States)

Sidik, S. M.

1972-01-01

NEWRAP, an improved version of a previous multiple linear regression program called RAPIER, CREDUC, and CRSPLT, allows for a complete regression analysis including cross plots of the independent and dependent variables, correlation coefficients, regression coefficients, analysis of variance tables, t-statistics and their probability levels, rejection of independent variables, plots of residuals against the independent and dependent variables, and a canonical reduction of quadratic response functions useful in optimum seeking experimentation. A major improvement over RAPIER is that all regression calculations are done in double precision arithmetic.

Feature network models for proximity data : statistical inference, model selection, network representations and links with related models

NARCIS (Netherlands)

Frank, Laurence Emmanuelle

2006-01-01

Feature Network Models (FNM) are graphical structures that represent proximity data in a discrete space with the use of features. A statistical inference theory is introduced, based on the additivity properties of networks and the linear regression framework. Considering features as predictor

Mixed-Integer-Linear-Programming-Based Energy Management System for Hybrid PV-Wind-Battery Microgrids

DEFF Research Database (Denmark)

Hernández, Adriana Carolina Luna; Aldana, Nelson Leonardo Diaz; Graells, Moises

2017-01-01

-side strategy, defined as a general mixed-integer linear programming by taking into account two stages for proper charging of the storage units. This model is considered as a deterministic problem that aims to minimize operating costs and promote self-consumption based on 24-hour ahead forecast data...

Comparison of acrylamide intake from Western and guideline based diets using probabilistic techniques and linear programming.

Science.gov (United States)

Katz, Josh M; Winter, Carl K; Buttrey, Samuel E; Fadel, James G

2012-03-01

Western and guideline based diets were compared to determine if dietary improvements resulting from following dietary guidelines reduce acrylamide intake. Acrylamide forms in heat treated foods and is a human neurotoxin and animal carcinogen. Acrylamide intake from the Western diet was estimated with probabilistic techniques using teenage (13-19 years) National Health and Nutrition Examination Survey (NHANES) food consumption estimates combined with FDA data on the levels of acrylamide in a large number of foods. Guideline based diets were derived from NHANES data using linear programming techniques to comport to recommendations from the Dietary Guidelines for Americans, 2005. Whereas the guideline based diets were more properly balanced and rich in consumption of fruits, vegetables, and other dietary components than the Western diets, acrylamide intake (mean±SE) was significantly greater (Plinear programming and results demonstrate that linear programming techniques can be used to model specific diets for the assessment of toxicological and nutritional dietary components. Copyright © 2011 Elsevier Ltd. All rights reserved.

Learning Bayesian network structure: towards the essential graph by integer linear programming tools

Czech Academy of Sciences Publication Activity Database

Studený, Milan; Haws, D.

2014-01-01

Roč. 55, č. 4 (2014), s. 1043-1071 ISSN 0888-613X R&D Projects: GA ČR GA13-20012S Institutional support: RVO:67985556 Keywords : learning Bayesian network structure * integer linear programming * characteristic imset * essential graph Subject RIV: BA - General Mathematics Impact factor: 2.451, year: 2014 http://library.utia.cas.cz/separaty/2014/MTR/studeny-0427002.pdf

Optimized remedial groundwater extraction using linear programming

International Nuclear Information System (INIS)

Quinn, J.J.

1995-01-01

Groundwater extraction systems are typically installed to remediate contaminant plumes or prevent further spread of contamination. These systems are expensive to install and maintain. A traditional approach to designing such a wellfield uses a series of trial-and-error simulations to test the effects of various well locations and pump rates. However, the optimal locations and pump rates of extraction wells are difficult to determine when objectives related to the site hydrogeology and potential pumping scheme are considered. This paper describes a case study of an application of linear programming theory to determine optimal well placement and pump rates. The objectives of the pumping scheme were to contain contaminant migration and reduce contaminant concentrations while minimizing the total amount of water pumped and treated. Past site activities at the area under study included disposal of contaminants in pits. Several groundwater plumes have been identified, and others may be present. The area of concern is bordered on three sides by a wetland, which receives a portion of its input budget as groundwater discharge from the pits. Optimization of the containment pumping scheme was intended to meet three goals: (1) prevent discharge of contaminated groundwater to the wetland, (2) minimize the total water pumped and treated (cost benefit), and (3) avoid dewatering of the wetland (cost and ecological benefits). Possible well locations were placed at known source areas. To constrain the problem, the optimization program was instructed to prevent any flow toward the wetland along a user-specified border. In this manner, the optimization routine selects well locations and pump rates so that a groundwater divide is produced along this boundary

A Method of Determination of an Acquisition Program in Order to Maximize the Total Utility Using Linear Programming in Integer Numbers

Directory of Open Access Journals (Sweden)

Alin Cristian Ioan

2010-03-01

Full Text Available This paper solves in a different way the problem of maximization of the total utility using the linear programming in integer numbers. The author uses the diofantic equations (equations in integers numbers and after a decomposing in different cases, he obtains the maximal utility.

A Novel Linear Programming Formulation of Maximum Lifetime Routing Problem in Wireless Sensor Networks

DEFF Research Database (Denmark)

Cetin, Bilge Kartal; Prasad, Neeli R.; Prasad, Ramjee

2011-01-01

In wireless sensor networks, one of the key challenge is to achieve minimum energy consumption in order to maximize network lifetime. In fact, lifetime depends on many parameters: the topology of the sensor network, the data aggregation regime in the network, the channel access schemes, the routing...... protocols, and the energy model for transmission. In this paper, we tackle the routing challenge for maximum lifetime of the sensor network. We introduce a novel linear programming approach to the maximum lifetime routing problem. To the best of our knowledge, this is the first mathematical programming...

Experience and development program for the I.V. Kurchatov Atomic Energy Institute electron linear accelerator

International Nuclear Information System (INIS)

Aref'ev, A.V.; Blokhov, M.V.; Gerasimov, V.F.

1981-01-01

A program of physical investigations and the corresponding requirements to accelerated beam parameters are discussed in brief. The state and working capacity of separate units and the accelerator as a whole for the 8-year operating period are analyzed. The aim and principal program points of linear electron accelerator modernization are defined. The program of accelerator modernization assumes: electron beam energy increase up to 100-120 MeV; mounting of three additional accelerating sections; clystron efficiency increase; development of a highly reliable modulator; stabilized power supply sources; a system of synchronous start-up; a focusing system; a beam separation system and etc [ru

A Mixed Integer Linear Programming Model for the North Atlantic Aircraft Trajectory Planning

OpenAIRE

Sbihi , Mohammed; Rodionova , Olga; Delahaye , Daniel; Mongeau , Marcel

2015-01-01

International audience; This paper discusses the trajectory planning problem for ights in the North Atlantic oceanic airspace (NAT). We develop a mathematical optimization framework in view of better utilizing available capacity by re-routing aircraft. The model is constructed by discretizing the problem parameters. A Mixed integer linear program (MILP) is proposed. Based on the MILP a heuristic to solve real-size instances is also introduced

What linear programming contributes: world food programme experience with the "cost of the diet" tool.

Science.gov (United States)

Frega, Romeo; Lanfranco, Jose Guerra; De Greve, Sam; Bernardini, Sara; Geniez, Perrine; Grede, Nils; Bloem, Martin; de Pee, Saskia

2012-09-01

Linear programming has been used for analyzing children's complementary feeding diets, for optimizing nutrient adequacy of dietary recommendations for a population, and for estimating the economic value of fortified foods. To describe and apply a linear programming tool ("Cost of the Diet") with data from Mozambique to determine what could be cost-effective fortification strategies. Based on locally assessed average household dietary needs, seasonal market prices of available food products, and food composition data, the tool estimates the lowest-cost diet that meets almost all nutrient needs. The results were compared with expenditure data from Mozambique to establish the affordability of this diet by quintiles of the population. Three different applications were illustrated: identifying likely "limiting nutrients," comparing cost effectiveness of different fortification interventions at the household level, and assessing economic access to nutritious foods. The analysis identified iron, vitamin B2, and pantothenic acid as "limiting nutrients." Under the Mozambique conditions, vegetable oil was estimated as a more cost-efficient vehicle for vitamin A fortification than sugar; maize flour may also be an effective vehicle to provide other constraining micronutrients. Multiple micronutrient fortification of maize flour could reduce the cost of the "lowest-cost nutritious diet" by 18%, but even this diet can be afforded by only 20% of the Mozambican population. Within the context of fortification, linear programming can be a useful tool for identifying likely nutrient inadequacies, for comparing fortification options in terms of cost effectiveness, and for illustrating the potential benefit of fortification for improving household access to a nutritious diet.

MODLP program description: A program for solving linear optimal hydraulic control of groundwater contamination based on MODFLOW simulation. Version 1.0

International Nuclear Information System (INIS)

Ahlfeld, D.P.; Dougherty, D.E.

1994-11-01

MODLP is a computational tool that may help design capture zones for controlling the movement of contaminated groundwater. It creates and solves linear optimization programs that contain constraints on hydraulic head or head differences in a groundwater system. The groundwater domain is represented by USGS MODFLOW groundwater flow simulation model. This document describes the general structure of the computer program, MODLP, the types of constraints that may be imposed, detailed input instructions, interpretation of the output, and the interaction with the MODFLOW simulation kernel

An SDP Approach for Multiperiod Mixed 0–1 Linear Programming Models with Stochastic Dominance Constraints for Risk Management

DEFF Research Database (Denmark)

Escudero, Laureano F.; Monge, Juan Francisco; Morales, Dolores Romero

2015-01-01

In this paper we consider multiperiod mixed 0–1 linear programming models under uncertainty. We propose a risk averse strategy using stochastic dominance constraints (SDC) induced by mixed-integer linear recourse as the risk measure. The SDC strategy extends the existing literature to the multist...

EABOT - Energetic analysis as a basis for robust optimization of trigeneration systems by linear programming

International Nuclear Information System (INIS)

Piacentino, A.; Cardona, F.

2008-01-01

The optimization of synthesis, design and operation in trigeneration systems for building applications is a quite complex task, due to the high number of decision variables, the presence of irregular heat, cooling and electric load profiles and the variable electricity price. Consequently, computer-aided techniques are usually adopted to achieve the optimal solution, based either on iterative techniques, linear or non-linear programming or evolutionary search. Large efforts have been made in improving algorithm efficiency, which have resulted in an increasingly rapid convergence to the optimal solution and in reduced calculation time; robust algorithm have also been formulated, assuming stochastic behaviour for energy loads and prices. This paper is based on the assumption that margins for improvements in the optimization of trigeneration systems still exist, which require an in-depth understanding of plant's energetic behaviour. Robustness in the optimization of trigeneration systems has more to do with a 'correct and comprehensive' than with an 'efficient' modelling, being larger efforts required to energy specialists rather than to experts in efficient algorithms. With reference to a mixed integer linear programming model implemented in MatLab for a trigeneration system including a pressurized (medium temperature) heat storage, the relevant contribute of thermoeconomics and energo-environmental analysis in the phase of mathematical modelling and code testing are shown

Trampoline fracture of the proximal tibial metaphysis in children may not progress into valgus: a report of seven cases and a brief review.

Science.gov (United States)

Kakel, R

2012-06-01

Fracture of the proximal tibial metaphysis in children is a rare injury but notorious for carrying the risk of subsequent valgus deformity of the tibia. Trampoline-caused fracture of the proximal tibial metaphysis in children may not progress into valgus. We followed up six children who collectively sustained seven fractures of the proximal tibial metaphysis while trampolining with other heavier and/or older children. Initial and follow-up x-rays were reviewed by an orthopaedic surgeons and two radiologists. None of the patients developed valgus deformity with follow-up. Trampoline is associated with a specific type of injury to the proximal tibia when children are trampolining with other heavier children even without falling off the trampoline. This fracture is linear and complete, often non-displaced. Unlike "other" proximal tibial metaphyseal fractures, trampoline-associated proximal tibial metaphysical fracture in children is not associated with a risk of subsequent valgus deformity. Level 4. case series. Copyright © 2012 Elsevier Masson SAS. All rights reserved.

A duality approach for solving bounded linear programming problems with fuzzy variables based on ranking functions and its application in bounded transportation problems

Science.gov (United States)

Ebrahimnejad, Ali

2015-08-01

There are several methods, in the literature, for solving fuzzy variable linear programming problems (fuzzy linear programming in which the right-hand-side vectors and decision variables are represented by trapezoidal fuzzy numbers). In this paper, the shortcomings of some existing methods are pointed out and to overcome these shortcomings a new method based on the bounded dual simplex method is proposed to determine the fuzzy optimal solution of that kind of fuzzy variable linear programming problems in which some or all variables are restricted to lie within lower and upper bounds. To illustrate the proposed method, an application example is solved and the obtained results are given. The advantages of the proposed method over existing methods are discussed. Also, one application of this algorithm in solving bounded transportation problems with fuzzy supplies and demands is dealt with. The proposed method is easy to understand and to apply for determining the fuzzy optimal solution of bounded fuzzy variable linear programming problems occurring in real-life situations.

STICAP: A linear circuit analysis program with stiff systems capability. Volume 1: Theory manual. [network analysis

Science.gov (United States)

Cooke, C. H.

1975-01-01

STICAP (Stiff Circuit Analysis Program) is a FORTRAN 4 computer program written for the CDC-6400-6600 computer series and SCOPE 3.0 operating system. It provides the circuit analyst a tool for automatically computing the transient responses and frequency responses of large linear time invariant networks, both stiff and nonstiff (algorithms and numerical integration techniques are described). The circuit description and user's program input language is engineer-oriented, making simple the task of using the program. Engineering theories underlying STICAP are examined. A user's manual is included which explains user interaction with the program and gives results of typical circuit design applications. Also, the program structure from a systems programmer's viewpoint is depicted and flow charts and other software documentation are given.

A Genetic-Algorithms-Based Approach for Programming Linear and Quadratic Optimization Problems with Uncertainty

Directory of Open Access Journals (Sweden)

Weihua Jin

2013-01-01

Full Text Available This paper proposes a genetic-algorithms-based approach as an all-purpose problem-solving method for operation programming problems under uncertainty. The proposed method was applied for management of a municipal solid waste treatment system. Compared to the traditional interactive binary analysis, this approach has fewer limitations and is able to reduce the complexity in solving the inexact linear programming problems and inexact quadratic programming problems. The implementation of this approach was performed using the Genetic Algorithm Solver of MATLAB (trademark of MathWorks. The paper explains the genetic-algorithms-based method and presents details on the computation procedures for each type of inexact operation programming problems. A comparison of the results generated by the proposed method based on genetic algorithms with those produced by the traditional interactive binary analysis method is also presented.

Dose optimization based on linear programming implemented in a system for treatment planning in Monte Carlo

International Nuclear Information System (INIS)

Ureba, A.; Palma, B. A.; Leal, A.

2011-01-01

Develop a more efficient method of optimization in relation to time, based on linear programming designed to implement a multi objective penalty function which also permits a simultaneous solution integrated boost situations considering two white volumes simultaneously.

GIS Application to Define Biomass Collection Points as Sources for Linear Programming of Delivery Networks

NARCIS (Netherlands)

Velazquez-Marti, B.; Annevelink, E.

2009-01-01

Much bio-energy can be obtained from wood pruning operations in forests and fruit orchards. Several spatial studies have been carried out for biomass surveys, and many linear programming models have been developed to model the logistics of bio-energy chains. These models can assist in determining

Stress-constrained truss topology optimization problems that can be solved by linear programming

DEFF Research Database (Denmark)

Stolpe, Mathias; Svanberg, Krister

2004-01-01

We consider the problem of simultaneously selecting the material and determining the area of each bar in a truss structure in such a way that the cost of the structure is minimized subject to stress constraints under a single load condition. We show that such problems can be solved by linear...... programming to give the global optimum, and that two different materials are always sufficient in an optimal structure....

Variability of United States Online Rehabilitation Protocols for Proximal Hamstring Tendon Repair.

Science.gov (United States)

Lightsey, Harry M; Kantrowitz, David E; Swindell, Hasani W; Trofa, David P; Ahmad, Christopher S; Lynch, T Sean

2018-02-01

The optimal postoperative rehabilitation protocol following repair of complete proximal hamstring tendon ruptures is the subject of ongoing investigation, with a need for more standardized regimens and evidence-based modalities. To assess the variability across proximal hamstring tendon repair rehabilitation protocols published online by United States (US) orthopaedic teaching programs. Cross-sectional study. Online proximal hamstring physical therapy protocols from US academic orthopaedic programs were reviewed. A web-based search using the search term complete proximal hamstring repair rehabilitation protocol provided an additional 14 protocols. A comprehensive scoring rubric was developed after review of all protocols and was used to assess each protocol for both the presence of various rehabilitation components and the point at which those components were introduced. Of 50 rehabilitation protocols identified, 35 satisfied inclusion criteria and were analyzed. Twenty-five protocols (71%) recommended immediate postoperative bracing: 12 (34%) prescribed knee bracing, 8 (23%) prescribed hip bracing, and 5 (14%) did not specify the type of brace recommended. Fourteen protocols (40%) advised immediate nonweightbearing with crutches, while 16 protocols (46%) permitted immediate toe-touch weightbearing. Advancement to full weightbearing was allowed at a mean of 7.1 weeks (range, 4-12 weeks). Most protocols (80%) recommended gentle knee and hip passive range of motion and active range of motion, starting at a mean 1.4 weeks (range, 0-3 weeks) and 4.0 weeks (range, 0-6 weeks), respectively. However, only 6 protocols (17%) provided specific time points to initiate full hip and knee range of motion: a mean 8.0 weeks (range, 4-12 weeks) and 7.8 weeks (range, 0-12 weeks), respectively. Considerable variability was noted in the inclusion and timing of strengthening, stretching, proprioception, and cardiovascular exercises. Fifteen protocols (43%) required completion of

PROXIMITY MANAGEMENT IN CRISIS CONDITIONS

Directory of Open Access Journals (Sweden)

Ion Dorin BUMBENECI

2010-01-01

Full Text Available The purpose of this study is to evaluate the level of assimilation for the terms "Proximity Management" and "Proximity Manager", both in the specialized literature and in practice. The study has two parts: the theoretical research of the two terms, and an evaluation of the use of Proximity management in 32 companies in Gorj, Romania. The object of the evaluation resides in 27 companies with less than 50 employees and 5 companies with more than 50 employees.

Novel methods for Solving Economic Dispatch of Security-Constrained Unit Commitment Based on Linear Programming

Science.gov (United States)

Guo, Sangang

2017-09-01

There are two stages in solving security-constrained unit commitment problems (SCUC) within Lagrangian framework: one is to obtain feasible units’ states (UC), the other is power economic dispatch (ED) for each unit. The accurate solution of ED is more important for enhancing the efficiency of the solution to SCUC for the fixed feasible units’ statues. Two novel methods named after Convex Combinatorial Coefficient Method and Power Increment Method respectively based on linear programming problem for solving ED are proposed by the piecewise linear approximation to the nonlinear convex fuel cost functions. Numerical testing results show that the methods are effective and efficient.

Problem Based Learning Technique and Its Effect on Acquisition of Linear Programming Skills by Secondary School Students in Kenya

Science.gov (United States)

Nakhanu, Shikuku Beatrice; Musasia, Amadalo Maurice

2015-01-01

The topic Linear Programming is included in the compulsory Kenyan secondary school mathematics curriculum at form four. The topic provides skills for determining best outcomes in a given mathematical model involving some linear relationship. This technique has found application in business, economics as well as various engineering fields. Yet many…

Solutions to estimation problems for scalar hamilton-jacobi equations using linear programming

KAUST Repository

Claudel, Christian G.; Chamoin, Timothee; Bayen, Alexandre M.

2014-01-01

This brief presents new convex formulations for solving estimation problems in systems modeled by scalar Hamilton-Jacobi (HJ) equations. Using a semi-analytic formula, we show that the constraints resulting from a HJ equation are convex, and can be written as a set of linear inequalities. We use this fact to pose various (and seemingly unrelated) estimation problems related to traffic flow-engineering as a set of linear programs. In particular, we solve data assimilation and data reconciliation problems for estimating the state of a system when the model and measurement constraints are incompatible. We also solve traffic estimation problems, such as travel time estimation or density estimation. For all these problems, a numerical implementation is performed using experimental data from the Mobile Century experiment. In the context of reproducible research, the code and data used to compute the results presented in this brief have been posted online and are accessible to regenerate the results. © 2013 IEEE.

Optimisation of substrate blends in anaerobic co-digestion using adaptive linear programming.

Science.gov (United States)

García-Gen, Santiago; Rodríguez, Jorge; Lema, Juan M

2014-12-01

Anaerobic co-digestion of multiple substrates has the potential to enhance biogas productivity by making use of the complementary characteristics of different substrates. A blending strategy based on a linear programming optimisation method is proposed aiming at maximising COD conversion into methane, but simultaneously maintaining a digestate and biogas quality. The method incorporates experimental and heuristic information to define the objective function and the linear restrictions. The active constraints are continuously adapted (by relaxing the restriction boundaries) such that further optimisations in terms of methane productivity can be achieved. The feasibility of the blends calculated with this methodology was previously tested and accurately predicted with an ADM1-based co-digestion model. This was validated in a continuously operated pilot plant, treating for several months different mixtures of glycerine, gelatine and pig manure at organic loading rates from 1.50 to 4.93 gCOD/Ld and hydraulic retention times between 32 and 40 days at mesophilic conditions. Copyright © 2014 Elsevier Ltd. All rights reserved.

Storage and distribution/Linear programming for storage operations

Energy Technology Data Exchange (ETDEWEB)

Coleman, D

1978-07-15

The techniques of linear programing to solve storage problems as applied in a tank farm tie-in with refinery throughput operation include: (1) the time-phased model which works on storage and refinery operations input parameters, e.g., production, distribution, cracking, etc., and is capable of representing product stockpiling in slack periods to meet future peak demands, and investigating alternative strategies such as exchange deals and purchase and leasing of additional storage, and (2) the Monte Carlo simulation method, which inputs parameters, e.g., arrival of crude products at refinery, tankage size, likely demand for products, etc., as probability distributions rather than single values, and is capable of showing the average utilization of facilities, potential bottlenecks, investment required to achieve an increase in utilization, and to enable the user to predict total investment, cash flow, and profit emanating from the original financing decision. The increasing use of computer techniques to solve refinery and storage problems is attributed to potential savings resulting from more effective planning, reduced computer costs, ease of access and more usable software. Diagrams.

Local beam angle optimization with linear programming and gradient search

International Nuclear Information System (INIS)

Craft, David

2007-01-01

The optimization of beam angles in IMRT planning is still an open problem, with literature focusing on heuristic strategies and exhaustive searches on discrete angle grids. We show how a beam angle set can be locally refined in a continuous manner using gradient-based optimization in the beam angle space. The gradient is derived using linear programming duality theory. Applying this local search to 100 random initial angle sets of a phantom pancreatic case demonstrates the method, and highlights the many-local-minima aspect of the BAO problem. Due to this function structure, we recommend a search strategy of a thorough global search followed by local refinement at promising beam angle sets. Extensions to nonlinear IMRT formulations are discussed. (note)

Proximal tubular hypertrophy and enlarged glomerular and proximal tubular urinary space in obese subjects with proteinuria.

Directory of Open Access Journals (Sweden)

Ana Tobar

Full Text Available BACKGROUND: Obesity is associated with glomerular hyperfiltration, increased proximal tubular sodium reabsorption, glomerular enlargement and renal hypertrophy. A single experimental study reported an increased glomerular urinary space in obese dogs. Whether proximal tubular volume is increased in obese subjects and whether their glomerular and tubular urinary spaces are enlarged is unknown. OBJECTIVE: To determine whether proximal tubules and glomerular and tubular urinary space are enlarged in obese subjects with proteinuria and glomerular hyperfiltration. METHODS: Kidney biopsies from 11 non-diabetic obese with proteinuria and 14 non-diabetic lean patients with a creatinine clearance above 50 ml/min and with mild or no interstitial fibrosis were retrospectively analyzed using morphometric methods. The cross-sectional area of the proximal tubular epithelium and lumen, the volume of the glomerular tuft and of Bowman's space and the nuclei number per tubular profile were estimated. RESULTS: Creatinine clearance was higher in the obese than in the lean group (P=0.03. Proteinuria was similarly increased in both groups. Compared to the lean group, the obese group displayed a 104% higher glomerular tuft volume (P=0.001, a 94% higher Bowman's space volume (P=0.003, a 33% higher cross-sectional area of the proximal tubular epithelium (P=0.02 and a 54% higher cross-sectional area of the proximal tubular lumen (P=0.01. The nuclei number per proximal tubular profile was similar in both groups, suggesting that the increase in tubular volume is due to hypertrophy and not to hyperplasia. CONCLUSIONS: Obesity-related glomerular hyperfiltration is associated with proximal tubular epithelial hypertrophy and increased glomerular and tubular urinary space volume in subjects with proteinuria. The expanded glomerular and urinary space is probably a direct consequence of glomerular hyperfiltration. These effects may be involved in the pathogenesis of obesity

A novel linear programming approach to fluence map optimization for intensity modulated radiation therapy treatment planning

International Nuclear Information System (INIS)

Romeijn, H Edwin; Ahuja, Ravindra K; Dempsey, James F; Kumar, Arvind; Li, Jonathan G

2003-01-01

We present a novel linear programming (LP) based approach for efficiently solving the intensity modulated radiation therapy (IMRT) fluence-map optimization (FMO) problem to global optimality. Our model overcomes the apparent limitations of a linear-programming approach by approximating any convex objective function by a piecewise linear convex function. This approach allows us to retain the flexibility offered by general convex objective functions, while allowing us to formulate the FMO problem as a LP problem. In addition, a novel type of partial-volume constraint that bounds the tail averages of the differential dose-volume histograms of structures is imposed while retaining linearity as an alternative approach to improve dose homogeneity in the target volumes, and to attempt to spare as many critical structures as possible. The goal of this work is to develop a very rapid global optimization approach that finds high quality dose distributions. Implementation of this model has demonstrated excellent results. We found globally optimal solutions for eight 7-beam head-and-neck cases in less than 3 min of computational time on a single processor personal computer without the use of partial-volume constraints. Adding such constraints increased the running times by a factor of 2-3, but improved the sparing of critical structures. All cases demonstrated excellent target coverage (>95%), target homogeneity (<10% overdosing and <7% underdosing) and organ sparing using at least one of the two models

Chance-constrained/stochastic linear programming model for acid rain abatement. I. Complete colinearity and noncolinearity

Energy Technology Data Exchange (ETDEWEB)

Ellis, J H; McBean, E A; Farquhar, G J

1985-01-01

A Linear Programming model is presented for development of acid rain abatement strategies in eastern North America. For a system comprised of 235 large controllable point sources and 83 uncontrolled area sources, it determines the least-cost method of reducing SO/sub 2/ emissions to satisfy maximum wet sulfur deposition limits at 20 sensitive receptor locations. In this paper, the purely deterministic model is extended to a probabilistic form by incorporating the effects of meteorologic variability on the long-range pollutant transport processes. These processes are represented by source-receptor-specific transfer coefficients. Experiments for quantifying the spatial variability of transfer coefficients showed their distributions to be approximately lognormal with logarithmic standard deviations consistently about unity. Three methods of incorporating second-moment random variable uncertainty into the deterministic LP framework are described: Two-Stage Programming Under Uncertainty, Chance-Constrained Programming and Stochastic Linear Programming. A composite CCP-SLP model is developed which embodies the two-dimensional characteristics of transfer coefficient uncertainty. Two probabilistic formulations are described involving complete colinearity and complete noncolinearity for the transfer coefficient covariance-correlation structure. The completely colinear and noncolinear formulations are considered extreme bounds in a meteorologic sense and yield abatement strategies of largely didactic value. Such strategies can be characterized as having excessive costs and undesirable deposition results in the completely colinear case and absence of a clearly defined system risk level (other than expected-value) in the noncolinear formulation.

Fractures of the proximal humerus

DEFF Research Database (Denmark)

Brorson, Stig

2013-01-01

Fractures of the proximal humerus have been diagnosed and managed since the earliest known surgical texts. For more than four millennia the preferred treatment was forceful traction, closed reduction, and immobilization with linen soaked in combinations of oil, honey, alum, wine, or cerate......, classification of proximal humeral fractures remains a challenge for the conduct, reporting, and interpretation of clinical trials. The evidence for the benefits of surgery in complex fractures of the proximal humerus is weak. In three systematic reviews I studied the outcome after locking plate osteosynthesis...

Split diversity in constrained conservation prioritization using integer linear programming.

Science.gov (United States)

Chernomor, Olga; Minh, Bui Quang; Forest, Félix; Klaere, Steffen; Ingram, Travis; Henzinger, Monika; von Haeseler, Arndt

2015-01-01

Phylogenetic diversity (PD) is a measure of biodiversity based on the evolutionary history of species. Here, we discuss several optimization problems related to the use of PD, and the more general measure split diversity (SD), in conservation prioritization.Depending on the conservation goal and the information available about species, one can construct optimization routines that incorporate various conservation constraints. We demonstrate how this information can be used to select sets of species for conservation action. Specifically, we discuss the use of species' geographic distributions, the choice of candidates under economic pressure, and the use of predator-prey interactions between the species in a community to define viability constraints.Despite such optimization problems falling into the area of NP hard problems, it is possible to solve them in a reasonable amount of time using integer programming. We apply integer linear programming to a variety of models for conservation prioritization that incorporate the SD measure.We exemplarily show the results for two data sets: the Cape region of South Africa and a Caribbean coral reef community. Finally, we provide user-friendly software at http://www.cibiv.at/software/pda.

Flexible solution of linear program with an application to decommissioning planning of nuclear reactor

International Nuclear Information System (INIS)

Shimizu, Yoshiaki

1988-01-01

Due to the simplicity and effectiveness, linear program has been popular in the actual optimization in various fields. In the previous study, the uncertainty involved in the model at the different stage of optimization was dealt with by post-optimizing analysis. But it often becomes insufficient to make a decision how to deal with an uncertain system especially suffering large parameter deviation. Recently in the field of processing systems, it is desired to obtain a flexible solution which can present the counterplan to a deviating system from a practical viewpoint. The scope of this preliminary note presents how to apply a methodology development to obtain the flexible solution of a linear program. For this purpose, a simple example associated with nuclear reactor decommissioning is shown. The problem to maximize a system performance given as an objective function under the constraint of the static behavior of the system is considered, and the flexible solution is determined. In Japan, the decommissioning of commercial nuclear power plants will being in near future, and the study using the retired research reactor JPDR is in progress. The planning of decontamination and the reuse of wastes is taken as the example. (Kako, I.)

A linear goal programming model for urban energy-economy-environment interaction

Energy Technology Data Exchange (ETDEWEB)

Kambo, N.S.; Handa, B.R. (Indian Inst. of Tech., New Delhi (India). Dept. of Mathematics); Bose, R.K. (Tata Energy Research Inst., New Delhi (India))

1991-01-01

This paper provides a comprehensive and systematic analysis of energy and pollution problems interconnected with the economic structure, by using a multi-objective sectoral end-use model for addressing regional energy policy issues. The multi-objective model proposed for the study is a 'linear goal programming (LGP)' technique of analysing a 'reference energy system (RES)' in a framework within which alternative policies and technical strategies may be evaluated. The model so developed has further been tested for the city of Delhi (India) for the period 1985 - 86, and a scenario analysis has been carried out by assuming different policy options. (orig./BWJ).

Linking linear programming and spatial simulation models to predict landscape effects of forest management alternatives

Science.gov (United States)

Eric J. Gustafson; L. Jay Roberts; Larry A. Leefers

2006-01-01

Forest management planners require analytical tools to assess the effects of alternative strategies on the sometimes disparate benefits from forests such as timber production and wildlife habitat. We assessed the spatial patterns of alternative management strategies by linking two models that were developed for different purposes. We used a linear programming model (...

Modeling the effects of palm-house proximity on the theoretical risk of Chagas disease transmission in a rural locality of the Orinoco basin, Colombia

Directory of Open Access Journals (Sweden)

Diana Erazo

2016-11-01

Full Text Available Abstract Background Chagas disease is a major public health concern in Latin America and it is transmitted by insects of the subfamily Triatominae, including Rhodnius spp. Since palm trees are ubiquitous in Colombia and a habitat for Rhodnius spp., the presence of palms near villages could increase contact rates between vectors and humans. Therefore, knowing whether a relationship exists between the proximity of palms to villages and the abundance and distribution of vectors therein, may be critical for Chagas disease prevention programs. Adapting a mathematical model for R. prolixus population dynamics in a small village, we model the implications of changing distances between palms and dwellings, to the risk of Chagas disease infection. Methods We implemented a mathematical model that reflects R. prolixus population dynamics in a small village located in the department of Casanare (Colombia to study the role of palm-house proximity. We varied the distance between palms and houses by monitoring the network global efficiency metric. We constructed 1,000 hypothetical villages varying distances and each one was run 100 times. Results According to the model, as palm-house proximity increases, houses were more likely to be visited by triatomine bugs. The number of bugs per unit time increased progressively in a non-linear fashion with high variability. We stress the importance of village configuration on the model output. Conclusions From a theoretical perspective, palm-house proximity may have a positive effect on the incidence of Chagas disease. The model predicts a 1% increase in new human cases per year when houses and palms are brought closer by 75%.

Initial outcome and efficacy of S3 proximal humerus locking plate in the treatment of proximal humerus fractures

International Nuclear Information System (INIS)

Zhang Zhiming; Zhu Xuesong; Bao Zhaohua; Yang Huilin

2012-01-01

Objective: to explore the initial outcome and efficacy of S 3 proximal humerus locking plate in the treatment of proximal humerus fractures. Methods: Twenty-two patients with proximal humerus fracture were treated with the S 3 proximal humerus locking plate. Most of the fractures were complex, two-part (n=4), three-part (n=11) and four-part (n=7) fractures according to the Neer classification of the proximal humerus fractures. Results: All patients were followed up for 3∼15 months. There were no complications related to the implant including loosening or breakage of the plate. Good and excellent results were documented in 17 patients fair results in 4 patients according the Neer scores of shoulder. Conclusion: New design concepts of S 3 proximal humerus plate provide the subchondral support and the internal fixation support. With the addition of the proper exercise of the shoulder joint, the outcomes would be satisfied. (authors)

A Global Optimization Algorithm for Sum of Linear Ratios Problem

OpenAIRE

Yuelin Gao; Siqiao Jin

2013-01-01

We equivalently transform the sum of linear ratios programming problem into bilinear programming problem, then by using the linear characteristics of convex envelope and concave envelope of double variables product function, linear relaxation programming of the bilinear programming problem is given, which can determine the lower bound of the optimal value of original problem. Therefore, a branch and bound algorithm for solving sum of linear ratios programming problem is put forward, and the c...

CiOpt: a program for optimization of the frequency response of linear circuits

OpenAIRE

Miró Sans, Joan Maria; Palà Schönwälder, Pere

1991-01-01

An interactive personal-computer program for optimizing the frequency response of linear lumped circuits (CiOpt) is presented. CiOpt has proved to be an efficient tool in improving designs where the inclusion of more accurate device models distorts the desired frequency response, as well as in device modeling. The outputs of CiOpt are the element values which best match the obtained and the desired frequency response. The optimization algorithms used (the Fletcher-Powell and Newton's methods,...

Fuzzy solution of the linear programming problem with interval coefficients in the constraints

OpenAIRE

Dorota Kuchta

2005-01-01

A fuzzy concept of solving the linear programming problem with interval coefficients is proposed. For each optimism level of the decision maker (where the optimism concerns the certainty that no errors have been committed in the estimation of the interval coefficients and the belief that optimistic realisations of the interval coefficients will occur) another interval solution of the problem will be generated and the decision maker will be able to choose the final solution having a complete v...

Preoperative assessment of the cancellous bone mineral density of the proximal humerus using CT data

International Nuclear Information System (INIS)

Krappinger, Dietmar; Roth, Tobias; Gschwentner, Martin; Suckert, Armin; Blauth, Michael; Hengg, Clemens; Kralinger, Franz

2012-01-01

Osteoporotic fractures of the proximal humerus show an increasing incidence. Osteoporosis not only influences the fracture risk after low-energy trauma, but also affects the mechanical stability of internal fixation. Preoperative assessment of the local bone quality may be useful in the surgical treatment of patients sustaining these injuries. The aim of the present study was to present a method for the preoperative assessment of the local cancellous bone mineral density (BMD) of the proximal humerus using CT data. In the first part of the study, CT scans of 30 patients with unilateral fractures of the proximal humerus after low-energy trauma were used. The local BMD was assessed on the contralateral uninjured side. All 30 patients additionally underwent dual-emission X-ray absorptiometry (DXA) of the lumbar spine, proximal femur, and forearm of the side of the uninjured proximal humerus within 6 weeks after trauma. Three independent trauma surgeons performed measurements on the uninjured proximal humerus twice with a time interval of 4 weeks in order to assess the inter- and intraobserver reliability of the method. In the second part of the study, the local BMD of 507 patients with either proximal humerus fractures or chronic shoulder instability was assessed by a single trauma surgeon. In both parts, the average HU values in standardized ROIs of the humeral head were automatically calculated after correcting for HU values below the water equivalent. A linear calibration equation was computed for the calculation from HU to BMD using a calibration device (EFP). The intra- and interobserver reliability was high (ICC > 0.95). Correlation coefficients between the local BMD of the proximal humerus and other anatomical sites were between 0.35 (lumbar spine) and 0.64 (forearm). We found a high correlation between the local BMD and age. The BMD in the fracture group was significantly lower than in the instability group. These patients were significantly older and more

Preoperative assessment of the cancellous bone mineral density of the proximal humerus using CT data

Energy Technology Data Exchange (ETDEWEB)

Krappinger, Dietmar; Roth, Tobias; Gschwentner, Martin; Suckert, Armin; Blauth, Michael; Hengg, Clemens; Kralinger, Franz [Innsbruck Medical University, Department of Trauma Surgery and Sports Medicine, Innsbruck (Austria)

2012-03-15

Osteoporotic fractures of the proximal humerus show an increasing incidence. Osteoporosis not only influences the fracture risk after low-energy trauma, but also affects the mechanical stability of internal fixation. Preoperative assessment of the local bone quality may be useful in the surgical treatment of patients sustaining these injuries. The aim of the present study was to present a method for the preoperative assessment of the local cancellous bone mineral density (BMD) of the proximal humerus using CT data. In the first part of the study, CT scans of 30 patients with unilateral fractures of the proximal humerus after low-energy trauma were used. The local BMD was assessed on the contralateral uninjured side. All 30 patients additionally underwent dual-emission X-ray absorptiometry (DXA) of the lumbar spine, proximal femur, and forearm of the side of the uninjured proximal humerus within 6 weeks after trauma. Three independent trauma surgeons performed measurements on the uninjured proximal humerus twice with a time interval of 4 weeks in order to assess the inter- and intraobserver reliability of the method. In the second part of the study, the local BMD of 507 patients with either proximal humerus fractures or chronic shoulder instability was assessed by a single trauma surgeon. In both parts, the average HU values in standardized ROIs of the humeral head were automatically calculated after correcting for HU values below the water equivalent. A linear calibration equation was computed for the calculation from HU to BMD using a calibration device (EFP). The intra- and interobserver reliability was high (ICC > 0.95). Correlation coefficients between the local BMD of the proximal humerus and other anatomical sites were between 0.35 (lumbar spine) and 0.64 (forearm). We found a high correlation between the local BMD and age. The BMD in the fracture group was significantly lower than in the instability group. These patients were significantly older and more

Preliminary study on leadership proximity

Directory of Open Access Journals (Sweden)

Ghinea Valentina Mihaela

2017-07-01

Full Text Available In general, it is agreed that effective leadership requires a certain degree of proximity, either physical or mental, which enables leaders to maintain control over their followers and communicate their vision. Although we agree with the leadership proximity principles which states that leaders are able to efficiently serve only those people with whom they interact frequently, in this article we focus instead on the disadvantages of being too close and the way in which close proximity can actually hurt the effectiveness of leadership. The main effects that we discuss regard the way in which proximity and familiarity allow followers to see the weaknesses and faults of the leader much more easily and thus diminish the leader’s heroic aura, and the emotional bias that results from a leader being too familiar with his followers which will impede the process of rational decision making. As a result, we argue that there exists a functional proximity which allows the leader the necessary space in which to perform effective identity work and to hide the backstage aspects of leadership, while also allowing him an emotional buffer zone which will enable him to maintain the ability to see clearly and make rational decisions.

Proximity search heuristics for wind farm optimal layout

DEFF Research Database (Denmark)

Fischetti, Martina; Monaci, Michele

2016-01-01

A heuristic framework for turbine layout optimization in a wind farm is proposed that combines ad-hoc heuristics and mixed-integer linear programming. In our framework, large-scale mixed-integer programming models are used to iteratively refine the current best solution according to the recently...

ProxImaL: efficient image optimization using proximal algorithms

KAUST Repository

Heide, Felix; Diamond, Steven; Nieß ner, Matthias; Ragan-Kelley, Jonathan; Heidrich, Wolfgang; Wetzstein, Gordon

2016-01-01

domain-specific language and compiler for image optimization problems that makes it easy to experiment with different problem formulations and algorithm choices. The language uses proximal operators as the fundamental building blocks of a variety

Aether: leveraging linear programming for optimal cloud computing in genomics.

Science.gov (United States)

Luber, Jacob M; Tierney, Braden T; Cofer, Evan M; Patel, Chirag J; Kostic, Aleksandar D

2018-05-01

Across biology, we are seeing rapid developments in scale of data production without a corresponding increase in data analysis capabilities. Here, we present Aether (http://aether.kosticlab.org), an intuitive, easy-to-use, cost-effective and scalable framework that uses linear programming to optimally bid on and deploy combinations of underutilized cloud computing resources. Our approach simultaneously minimizes the cost of data analysis and provides an easy transition from users' existing HPC pipelines. Data utilized are available at https://pubs.broadinstitute.org/diabimmune and with EBI SRA accession ERP005989. Source code is available at (https://github.com/kosticlab/aether). Examples, documentation and a tutorial are available at http://aether.kosticlab.org. chirag_patel@hms.harvard.edu or aleksandar.kostic@joslin.harvard.edu. Supplementary data are available at Bioinformatics online.

Microgrid Reliability Modeling and Battery Scheduling Using Stochastic Linear Programming

Energy Technology Data Exchange (ETDEWEB)

Cardoso, Goncalo; Stadler, Michael; Siddiqui, Afzal; Marnay, Chris; DeForest, Nicholas; Barbosa-Povoa, Ana; Ferrao, Paulo

2013-05-23

This paper describes the introduction of stochastic linear programming into Operations DER-CAM, a tool used to obtain optimal operating schedules for a given microgrid under local economic and environmental conditions. This application follows previous work on optimal scheduling of a lithium-iron-phosphate battery given the output uncertainty of a 1 MW molten carbonate fuel cell. Both are in the Santa Rita Jail microgrid, located in Dublin, California. This fuel cell has proven unreliable, partially justifying the consideration of storage options. Several stochastic DER-CAM runs are executed to compare different scenarios to values obtained by a deterministic approach. Results indicate that using a stochastic approach provides a conservative yet more lucrative battery schedule. Lower expected energy bills result, given fuel cell outages, in potential savings exceeding 6percent.

PROXIMAL DISABILITY AND SPINAL DEFORMITY INDEX IN PATIENTS WITH PROXIMAL FEMUR FRACTURES

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Sylvio Mistro Neto

2015-12-01

Full Text Available Objective : To evaluate the quality of life related to the spine in patients with proximal femoral fractures. Methods : Study conducted in a tertiary public hospital in patients with proximal femoral fractures caused by low-energy trauma, through the Oswestry Disability Index questionnaire to asses complaints related to the spine at the time of life prior to the femoral fracture. The thoracic and lumbar spine of patients were also evaluated applying the radiographic index described by Gennant (Spinal Deformity Index, which assesses the number and severity of fractures. Results : Seventeen subjects completed the study. All had some degree of vertebral fracture. Patients were classified in the categories of severe and very severe disability in the questionnaire about quality of life. It was found that the higher SDI, the better the quality of life. Conclusion : There is a strong association of disability related to the spine in patients with proximal femoral fracture, and this complaint must be systematically evaluated in patients with appendicular fracture.

Proximal methods for the resolution of inverse problems: application to positron emission tomography

International Nuclear Information System (INIS)

Pustelnik, N.

2010-12-01

The objective of this work is to propose reliable, efficient and fast methods for minimizing convex criteria, that are found in inverse problems for imagery. We focus on restoration/reconstruction problems when data is degraded with both a linear operator and noise, where the latter is not assumed to be necessarily additive.The reliability of the method is ensured through the use of proximal algorithms, the convergence of which is guaranteed when a convex criterion is considered. Efficiency is sought through the choice of criteria adapted to the noise characteristics, the linear operators and the image specificities. Of particular interest are regularization terms based on total variation and/or sparsity of signal frame coefficients. As a consequence of the use of frames, two approaches are investigated, depending on whether the analysis or the synthesis formulation is chosen. Fast processing requirements lead us to consider proximal algorithms with a parallel structure. Theoretical results are illustrated on several large size inverse problems arising in image restoration, stereoscopy, multi-spectral imagery and decomposition into texture and geometry components. We focus on a particular application, namely Positron Emission Tomography (PET), which is particularly difficult because of the presence of a projection operator combined with Poisson noise, leading to highly corrupted data. To optimize the quality of the reconstruction, we make use of the spatio-temporal characteristics of brain tissue activity. (author)

A non-linear regression analysis program for describing electrophysiological data with multiple functions using Microsoft Excel.

Science.gov (United States)

Brown, Angus M

2006-04-01

The objective of this present study was to demonstrate a method for fitting complex electrophysiological data with multiple functions using the SOLVER add-in of the ubiquitous spreadsheet Microsoft Excel. SOLVER minimizes the difference between the sum of the squares of the data to be fit and the function(s) describing the data using an iterative generalized reduced gradient method. While it is a straightforward procedure to fit data with linear functions, and we have previously demonstrated a method of non-linear regression analysis of experimental data based upon a single function, it is more complex to fit data with multiple functions, usually requiring specialized expensive computer software. In this paper we describe an easily understood program for fitting experimentally acquired data, in this case the stimulus-evoked compound action potential from the mouse optic nerve, with multiple Gaussian functions. The program is flexible and can be applied to describe data with a wide variety of user-input functions.

Statistical mechanical analysis of linear programming relaxation for combinatorial optimization problems

Science.gov (United States)

Takabe, Satoshi; Hukushima, Koji

2016-05-01

Typical behavior of the linear programming (LP) problem is studied as a relaxation of the minimum vertex cover (min-VC), a type of integer programming (IP) problem. A lattice-gas model on the Erdös-Rényi random graphs of α -uniform hyperedges is proposed to express both the LP and IP problems of the min-VC in the common statistical mechanical model with a one-parameter family. Statistical mechanical analyses reveal for α =2 that the LP optimal solution is typically equal to that given by the IP below the critical average degree c =e in the thermodynamic limit. The critical threshold for good accuracy of the relaxation extends the mathematical result c =1 and coincides with the replica symmetry-breaking threshold of the IP. The LP relaxation for the minimum hitting sets with α ≥3 , minimum vertex covers on α -uniform random graphs, is also studied. Analytic and numerical results strongly suggest that the LP relaxation fails to estimate optimal values above the critical average degree c =e /(α -1 ) where the replica symmetry is broken.

Statistical mechanical analysis of linear programming relaxation for combinatorial optimization problems.

Science.gov (United States)

Takabe, Satoshi; Hukushima, Koji

2016-05-01

Typical behavior of the linear programming (LP) problem is studied as a relaxation of the minimum vertex cover (min-VC), a type of integer programming (IP) problem. A lattice-gas model on the Erdös-Rényi random graphs of α-uniform hyperedges is proposed to express both the LP and IP problems of the min-VC in the common statistical mechanical model with a one-parameter family. Statistical mechanical analyses reveal for α=2 that the LP optimal solution is typically equal to that given by the IP below the critical average degree c=e in the thermodynamic limit. The critical threshold for good accuracy of the relaxation extends the mathematical result c=1 and coincides with the replica symmetry-breaking threshold of the IP. The LP relaxation for the minimum hitting sets with α≥3, minimum vertex covers on α-uniform random graphs, is also studied. Analytic and numerical results strongly suggest that the LP relaxation fails to estimate optimal values above the critical average degree c=e/(α-1) where the replica symmetry is broken.

Fitting boxes to Manhattan scenes using linear integer programming

KAUST Repository

Li, Minglei

2016-02-19

We propose an approach for automatic generation of building models by assembling a set of boxes using a Manhattan-world assumption. The method first aligns the point cloud with a per-building local coordinate system, and then fits axis-aligned planes to the point cloud through an iterative regularization process. The refined planes partition the space of the data into a series of compact cubic cells (candidate boxes) spanning the entire 3D space of the input data. We then choose to approximate the target building by the assembly of a subset of these candidate boxes using a binary linear programming formulation. The objective function is designed to maximize the point cloud coverage and the compactness of the final model. Finally, all selected boxes are merged into a lightweight polygonal mesh model, which is suitable for interactive visualization of large scale urban scenes. Experimental results and a comparison with state-of-the-art methods demonstrate the effectiveness of the proposed framework.

PAPR reduction in FBMC using an ACE-based linear programming optimization

Science.gov (United States)

van der Neut, Nuan; Maharaj, Bodhaswar TJ; de Lange, Frederick; González, Gustavo J.; Gregorio, Fernando; Cousseau, Juan

2014-12-01

This paper presents four novel techniques for peak-to-average power ratio (PAPR) reduction in filter bank multicarrier (FBMC) modulation systems. The approach extends on current PAPR reduction active constellation extension (ACE) methods, as used in orthogonal frequency division multiplexing (OFDM), to an FBMC implementation as the main contribution. The four techniques introduced can be split up into two: linear programming optimization ACE-based techniques and smart gradient-project (SGP) ACE techniques. The linear programming (LP)-based techniques compensate for the symbol overlaps by utilizing a frame-based approach and provide a theoretical upper bound on achievable performance for the overlapping ACE techniques. The overlapping ACE techniques on the other hand can handle symbol by symbol processing. Furthermore, as a result of FBMC properties, the proposed techniques do not require side information transmission. The PAPR performance of the techniques is shown to match, or in some cases improve, on current PAPR techniques for FBMC. Initial analysis of the computational complexity of the SGP techniques indicates that the complexity issues with PAPR reduction in FBMC implementations can be addressed. The out-of-band interference introduced by the techniques is investigated. As a result, it is shown that the interference can be compensated for, whilst still maintaining decent PAPR performance. Additional results are also provided by means of a study of the PAPR reduction of the proposed techniques at a fixed clipping probability. The bit error rate (BER) degradation is investigated to ensure that the trade-off in terms of BER degradation is not too severe. As illustrated by exhaustive simulations, the SGP ACE-based technique proposed are ideal candidates for practical implementation in systems employing the low-complexity polyphase implementation of FBMC modulators. The methods are shown to offer significant PAPR reduction and increase the feasibility of FBMC as

Reactor Network Synthesis Using Coupled Genetic Algorithm with the Quasi-linear Programming Method

OpenAIRE

Soltani, H.; Shafiei, S.; Edraki, J.

2016-01-01

This research is an attempt to develop a new procedure for the synthesis of reactor networks (RNs) using a genetic algorithm (GA) coupled with the quasi-linear programming (LP) method. The GA is used to produce structural configuration, whereas continuous variables are handled using a quasi-LP formulation for finding the best objective function. Quasi-LP consists of LP together with a search loop to find the best reactor conversions (xi), as well as split and recycle ratios (yi). Quasi-LP rep...

Model Predictive Control for Linear Complementarity and Extended Linear Complementarity Systems

Directory of Open Access Journals (Sweden)

Bambang Riyanto

2005-11-01

Full Text Available In this paper, we propose model predictive control method for linear complementarity and extended linear complementarity systems by formulating optimization along prediction horizon as mixed integer quadratic program. Such systems contain interaction between continuous dynamics and discrete event systems, and therefore, can be categorized as hybrid systems. As linear complementarity and extended linear complementarity systems finds applications in different research areas, such as impact mechanical systems, traffic control and process control, this work will contribute to the development of control design method for those areas as well, as shown by three given examples.

Variability of United States Online Rehabilitation Protocols for Proximal Hamstring Tendon Repair

Science.gov (United States)

Lightsey, Harry M.; Kantrowitz, David E.; Swindell, Hasani W.; Trofa, David P.; Ahmad, Christopher S.; Lynch, T. Sean

2018-01-01

Background: The optimal postoperative rehabilitation protocol following repair of complete proximal hamstring tendon ruptures is the subject of ongoing investigation, with a need for more standardized regimens and evidence-based modalities. Purpose: To assess the variability across proximal hamstring tendon repair rehabilitation protocols published online by United States (US) orthopaedic teaching programs. Study Design: Cross-sectional study. Methods: Online proximal hamstring physical therapy protocols from US academic orthopaedic programs were reviewed. A web-based search using the search term complete proximal hamstring repair rehabilitation protocol provided an additional 14 protocols. A comprehensive scoring rubric was developed after review of all protocols and was used to assess each protocol for both the presence of various rehabilitation components and the point at which those components were introduced. Results: Of 50 rehabilitation protocols identified, 35 satisfied inclusion criteria and were analyzed. Twenty-five protocols (71%) recommended immediate postoperative bracing: 12 (34%) prescribed knee bracing, 8 (23%) prescribed hip bracing, and 5 (14%) did not specify the type of brace recommended. Fourteen protocols (40%) advised immediate nonweightbearing with crutches, while 16 protocols (46%) permitted immediate toe-touch weightbearing. Advancement to full weightbearing was allowed at a mean of 7.1 weeks (range, 4-12 weeks). Most protocols (80%) recommended gentle knee and hip passive range of motion and active range of motion, starting at a mean 1.4 weeks (range, 0-3 weeks) and 4.0 weeks (range, 0-6 weeks), respectively. However, only 6 protocols (17%) provided specific time points to initiate full hip and knee range of motion: a mean 8.0 weeks (range, 4-12 weeks) and 7.8 weeks (range, 0-12 weeks), respectively. Considerable variability was noted in the inclusion and timing of strengthening, stretching, proprioception, and cardiovascular exercises

A Mixed-Integer Linear Programming approach to wind farm layout and inter-array cable routing

DEFF Research Database (Denmark)

Fischetti, Martina; Leth, John-Josef; Borchersen, Anders Bech

2015-01-01

A Mixed-Integer Linear Programming (MILP) approach is proposed to optimize the turbine allocation and inter-array offshore cable routing. The two problems are considered with a two steps strategy, solving the layout problem first and then the cable problem. We give an introduction to both problems...... and present the MILP models we developed to solve them. To deal with interference in the onshore cases, we propose an adaptation of the standard Jensen’s model, suitable for 3D cases. A simple Stochastic Programming variant of our model allows us to consider different wind scenarios in the optimization...

A Mixed Integer Linear Programming Approach to Electrical Stimulation Optimization Problems.

Science.gov (United States)

Abouelseoud, Gehan; Abouelseoud, Yasmine; Shoukry, Amin; Ismail, Nour; Mekky, Jaidaa

2018-02-01

Electrical stimulation optimization is a challenging problem. Even when a single region is targeted for excitation, the problem remains a constrained multi-objective optimization problem. The constrained nature of the problem results from safety concerns while its multi-objectives originate from the requirement that non-targeted regions should remain unaffected. In this paper, we propose a mixed integer linear programming formulation that can successfully address the challenges facing this problem. Moreover, the proposed framework can conclusively check the feasibility of the stimulation goals. This helps researchers to avoid wasting time trying to achieve goals that are impossible under a chosen stimulation setup. The superiority of the proposed framework over alternative methods is demonstrated through simulation examples.

Quadratic-linear pattern in cancer fractional radiotherapy. Equations for a computering program

International Nuclear Information System (INIS)

Burgos, D.; Bullejos, J.; Garcia Puche, J.L.; Pedraza, V.

1990-01-01

Knowledge of equivalence between different tratment schemes with the same iso-effect is the essential thing in clinical cancer radiotherapy. For this purpose it is very useful the group of ideas derived from quadratic-linear pattern (Q-L) proposed in order to analyze cell survival curve to radiation. Iso-effect definition caused by several irradiation rules is done by extrapolated tolerance dose (ETD). Because equations for ETD are complex, a computering program have been carried out. In this paper, iso-effect equations for well defined therapeutic situations and flow diagram proposed for resolution, have been studied. (Author)

The use of linear programming to determine whether a formulated complementary food product can ensure adequate nutrients for 6- to 11-month-old Cambodian infants

DEFF Research Database (Denmark)

Skau, Jutta Kloppenborg Heick; Bunthang, Touch; Chamnan, Chhoun

2014-01-01

A new software tool, Optifood, developed by the WHO and based on linear programming (LP) analysis, has been developed to formulate food-based recommendations.......A new software tool, Optifood, developed by the WHO and based on linear programming (LP) analysis, has been developed to formulate food-based recommendations....

A generalized fuzzy credibility-constrained linear fractional programming approach for optimal irrigation water allocation under uncertainty

Science.gov (United States)

Zhang, Chenglong; Guo, Ping

2017-10-01

The vague and fuzzy parametric information is a challenging issue in irrigation water management problems. In response to this problem, a generalized fuzzy credibility-constrained linear fractional programming (GFCCFP) model is developed for optimal irrigation water allocation under uncertainty. The model can be derived from integrating generalized fuzzy credibility-constrained programming (GFCCP) into a linear fractional programming (LFP) optimization framework. Therefore, it can solve ratio optimization problems associated with fuzzy parameters, and examine the variation of results under different credibility levels and weight coefficients of possibility and necessary. It has advantages in: (1) balancing the economic and resources objectives directly; (2) analyzing system efficiency; (3) generating more flexible decision solutions by giving different credibility levels and weight coefficients of possibility and (4) supporting in-depth analysis of the interrelationships among system efficiency, credibility level and weight coefficient. The model is applied to a case study of irrigation water allocation in the middle reaches of Heihe River Basin, northwest China. Therefore, optimal irrigation water allocation solutions from the GFCCFP model can be obtained. Moreover, factorial analysis on the two parameters (i.e. λ and γ) indicates that the weight coefficient is a main factor compared with credibility level for system efficiency. These results can be effective for support reasonable irrigation water resources management and agricultural production.

A Global Optimization Algorithm for Sum of Linear Ratios Problem

Directory of Open Access Journals (Sweden)

Yuelin Gao

2013-01-01

Full Text Available We equivalently transform the sum of linear ratios programming problem into bilinear programming problem, then by using the linear characteristics of convex envelope and concave envelope of double variables product function, linear relaxation programming of the bilinear programming problem is given, which can determine the lower bound of the optimal value of original problem. Therefore, a branch and bound algorithm for solving sum of linear ratios programming problem is put forward, and the convergence of the algorithm is proved. Numerical experiments are reported to show the effectiveness of the proposed algorithm.

Proximal Probes Facility

Data.gov (United States)

Federal Laboratory Consortium — The Proximal Probes Facility consists of laboratories for microscopy, spectroscopy, and probing of nanostructured materials and their functional properties. At the...

CONTRIBUTION OF A LINEAR PROGRAMMING VBA MODULE TO STUDENTS PEFORMANCE

Directory of Open Access Journals (Sweden)

KUČÍRKOVÁ Lenka

2010-12-01

Full Text Available This paper deals with the application of freeware modules as a teaching support of Operations Research methods at the Department of Systems Engineering, Czech university of Life Sciences (CULS Prague. In particular, we concentrated on a linear programming module and measured the impact on student performance. The motivation for this evaluation is based on a current development of a new module that focuses on Traveling Salesman Problem. First, we explain the current situation both worldwide and in the Czech Republic and the CULS Prague. Subsequently, we describe the content of students’ exams and statistical methods applied to the evaluation. Finally, we analyze and generalize the obtained results. The students exams have show a positive impact of the modules. Further, our analysis has proven that this impact is statistically significant. The findings motivate us to made new modules for other methods.

Construction of Healthy and Palatable Diet for Low Socioeconomic Female Adults using Linear Programming

OpenAIRE

Roslee Rajikan; Nurul Izza Ahmad Zaidi; Siti Masitah Elias; Suzana Shahar; Zahara Abd Manaf; Noor Aini Md Yusoff

2017-01-01

Differences in socioeconomic profile may influences healthy food choices, particularly among individuals with low socioeconomic status. Thus, high-energy dense foods become the preferences compared to high nutritional content foods due to their cheaper price. The present study aims to develop healthy and palatable diet at the minimum cost based on Malaysian Dietary Guidelines 2010 and Recommended Nutrient Intake 2005 via linear programming. A total of 96 female adults from low socioeconomic f...

A novel approach based on preference-based index for interval bilevel linear programming problem.

Science.gov (United States)

Ren, Aihong; Wang, Yuping; Xue, Xingsi

2017-01-01

This paper proposes a new methodology for solving the interval bilevel linear programming problem in which all coefficients of both objective functions and constraints are considered as interval numbers. In order to keep as much uncertainty of the original constraint region as possible, the original problem is first converted into an interval bilevel programming problem with interval coefficients in both objective functions only through normal variation of interval number and chance-constrained programming. With the consideration of different preferences of different decision makers, the concept of the preference level that the interval objective function is preferred to a target interval is defined based on the preference-based index. Then a preference-based deterministic bilevel programming problem is constructed in terms of the preference level and the order relation [Formula: see text]. Furthermore, the concept of a preference δ -optimal solution is given. Subsequently, the constructed deterministic nonlinear bilevel problem is solved with the help of estimation of distribution algorithm. Finally, several numerical examples are provided to demonstrate the effectiveness of the proposed approach.

A novel approach based on preference-based index for interval bilevel linear programming problem

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Aihong Ren

2017-05-01

Full Text Available Abstract This paper proposes a new methodology for solving the interval bilevel linear programming problem in which all coefficients of both objective functions and constraints are considered as interval numbers. In order to keep as much uncertainty of the original constraint region as possible, the original problem is first converted into an interval bilevel programming problem with interval coefficients in both objective functions only through normal variation of interval number and chance-constrained programming. With the consideration of different preferences of different decision makers, the concept of the preference level that the interval objective function is preferred to a target interval is defined based on the preference-based index. Then a preference-based deterministic bilevel programming problem is constructed in terms of the preference level and the order relation ⪯ m w $\\preceq_{mw}$ . Furthermore, the concept of a preference δ-optimal solution is given. Subsequently, the constructed deterministic nonlinear bilevel problem is solved with the help of estimation of distribution algorithm. Finally, several numerical examples are provided to demonstrate the effectiveness of the proposed approach.

Possibility/Necessity-Based Probabilistic Expectation Models for Linear Programming Problems with Discrete Fuzzy Random Variables

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Hideki Katagiri

2017-10-01

Full Text Available This paper considers linear programming problems (LPPs where the objective functions involve discrete fuzzy random variables (fuzzy set-valued discrete random variables. New decision making models, which are useful in fuzzy stochastic environments, are proposed based on both possibility theory and probability theory. In multi-objective cases, Pareto optimal solutions of the proposed models are newly defined. Computational algorithms for obtaining the Pareto optimal solutions of the proposed models are provided. It is shown that problems involving discrete fuzzy random variables can be transformed into deterministic nonlinear mathematical programming problems which can be solved through a conventional mathematical programming solver under practically reasonable assumptions. A numerical example of agriculture production problems is given to demonstrate the applicability of the proposed models to real-world problems in fuzzy stochastic environments.

Neighborhoods and manageable proximity

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Stavros Stavrides

2011-08-01

Full Text Available The theatricality of urban encounters is above all a theatricality of distances which allow for the encounter. The absolute “strangeness” of the crowd (Simmel 1997: 74 expressed, in its purest form, in the absolute proximity of a crowded subway train, does not generally allow for any movements of approach, but only for nervous hostile reactions and submissive hypnotic gestures. Neither forced intersections in the course of pedestrians or vehicles, nor the instantaneous crossing of distances by the technology of live broadcasting and remote control give birth to places of encounter. In the forced proximity of the metropolitan crowd which haunted the city of the 19th and 20th century, as well as in the forced proximity of the tele-presence which haunts the dystopic prospect of the future “omnipolis” (Virilio 1997: 74, the necessary distance, which is the stage of an encounter between different instances of otherness, is dissipated.

Digital contrast subtraction radiography for proximal caries diagnosis

International Nuclear Information System (INIS)

Kang, Byung Cheol; Yoon, Suk Ja

2002-01-01

To determine whether subtraction images utilizing contrast media can improve the diagnostic performance of proximal caries diagnosis compared to conventional periapical radiographic images. Thirty-six teeth with 57 proximal surfaces were radiographied using a size no.2 RVG-ui sensor (Trophy Radiology, Marne-la-Vallee, France). The teeth immersed in water-soluble contrast media and subtraction images were taken. Each tooth was then sectioned for histologic examination. The digital radiographic images and subtraction images were examined and interpreted by three dentists for proximal caries. The results of the proximal caries diagnosis were then verified with the results of the histologic examination. The proximal caries sensitivity using digital subtraction radiography was significantly higher than simply examining a single digital radiograph. The sensitivity of the proximal dentinal carious lesion when analyzed with the subtraction radiograph and the radiograph together was higher than with the subtraction radiograph or the radiograph alone. The use of subtraction radiography with contrast media may be useful for detecting proximal dentinal carious lesions.

Nature beyond Linearity: Meteorological Variability and Jensen's Inequality Can Explain Mast Seeding Behavior

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Marcos Fernández-Martínez

2017-11-01

Full Text Available Mast seeding, the extremely variable and synchronized production of fruits, is a common reproductive behavior in plants. Weather is centrally involved in driving masting. Yet, it is often claimed that it cannot be the sole proximate cause of masting because weather is less variable than fruit production and because the shape of their distributions differ. We used computer simulations to demonstrate that the assumption that weather cannot be the main driver of masting was only valid for linear relationships between weather and fruit production. Non-linear relationships between interannual variability in weather and crop size, however, can account for the differences in their variability and the shape of their distributions because of Jensen's inequality. Exponential relationships with weather can increase the variability of fruit production, and sigmoidal relationships can produce bimodal distributions. These results challenge the idea that meteorological variability cannot be the main proximate driver of mast seeding, returning meteorological variability to the forefront of masting research.

Validation of a Quasi-Linear Numerical Model of a Pitching Wave Energy Converter in Close Proximity to a Fixed Structure

DEFF Research Database (Denmark)

López, Maria del Pilar Heras; Thomas, Sarah; Kramer, Morten Mejlhede

2017-01-01

attempting to validate a numerical model of a WEC using a variety of scaled physical tests in a waveflume. The technology used as a case study in this paper is a pitching WEC in close proximity to a fixed structure. Challenges are presented relating to waveflume effects and obtaining accurate physical input...

Calculus Rules for V-Proximal Subdifferentials in Smooth Banach Spaces

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Messaoud Bounkhel

2016-01-01

Full Text Available In 2010, Bounkhel et al. introduced new proximal concepts (analytic proximal subdifferential, geometric proximal subdifferential, and proximal normal cone in reflexive smooth Banach spaces. They proved, in p-uniformly convex and q-uniformly smooth Banach spaces, the density theorem for the new concepts of proximal subdifferential and various important properties for both proximal subdifferential concepts and the proximal normal cone concept. In this paper, we establish calculus rules (fuzzy sum rule and chain rule for both proximal subdifferentials and we prove the Bishop-Phelps theorem for the proximal normal cone. The limiting concept for both proximal subdifferentials and for the proximal normal cone is defined and studied. We prove that both limiting constructions coincide with the Mordukhovich constructions under some assumptions on the space. Applications to nonconvex minimisation problems and nonconvex variational inequalities are established.

Sport-Specific Training Targeting the Proximal Segments and Throwing Velocity in Collegiate Throwing Athletes

Science.gov (United States)

Palmer, Thomas; Uhl, Timothy L.; Howell, Dana; Hewett, Timothy E.; Viele, Kert; Mattacola, Carl G.

2015-01-01

Context The ability to generate, absorb, and transmit forces through the proximal segments of the pelvis, spine, and trunk has been proposed to influence sport performance, yet traditional training techniques targeting the proximal segments have had limited success improving sport-specific performance. Objective To investigate the effects of a traditional endurance-training program and a sport-specific power-training program targeting the muscles that support the proximal segments and throwing velocity. Design Randomized controlled clinical trial. Setting University research laboratory and gymnasium. Patients or Other Participants A total of 46 (age = 20 ± 1.3 years, height = 175.7 ± 8.7 cm) healthy National Collegiate Athletic Association Division III female softball (n = 17) and male baseball (n = 29) players. Intervention(s) Blocked stratification for sex and position was used to randomly assign participants to 1 of 2 training groups for 7 weeks: a traditional endurance-training group (ET group; n = 21) or a power-stability–training group (PS group; n = 25). Mean Outcome Measure(s) The change score in peak throwing velocity (km/h) normalized for body weight (BW; kilograms) and change score in tests that challenge the muscles of the proximal segments normalized for BW (kilograms). We used 2-tailed independent-samples t tests to compare differences between the change scores. Results The peak throwing velocity (ET group = 0.01 ± 0.1 km/h/kg of BW, PS group = 0.08 ± 0.03 km/h/kg of BW; P < .001) and muscle power outputs for the chop (ET group = 0.22 ± 0.91 W/kg of BW, PS group = 1.3 ± 0.91 W/kg of BW; P < .001) and lift (ET group = 0.59 ± 0.67 W/kg of BW, PS group = 1.4 ± 0.87 W/kg of BW; P < .001) tests were higher at postintervention in the PT than in the ET group. Conclusions An improvement in throwing velocity occurred simultaneously with measures of muscular endurance and power after a sport-specific training regimen targeting the proximal segments

INFORMATION SECURITY RISKS OPTIMIZATION IN CLOUDY SERVICES ON THE BASIS OF LINEAR PROGRAMMING

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I. A. Zikratov

2013-01-01

Full Text Available The paper discusses theoretical aspects of secure cloud services creation for information processing of various confidentiality degrees. A new approach to the reasoning of information security composition in distributed computing structures is suggested, presenting the problem of risk assessment as an extreme problem of decisionmaking. Linear programming method application is proved to minimize the risk of information security for given performance security in compliance with the economic balance for the maintenance of security facilities and cost of services. An example is given to illustrate the obtained theoretical results.

Integrating Linear Programming and Analytical Hierarchical ...

African Journals Online (AJOL)

Study area is about 28000 ha of Keleibar- Chai Watershed, located in eastern Azerbaijan, Iran. Socio-economic information collected through a two-stage survey of 19 villages, including 300 samples. Thematic maps also have summarized Ecological factors, including physical and economic data. A comprehensive Linear ...

Linear programming model for solution of matrix game with payoffs trapezoidal intuitionistic fuzzy number

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Darunee Hunwisai

2017-01-01

Full Text Available In this work, we considered two-person zero-sum games with fuzzy payoffs and matrix games with payoffs of trapezoidal intuitionistic fuzzy numbers (TrIFNs. The concepts of TrIFNs and their arithmetic operations were used. The cut-set based method for matrix game with payoffs of TrIFNs was also considered. Compute the interval-type value of any alfa-constrategies by simplex method for linear programming. The proposed method is illustrated with a numerical example.

The evaluation of multi-element personal dosemeters using the linear programming method

International Nuclear Information System (INIS)

Kragh, P.; Ambrosi, P.; Boehm, J.; Hilgers, G.

1996-01-01

Multi-element dosemeters are frequently used in individual monitoring. Each element can be regarded as an individual dosemeter with its own individual dose measurement value. In general, the individual dose values of one dosemeter vary according to the exposure conditions, i. e. the energy and angle of incidence of the radiation. The (final) dose measurement value of the personal dosemeter is calculated from the individual dose values by means of an evaluation algorithm. The best possible dose value, i.e. that of the smallest systematic (type B) uncertainty if the exposure conditions are changed in the dosemeter's rated range of use, is obtained by the method of linear programming. (author)

Analisis Peramalan Penjualan dan Penggunaan Metode Linear Programming dan Decision Tree Guna Mengoptimalkan Keuntungan pada PT Primajaya Pantes Garment

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Inti Sariani Jianta Djie

2013-09-01

Full Text Available Primajaya Pantes Garment is a company that runs its business in garment sector. However, due to various numbers of requests each month, the company is difficult to determine the amount of production per month that is appropriate to maximize profits. The purpose of this study is to determine the appropriate forecasting method that can be used as a reference to determine the amount of production in the next period and to find a combination of products to maximize profits. Research used forecasting methods, including naive method, moving averages, weighted moving averages, exponential smoothing, exponential smoothing with trend, and linear regression. In addition, this study also used Linear Programming method with Simplex method to determine the best combination of products for the company and to choose a decision using a decision tree to determine which alternative should be done by the company. Results of this study found that the linear regression method is the most appropriate method in determining the forecast demand in the next period. While in the Linear Programming method, constraints used were the constraints of raw materials, labor hours, and limited demand for the product. The result of the decision tree is to increase production capacity.

Predicting Performance in Higher Education Using Proximal Predictors

Science.gov (United States)

Niessen, A. Susan M.; Meijer, Rob R.; Tendeiro, Jorge N.

2016-01-01

We studied the validity of two methods for predicting academic performance and student-program fit that were proximal to important study criteria. Applicants to an undergraduate psychology program participated in a selection procedure containing a trial-studying test based on a work sample approach, and specific skills tests in English and math. Test scores were used to predict academic achievement and progress after the first year, achievement in specific course types, enrollment, and dropout after the first year. All tests showed positive significant correlations with the criteria. The trial-studying test was consistently the best predictor in the admission procedure. We found no significant differences between the predictive validity of the trial-studying test and prior educational performance, and substantial shared explained variance between the two predictors. Only applicants with lower trial-studying scores were significantly less likely to enroll in the program. In conclusion, the trial-studying test yielded predictive validities similar to that of prior educational performance and possibly enabled self-selection. In admissions aimed at student-program fit, or in admissions in which past educational performance is difficult to use, a trial-studying test is a good instrument to predict academic performance. PMID:27073859

Biomechanical evaluation of straight antegrade nailing in proximal humeral fractures: the rationale of the "proximal anchoring point".

Science.gov (United States)

Euler, Simon A; Petri, Maximilian; Venderley, Melanie B; Dornan, Grant J; Schmoelz, Werner; Turnbull, Travis Lee; Plecko, Michael; Kralinger, Franz S; Millett, Peter J

2017-09-01

Varus failure is one of the most common failure modes following surgical treatment of proximal humeral fractures. Straight antegrade nails (SAN) theoretically provide increased stability by anchoring to the densest zone of the proximal humerus (subchondral zone) with the end of the nail. The aim of this study was to biomechanically investigate the characteristics of this "proximal anchoring point" (PAP). We hypothesized that the PAP would improve stability compared to the same construct without the PAP. Straight antegrade humeral nailing was performed in 20 matched pairs of human cadaveric humeri for a simulated unstable two-part fracture. Biomechanical testing, with stepwise increasing cyclic axial loading (50-N increments each 100 cycles) at an angle of 20° abduction revealed significantly higher median loads to failure for SAN constructs with the PAP (median, 450 N; range, 200-1.000 N) compared to those without the PAP (median, 325 N; range, 100-500 N; p = 0.009). SAN constructs with press-fit proximal extensions (endcaps) showed similar median loads to failure (median, 400 N; range, 200-650 N), when compared to the undersized, commercially available SAN endcaps (median, 450 N; range, 200-600 N; p = 0.240). The PAP provided significantly increased stability in SAN constructs compared to the same setup without this additional proximal anchoring point. Varus-displacing forces to the humeral head were superiorly reduced in this setting. This study provides biomechanical evidence for the "proximal anchoring point's" rationale. Straight antegrade humeral nailing may be beneficial for patients undergoing surgical treatment for unstable proximal humeral fractures to decrease secondary varus displacement and thus potentially reduce revision rates.

Approximating high-dimensional dynamics by barycentric coordinates with linear programming

Energy Technology Data Exchange (ETDEWEB)

Hirata, Yoshito, E-mail: yoshito@sat.t.u-tokyo.ac.jp; Aihara, Kazuyuki; Suzuki, Hideyuki [Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505 (Japan); Department of Mathematical Informatics, The University of Tokyo, Bunkyo-ku, Tokyo 113-8656 (Japan); CREST, JST, 4-1-8 Honcho, Kawaguchi, Saitama 332-0012 (Japan); Shiro, Masanori [Department of Mathematical Informatics, The University of Tokyo, Bunkyo-ku, Tokyo 113-8656 (Japan); Mathematical Neuroinformatics Group, Advanced Industrial Science and Technology, Tsukuba, Ibaraki 305-8568 (Japan); Takahashi, Nozomu; Mas, Paloma [Center for Research in Agricultural Genomics (CRAG), Consorci CSIC-IRTA-UAB-UB, Barcelona 08193 (Spain)

2015-01-15

The increasing development of novel methods and techniques facilitates the measurement of high-dimensional time series but challenges our ability for accurate modeling and predictions. The use of a general mathematical model requires the inclusion of many parameters, which are difficult to be fitted for relatively short high-dimensional time series observed. Here, we propose a novel method to accurately model a high-dimensional time series. Our method extends the barycentric coordinates to high-dimensional phase space by employing linear programming, and allowing the approximation errors explicitly. The extension helps to produce free-running time-series predictions that preserve typical topological, dynamical, and/or geometric characteristics of the underlying attractors more accurately than the radial basis function model that is widely used. The method can be broadly applied, from helping to improve weather forecasting, to creating electronic instruments that sound more natural, and to comprehensively understanding complex biological data.

Approximating high-dimensional dynamics by barycentric coordinates with linear programming.

Science.gov (United States)

Hirata, Yoshito; Shiro, Masanori; Takahashi, Nozomu; Aihara, Kazuyuki; Suzuki, Hideyuki; Mas, Paloma

2015-01-01

The increasing development of novel methods and techniques facilitates the measurement of high-dimensional time series but challenges our ability for accurate modeling and predictions. The use of a general mathematical model requires the inclusion of many parameters, which are difficult to be fitted for relatively short high-dimensional time series observed. Here, we propose a novel method to accurately model a high-dimensional time series. Our method extends the barycentric coordinates to high-dimensional phase space by employing linear programming, and allowing the approximation errors explicitly. The extension helps to produce free-running time-series predictions that preserve typical topological, dynamical, and/or geometric characteristics of the underlying attractors more accurately than the radial basis function model that is widely used. The method can be broadly applied, from helping to improve weather forecasting, to creating electronic instruments that sound more natural, and to comprehensively understanding complex biological data.

Approximating high-dimensional dynamics by barycentric coordinates with linear programming

International Nuclear Information System (INIS)

Hirata, Yoshito; Aihara, Kazuyuki; Suzuki, Hideyuki; Shiro, Masanori; Takahashi, Nozomu; Mas, Paloma

2015-01-01

The increasing development of novel methods and techniques facilitates the measurement of high-dimensional time series but challenges our ability for accurate modeling and predictions. The use of a general mathematical model requires the inclusion of many parameters, which are difficult to be fitted for relatively short high-dimensional time series observed. Here, we propose a novel method to accurately model a high-dimensional time series. Our method extends the barycentric coordinates to high-dimensional phase space by employing linear programming, and allowing the approximation errors explicitly. The extension helps to produce free-running time-series predictions that preserve typical topological, dynamical, and/or geometric characteristics of the underlying attractors more accurately than the radial basis function model that is widely used. The method can be broadly applied, from helping to improve weather forecasting, to creating electronic instruments that sound more natural, and to comprehensively understanding complex biological data

Using Set Covering with Item Sampling to Analyze the Infeasibility of Linear Programming Test Assembly Models

Science.gov (United States)

Huitzing, Hiddo A.

2004-01-01

This article shows how set covering with item sampling (SCIS) methods can be used in the analysis and preanalysis of linear programming models for test assembly (LPTA). LPTA models can construct tests, fulfilling a set of constraints set by the test assembler. Sometimes, no solution to the LPTA model exists. The model is then said to be…

Sequential computation of elementary modes and minimal cut sets in genome-scale metabolic networks using alternate integer linear programming

Energy Technology Data Exchange (ETDEWEB)

Song, Hyun-Seob; Goldberg, Noam; Mahajan, Ashutosh; Ramkrishna, Doraiswami

2017-03-27

Elementary (flux) modes (EMs) have served as a valuable tool for investigating structural and functional properties of metabolic networks. Identification of the full set of EMs in genome-scale networks remains challenging due to combinatorial explosion of EMs in complex networks. It is often, however, that only a small subset of relevant EMs needs to be known, for which optimization-based sequential computation is a useful alternative. Most of the currently available methods along this line are based on the iterative use of mixed integer linear programming (MILP), the effectiveness of which significantly deteriorates as the number of iterations builds up. To alleviate the computational burden associated with the MILP implementation, we here present a novel optimization algorithm termed alternate integer linear programming (AILP). Results: Our algorithm was designed to iteratively solve a pair of integer programming (IP) and linear programming (LP) to compute EMs in a sequential manner. In each step, the IP identifies a minimal subset of reactions, the deletion of which disables all previously identified EMs. Thus, a subsequent LP solution subject to this reaction deletion constraint becomes a distinct EM. In cases where no feasible LP solution is available, IP-derived reaction deletion sets represent minimal cut sets (MCSs). Despite the additional computation of MCSs, AILP achieved significant time reduction in computing EMs by orders of magnitude. The proposed AILP algorithm not only offers a computational advantage in the EM analysis of genome-scale networks, but also improves the understanding of the linkage between EMs and MCSs.

Periodic inventory system in cafeteria using linear programming

Science.gov (United States)

Usop, Mohd Fais; Ishak, Ruzana; Hamdan, Ahmad Ridhuan

2017-11-01

Inventory management is an important factor in running a business. It plays a big role of managing the stock in cafeteria. If the inventories are failed to be managed wisely, it will affect the profit of the cafeteria. Therefore, the purpose of this study is to find the solution of the inventory management in cafeteria. Most of the cafeteria in Malaysia did not manage their stock well. Therefore, this study is to propose a database system of inventory management and to develop the inventory model in cafeteria management. In this study, new database system to improve the management of the stock in a weekly basis will be provided using Linear Programming Model to get the optimal range of the inventory needed for selected categories. Data that were collected by using the Periodic Inventory System at the end of the week within three months period being analyzed by using the Food Stock-take Database. The inventory model was developed from the collected data according to the category of the inventory in the cafeteria. Results showed the effectiveness of using the Periodic Inventory System and will be very helpful to the cafeteria management in organizing the inventory. Moreover, the findings in this study can reduce the cost of operation and increased the profit.

From diets to foods: using linear programming to formulate a nutritious, minimum-cost porridge mix for children aged 1 to 2 years.

Science.gov (United States)

De Carvalho, Irene Stuart Torrié; Granfeldt, Yvonne; Dejmek, Petr; Håkansson, Andreas

2015-03-01

Linear programming has been used extensively as a tool for nutritional recommendations. Extending the methodology to food formulation presents new challenges, since not all combinations of nutritious ingredients will produce an acceptable food. Furthermore, it would help in implementation and in ensuring the feasibility of the suggested recommendations. To extend the previously used linear programming methodology from diet optimization to food formulation using consistency constraints. In addition, to exemplify usability using the case of a porridge mix formulation for emergency situations in rural Mozambique. The linear programming method was extended with a consistency constraint based on previously published empirical studies on swelling of starch in soft porridges. The new method was exemplified using the formulation of a nutritious, minimum-cost porridge mix for children aged 1 to 2 years for use as a complete relief food, based primarily on local ingredients, in rural Mozambique. A nutritious porridge fulfilling the consistency constraints was found; however, the minimum cost was unfeasible with local ingredients only. This illustrates the challenges in formulating nutritious yet economically feasible foods from local ingredients. The high cost was caused by the high cost of mineral-rich foods. A nutritious, low-cost porridge that fulfills the consistency constraints was obtained by including supplements of zinc and calcium salts as ingredients. The optimizations were successful in fulfilling all constraints and provided a feasible porridge, showing that the extended constrained linear programming methodology provides a systematic tool for designing nutritious foods.

Prediction of protein interaction hot spots using rough set-based multiple criteria linear programming.

Science.gov (United States)

Chen, Ruoying; Zhang, Zhiwang; Wu, Di; Zhang, Peng; Zhang, Xinyang; Wang, Yong; Shi, Yong

2011-01-21

Protein-protein interactions are fundamentally important in many biological processes and it is in pressing need to understand the principles of protein-protein interactions. Mutagenesis studies have found that only a small fraction of surface residues, known as hot spots, are responsible for the physical binding in protein complexes. However, revealing hot spots by mutagenesis experiments are usually time consuming and expensive. In order to complement the experimental efforts, we propose a new computational approach in this paper to predict hot spots. Our method, Rough Set-based Multiple Criteria Linear Programming (RS-MCLP), integrates rough sets theory and multiple criteria linear programming to choose dominant features and computationally predict hot spots. Our approach is benchmarked by a dataset of 904 alanine-mutated residues and the results show that our RS-MCLP method performs better than other methods, e.g., MCLP, Decision Tree, Bayes Net, and the existing HotSprint database. In addition, we reveal several biological insights based on our analysis. We find that four features (the change of accessible surface area, percentage of the change of accessible surface area, size of a residue, and atomic contacts) are critical in predicting hot spots. Furthermore, we find that three residues (Tyr, Trp, and Phe) are abundant in hot spots through analyzing the distribution of amino acids. Copyright © 2010 Elsevier Ltd. All rights reserved.

Finite element historical deformation analysis in piecewise linear plasticity by mathematical programming

International Nuclear Information System (INIS)

De Donato, O.; Parisi, M.A.

1977-01-01

When loads increase proportionally beyond the elastic limit in the presence of elastic-plastic piecewise-linear constitutive laws, the problem of finding the whole evolution of the plastic strain and displacements of structures was recently shown to be amenable to a parametric linear complementary problem (PLCP) in which the parameter is represented by the load factor, the matrix is symmetric positive definite or at least semi-definite (for perfect plasticity) and the variables with a direct mechanical meaning are the plastic multipliers. With reference to plane trusses and frames with elastic-plastic linear work-hardening material behaviour numerical solutions were also fairly efficiently obtained using a recent mathematical programming algorithm (due to R.W. Cottle) which is able to provide the whole deformation history of the structure and, at the same time to rule out local unloadings along the given proportional loading process by means of 'a priori' checks carried out before each pivotal step of the procedure. Hence it becomes possible to use the holonomic (reversible, path-independent) constitutive laws in finite terms and to benefit by all the relevant numerical and computational advantages despite the non-holonomic nature of plastic behaviour. In the present paper the method of solution is re-examined in view to overcome an important drawback of the algorithm deriving from the size of PLCP fully populated matrix when structural problems with large number of variables are considered and, consequently, the updating, the storing or, generally, the handling of the current tableau may become prohibitive. (Auth.)

Proximity Operations and Docking Sensor Development

Science.gov (United States)

Howard, Richard T.; Bryan, Thomas C.; Brewster, Linda L.; Lee, James E.

2009-01-01

The Next Generation Advanced Video Guidance Sensor (NGAVGS) has been under development for the last three years as a long-range proximity operations and docking sensor for use in an Automated Rendezvous and Docking (AR&D) system. The first autonomous rendezvous and docking in the history of the U.S. Space Program was successfully accomplished by Orbital Express, using the Advanced Video Guidance Sensor (AVGS) as the primary docking sensor. That flight proved that the United States now has a mature and flight proven sensor technology for supporting Crew Exploration Vehicles (CEV) and Commercial Orbital Transport Systems (COTS) Automated Rendezvous and Docking (AR&D). NASA video sensors have worked well in the past: the AVGS used on the Demonstration of Autonomous Rendezvous Technology (DART) mission operated successfully in spot mode out to 2 km, and the first generation rendezvous and docking sensor, the Video Guidance Sensor (VGS), was developed and successfully flown on Space Shuttle flights in 1997 and 1998. 12 Parts obsolescence issues prevent the construction of more AVGS units, and the next generation sensor was updated to allow it to support the CEV and COTS programs. The flight proven AR&D sensor has been redesigned to update parts and add additional capabilities for CEV and COTS with the development of the Next Generation AVGS at the Marshall Space Flight Center. The obsolete imager and processor are being replaced with new radiation tolerant parts. In addition, new capabilities include greater sensor range, auto ranging capability, and real-time video output. This paper presents some sensor hardware trades, use of highly integrated laser components, and addresses the needs of future vehicles that may rendezvous and dock with the International Space Station (ISS) and other Constellation vehicles. It also discusses approaches for upgrading AVGS to address parts obsolescence, and concepts for minimizing the sensor footprint, weight, and power requirements

Giant proximity effect in ferromagnetic bilayers

Science.gov (United States)

Ramos, Silvia; Charlton, Tim; Quintanilla, Jorge; Suter, Andreas; Moodera, Jagadeesh; Prokscha, Thomas; Salman, Zaher; Forgan, Ted

2013-03-01

The proximity effect is a phenomenon where an ordered state leaks from a material into an adjacent one over some finite distance, ξ. For superconductors, this distance is ~ the coherence length. Nevertheless much longer-range, ``giant'' proximity effects have been observed in cuprate junctions. This surprising effect can be understood as a consequence of critical opalescence. Since this occurs near all second order phase transitions, giant proximity effects should be very general and, in particular, they should be present in magnetic systems. The ferromagnetic proximity effect has the advantage that its order parameter (magnetization) can be observed directly. We investigate the above phenomenon in Co/EuS bilayer films, where both materials undergo ferromagnetic transitions but at rather different temperatures (bulk TC of 1400K for Co and 16.6K for EuS). A dramatic increase in the range of the proximity effect is expected near the TC of EuS. We present the results of our measurements of the magnetization profiles as a function of temperature, carried out using the complementary techniques of low energy muon rotation and polarized neutron reflectivity. Work supported by EPSRC, STFC and ONR grant N00014-09-1-0177 and NSF grant DMR 0504158.

An Improved Search Approach for Solving Non-Convex Mixed-Integer Non Linear Programming Problems

Science.gov (United States)

Sitopu, Joni Wilson; Mawengkang, Herman; Syafitri Lubis, Riri

2018-01-01

The nonlinear mathematical programming problem addressed in this paper has a structure characterized by a subset of variables restricted to assume discrete values, which are linear and separable from the continuous variables. The strategy of releasing nonbasic variables from their bounds, combined with the “active constraint” method, has been developed. This strategy is used to force the appropriate non-integer basic variables to move to their neighbourhood integer points. Successful implementation of these algorithms was achieved on various test problems.

Explicit/multi-parametric model predictive control (MPC) of linear discrete-time systems by dynamic and multi-parametric programming

KAUST Repository

Kouramas, K.I.

2011-08-01

This work presents a new algorithm for solving the explicit/multi- parametric model predictive control (or mp-MPC) problem for linear, time-invariant discrete-time systems, based on dynamic programming and multi-parametric programming techniques. The algorithm features two key steps: (i) a dynamic programming step, in which the mp-MPC problem is decomposed into a set of smaller subproblems in which only the current control, state variables, and constraints are considered, and (ii) a multi-parametric programming step, in which each subproblem is solved as a convex multi-parametric programming problem, to derive the control variables as an explicit function of the states. The key feature of the proposed method is that it overcomes potential limitations of previous methods for solving multi-parametric programming problems with dynamic programming, such as the need for global optimization for each subproblem of the dynamic programming step. © 2011 Elsevier Ltd. All rights reserved.

Aspect-object alignment with Integer Linear Programming in opinion mining.

Directory of Open Access Journals (Sweden)

Yanyan Zhao

Full Text Available Target extraction is an important task in opinion mining. In this task, a complete target consists of an aspect and its corresponding object. However, previous work has always simply regarded the aspect as the target itself and has ignored the important "object" element. Thus, these studies have addressed incomplete targets, which are of limited use for practical applications. This paper proposes a novel and important sentiment analysis task, termed aspect-object alignment, to solve the "object neglect" problem. The objective of this task is to obtain the correct corresponding object for each aspect. We design a two-step framework for this task. We first provide an aspect-object alignment classifier that incorporates three sets of features, namely, the basic, relational, and special target features. However, the objects that are assigned to aspects in a sentence often contradict each other and possess many complicated features that are difficult to incorporate into a classifier. To resolve these conflicts, we impose two types of constraints in the second step: intra-sentence constraints and inter-sentence constraints. These constraints are encoded as linear formulations, and Integer Linear Programming (ILP is used as an inference procedure to obtain a final global decision that is consistent with the constraints. Experiments on a corpus in the camera domain demonstrate that the three feature sets used in the aspect-object alignment classifier are effective in improving its performance. Moreover, the classifier with ILP inference performs better than the classifier without it, thereby illustrating that the two types of constraints that we impose are beneficial.

Aspect-object alignment with Integer Linear Programming in opinion mining.

Science.gov (United States)

Zhao, Yanyan; Qin, Bing; Liu, Ting; Yang, Wei

2015-01-01

Target extraction is an important task in opinion mining. In this task, a complete target consists of an aspect and its corresponding object. However, previous work has always simply regarded the aspect as the target itself and has ignored the important "object" element. Thus, these studies have addressed incomplete targets, which are of limited use for practical applications. This paper proposes a novel and important sentiment analysis task, termed aspect-object alignment, to solve the "object neglect" problem. The objective of this task is to obtain the correct corresponding object for each aspect. We design a two-step framework for this task. We first provide an aspect-object alignment classifier that incorporates three sets of features, namely, the basic, relational, and special target features. However, the objects that are assigned to aspects in a sentence often contradict each other and possess many complicated features that are difficult to incorporate into a classifier. To resolve these conflicts, we impose two types of constraints in the second step: intra-sentence constraints and inter-sentence constraints. These constraints are encoded as linear formulations, and Integer Linear Programming (ILP) is used as an inference procedure to obtain a final global decision that is consistent with the constraints. Experiments on a corpus in the camera domain demonstrate that the three feature sets used in the aspect-object alignment classifier are effective in improving its performance. Moreover, the classifier with ILP inference performs better than the classifier without it, thereby illustrating that the two types of constraints that we impose are beneficial.

Effect of camber and thickness on the aerodynamic properties of an airfoil in ground proximity

International Nuclear Information System (INIS)

Rad, M.; Kazemi, F. J.

2001-01-01

A linear vortex panel method is extended to include the effect of ground proximity on the aerodynamic properties of two dimensional airfoils. The image method is used to model the ground effect. According to the results, lift coefficient of an airfoil may increase or decrease in ground effect based on a combinative effect of its camber, thickness, angle of attack and ground clearance. Airfoils with different section parameters are analysed and their relative effectiveness are compared

Application of mixed-integer linear programming in a car seats assembling process

Directory of Open Access Journals (Sweden)

Jorge Iván Perez Rave

2011-12-01

Full Text Available In this paper, a decision problem involving a car parts manufacturing company is modeled in order to prepare the company for an increase in demand. Mixed-integer linear programming was used with the following decision variables: creating a second shift, purchasing additional equipment, determining the required work force, and other alternatives involving new manners of work distribution that make it possible to separate certain operations from some workplaces and integrate them into others to minimize production costs. The model was solved using GAMS. The solution consisted of programming 19 workers under a configuration that merges two workplaces and separates some operations from some workplaces. The solution did not involve purchasing additional machinery or creating a second shift. As a result, the manufacturing paradigms that had been valid in the company for over 14 years were broken. This study allowed the company to increase its productivity and obtain significant savings. It also shows the benefits of joint work between academia and companies, and provides useful information for professors, students and engineers regarding production and continuous improvement.

A linear programming algorithm to test for jamming in hard-sphere packings

International Nuclear Information System (INIS)

Donev, Aleksandar; Torquato, Salvatore.; Stillinger, Frank H.; Connelly, Robert

2004-01-01

Jamming in hard-particle packings has been the subject of considerable interest in recent years. In a paper by Torquato and Stillinger [J. Phys. Chem. B 105 (2001)], a classification scheme of jammed packings into hierarchical categories of locally, collectively and strictly jammed configurations has been proposed. They suggest that these jamming categories can be tested using numerical algorithms that analyze an equivalent contact network of the packing under applied displacements, but leave the design of such algorithms as a future task. In this work, we present a rigorous and practical algorithm to assess whether an ideal hard-sphere packing in two or three dimensions is jammed according to the aforementioned categories. The algorithm is based on linear programming and is applicable to regular as well as random packings of finite size with hard-wall and periodic boundary conditions. If the packing is not jammed, the algorithm yields representative multi-particle unjamming motions. Furthermore, we extend the jamming categories and the testing algorithm to packings with significant interparticle gaps. We describe in detail two variants of the proposed randomized linear programming approach to test for jamming in hard-sphere packings. The first algorithm treats ideal packings in which particles form perfect contacts. Another algorithm treats the case of jamming in packings with significant interparticle gaps. This extended algorithm allows one to explore more fully the nature of the feasible particle displacements. We have implemented the algorithms and applied them to ordered as well as random packings of circular disks and spheres with periodic boundary conditions. Some representative results for large disordered disk and sphere packings are given, but more robust and efficient implementations as well as further applications (e.g., non-spherical particles) are anticipated for the future

Quantum Proximity Resonances

International Nuclear Information System (INIS)

Heller, E.J.

1996-01-01

It is well known that at long wavelengths λ an s-wave scatterer can have a scattering cross section σ on the order of λ 2 , much larger than its physical size, as measured by the range of its potential. Very interesting phenomena can arise when two or more identical scatterers are placed close together, well within one wavelength. We show that, for a pair of identical scatterers, an extremely narrow p-wave open-quote open-quote proximity close-quote close-quote resonance develops from a broader s-wave resonance of the individual scatterers. A new s-wave resonance of the pair also appears. The relation of these proximity resonances (so called because they appear when the scatterers are close together) to the Thomas and Efimov effects is discussed. copyright 1996 The American Physical Society

Early results for treatment of two- and three-part fractures of the proximal humerus using Contours PHP (proximal humeral plate).

Science.gov (United States)

Biazzo, Alessio; Cardile, Carlo; Brunelli, Luca; Ragni, Paolo; Clementi, Daniele

2017-04-28

The management of displaced 2- and 3-part fractures of the proximal humerus is controversial, both in younger and in elderly patients. The purpose of this paper is to evaluate the functional results of the Contours Proximal Humerus Plate (OrthofixR, Bussolengo,Verona, Italy), for the treatment of displaced 2- and 3-part fractures of the proximal humerus. We retrospectively reviewed 55 patients with proximal humerus fractures, who underwent osteosynthesis with Contours Proximal Humerus Plate from December 2011 to March 2015. We had 21 patients with 2-part fractures and with an average age of 67.1 years and 34 patients with 3-part fractures, with average age of 63.6 years. The average union time was 3 months. The mean Constant score was 67 for 2-part fracture group and 64.9 for 3-part fracture group. The difference was not statistically significant (p = 0.18). The overall complication rate was 14.5 %. Six patients underwent additional surgery (10.9%). The most frequent major complication was secondary loss of reduction following varus collapse of the fracture (2 cases). In these patients, there was loss of medial hinge integrity due to impaction and osteoporosis. The placement of the main locking screw in the calcar area to provide inferomedial support is the rational of the Contours Proximal Humerus Plate. Osteosynthesis with Contours Proximal Humerus Plate is a safe system for treating displaced 2- and 3-part fractures of the proximal humerus, with good functional results and complication rates comparable to those reported in the literature.

SAS macro programs for geographically weighted generalized linear modeling with spatial point data: applications to health research.

Science.gov (United States)

Chen, Vivian Yi-Ju; Yang, Tse-Chuan

2012-08-01

An increasing interest in exploring spatial non-stationarity has generated several specialized analytic software programs; however, few of these programs can be integrated natively into a well-developed statistical environment such as SAS. We not only developed a set of SAS macro programs to fill this gap, but also expanded the geographically weighted generalized linear modeling (GWGLM) by integrating the strengths of SAS into the GWGLM framework. Three features distinguish our work. First, the macro programs of this study provide more kernel weighting functions than the existing programs. Second, with our codes the users are able to better specify the bandwidth selection process compared to the capabilities of existing programs. Third, the development of the macro programs is fully embedded in the SAS environment, providing great potential for future exploration of complicated spatially varying coefficient models in other disciplines. We provided three empirical examples to illustrate the use of the SAS macro programs and demonstrated the advantages explained above. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

An Efficacious Multi-Objective Fuzzy Linear Programming Approach for Optimal Power Flow Considering Distributed Generation.

Science.gov (United States)

Warid, Warid; Hizam, Hashim; Mariun, Norman; Abdul-Wahab, Noor Izzri

2016-01-01

This paper proposes a new formulation for the multi-objective optimal power flow (MOOPF) problem for meshed power networks considering distributed generation. An efficacious multi-objective fuzzy linear programming optimization (MFLP) algorithm is proposed to solve the aforementioned problem with and without considering the distributed generation (DG) effect. A variant combination of objectives is considered for simultaneous optimization, including power loss, voltage stability, and shunt capacitors MVAR reserve. Fuzzy membership functions for these objectives are designed with extreme targets, whereas the inequality constraints are treated as hard constraints. The multi-objective fuzzy optimal power flow (OPF) formulation was converted into a crisp OPF in a successive linear programming (SLP) framework and solved using an efficient interior point method (IPM). To test the efficacy of the proposed approach, simulations are performed on the IEEE 30-busand IEEE 118-bus test systems. The MFLP optimization is solved for several optimization cases. The obtained results are compared with those presented in the literature. A unique solution with a high satisfaction for the assigned targets is gained. Results demonstrate the effectiveness of the proposed MFLP technique in terms of solution optimality and rapid convergence. Moreover, the results indicate that using the optimal DG location with the MFLP algorithm provides the solution with the highest quality.

Impulsive Control for Continuous-Time Markov Decision Processes: A Linear Programming Approach

Energy Technology Data Exchange (ETDEWEB)

Dufour, F., E-mail: dufour@math.u-bordeaux1.fr [Bordeaux INP, IMB, UMR CNRS 5251 (France); Piunovskiy, A. B., E-mail: piunov@liv.ac.uk [University of Liverpool, Department of Mathematical Sciences (United Kingdom)

2016-08-15

In this paper, we investigate an optimization problem for continuous-time Markov decision processes with both impulsive and continuous controls. We consider the so-called constrained problem where the objective of the controller is to minimize a total expected discounted optimality criterion associated with a cost rate function while keeping other performance criteria of the same form, but associated with different cost rate functions, below some given bounds. Our model allows multiple impulses at the same time moment. The main objective of this work is to study the associated linear program defined on a space of measures including the occupation measures of the controlled process and to provide sufficient conditions to ensure the existence of an optimal control.

A linear programming approach to max-sum problem: a review.

Science.gov (United States)

Werner, Tomás

2007-07-01

The max-sum labeling problem, defined as maximizing a sum of binary (i.e., pairwise) functions of discrete variables, is a general NP-hard optimization problem with many applications, such as computing the MAP configuration of a Markov random field. We review a not widely known approach to the problem, developed by Ukrainian researchers Schlesinger et al. in 1976, and show how it contributes to recent results, most importantly, those on the convex combination of trees and tree-reweighted max-product. In particular, we review Schlesinger et al.'s upper bound on the max-sum criterion, its minimization by equivalent transformations, its relation to the constraint satisfaction problem, the fact that this minimization is dual to a linear programming relaxation of the original problem, and the three kinds of consistency necessary for optimality of the upper bound. We revisit problems with Boolean variables and supermodular problems. We describe two algorithms for decreasing the upper bound. We present an example application for structural image analysis.

An efficient dose-compensation method for proximity effect correction

International Nuclear Information System (INIS)

Wang Ying; Han Weihua; Yang Xiang; Zhang Yang; Yang Fuhua; Zhang Renping

2010-01-01

A novel simple dose-compensation method is developed for proximity effect correction in electron-beam lithography. The sizes of exposed patterns depend on dose factors while other exposure parameters (including accelerate voltage, resist thickness, exposing step size, substrate material, and so on) remain constant. This method is based on two reasonable assumptions in the evaluation of the compensated dose factor: one is that the relation between dose factors and circle-diameters is linear in the range under consideration; the other is that the compensated dose factor is only affected by the nearest neighbors for simplicity. Four-layer-hexagon photonic crystal structures were fabricated as test patterns to demonstrate this method. Compared to the uncorrected structures, the homogeneity of the corrected hole-size in photonic crystal structures was clearly improved. (semiconductor technology)

Proximal Hamstring Tendinosis and Partial Ruptures.

Science.gov (United States)

Startzman, Ashley N; Fowler, Oliver; Carreira, Dominic

2017-07-01

Proximal hamstring tendinosis and partial hamstring origin ruptures are painful conditions of the proximal thigh and hip that may occur in the acute, chronic, or acute on chronic setting. Few publications exist related to their diagnosis and management. This systematic review discusses the incidence, treatment, and prognosis of proximal hamstring tendinosis and partial hamstring ruptures. Conservative treatment measures include nonsteroidal anti-inflammatory drugs, physical therapy, rest, and ice. If these measures fail, platelet-rich plasma or shockwave therapy may be considered. When refractory to conservative management, these injuries may be treated with surgical debridement and hamstring reattachment. [Orthopedics. 2017; 40(4):e574-e582.]. Copyright 2017, SLACK Incorporated.

Introduction to computational linear algebra

CERN Document Server

Nassif, Nabil; Erhel, Jocelyne

2015-01-01

Introduction to Computational Linear Algebra introduces the reader with a background in basic mathematics and computer programming to the fundamentals of dense and sparse matrix computations with illustrating examples. The textbook is a synthesis of conceptual and practical topics in ""Matrix Computations."" The book's learning outcomes are twofold: to understand state-of-the-art computational tools to solve matrix computations problems (BLAS primitives, MATLAB® programming) as well as essential mathematical concepts needed to master the topics of numerical linear algebra. It is suitable for s

A comprehensive linear programming tool to optimize formulations of ready-to-use therapeutic foods: An application to Ethiopia

Science.gov (United States)

Ready-to-use therapeutic food (RUTF) is the standard of care for children suffering from noncomplicated severe acute malnutrition (SAM). The objective was to develop a comprehensive linear programming (LP) tool to create novel RUTF formulations for Ethiopia. A systematic approach that surveyed inter...

Proximal Participation: A Pathway into Work

Science.gov (United States)

Chan, Selena

2013-01-01

In a longitudinal case study of apprentices, the term proximal participation was coined to describe the entry process of young people, with unclear career destinations, into the trade of baking. This article unravels the significance of proximal participation in the decision-making processes of young people who enter a trade through initial…

Ultimate and proximate explanations of strong reciprocity.

Science.gov (United States)

Vromen, Jack

2017-08-23

Strong reciprocity (SR) has recently been subject to heated debate. In this debate, the "West camp" (West et al. in Evol Hum Behav 32(4):231-262, 2011), which is critical of the case for SR, and the "Laland camp" (Laland et al. in Science, 334(6062):1512-1516, 2011, Biol Philos 28(5):719-745, 2013), which is sympathetic to the case of SR, seem to take diametrically opposed positions. The West camp criticizes advocates of SR for conflating proximate and ultimate causation. SR is said to be a proximate mechanism that is put forward by its advocates as an ultimate explanation of human cooperation. The West camp thus accuses advocates of SR for not heeding Mayr's original distinction between ultimate and proximate causation. The Laland camp praises advocates of SR for revising Mayr's distinction. Advocates of SR are said to replace Mayr's uni-directional view on the relation between ultimate and proximate causes by the bi-directional one of reciprocal causation. The paper argues that both the West camp and the Laland camp misrepresent what advocates of SR are up to. The West camp is right that SR is a proximate cause of human cooperation. But rather than putting forward SR as an ultimate explanation, as the West camp argues, advocates of SR believe that SR itself is in need of ultimate explanation. Advocates of SR tend to take gene-culture co-evolutionary theory as the correct meta-theoretical framework for advancing ultimate explanations of SR. Appearances notwithstanding, gene-culture coevolutionary theory does not imply Laland et al.'s notion of reciprocal causation. "Reciprocal causation" suggests that proximate and ultimate causes interact simultaneously, while advocates of SR assume that they interact sequentially. I end by arguing that the best way to understand the debate is by disambiguating Mayr's ultimate-proximate distinction. I propose to reserve "ultimate" and "proximate" for different sorts of explanations, and to use other terms for distinguishing

Linear programming: an alternative approach for developing formulations for emergency food products.

Science.gov (United States)

Sheibani, Ershad; Dabbagh Moghaddam, Arasb; Sharifan, Anousheh; Afshari, Zahra

2018-03-01

To minimize the mortality rates of individuals affected by disasters, providing high-quality food relief during the initial stages of an emergency is crucial. The goal of this study was to develop a formulation for a high-energy, nutrient-dense prototype using linear programming (LP) model as a novel method for developing formulations for food products. The model consisted of the objective function and the decision variables, which were the formulation costs and weights of the selected commodities, respectively. The LP constraints were the Institute of Medicine and the World Health Organization specifications of the content of nutrients in the product. Other constraints related to the product's sensory properties were also introduced to the model. Nonlinear constraints for energy ratios of nutrients were linearized to allow their use in the LP. Three focus group studies were conducted to evaluate the palatability and other aspects of the optimized formulation. New constraints were introduced to the LP model based on the focus group evaluations to improve the formulation. LP is an appropriate tool for designing formulations of food products to meet a set of nutritional requirements. This method is an excellent alternative to the traditional 'trial and error' method in designing formulations. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Approximate labeling via graph cuts based on linear programming.

Science.gov (United States)

Komodakis, Nikos; Tziritas, Georgios

2007-08-01

A new framework is presented for both understanding and developing graph-cut-based combinatorial algorithms suitable for the approximate optimization of a very wide class of Markov Random Fields (MRFs) that are frequently encountered in computer vision. The proposed framework utilizes tools from the duality theory of linear programming in order to provide an alternative and more general view of state-of-the-art techniques like the \\alpha-expansion algorithm, which is included merely as a special case. Moreover, contrary to \\alpha-expansion, the derived algorithms generate solutions with guaranteed optimality properties for a much wider class of problems, for example, even for MRFs with nonmetric potentials. In addition, they are capable of providing per-instance suboptimality bounds in all occasions, including discrete MRFs with an arbitrary potential function. These bounds prove to be very tight in practice (that is, very close to 1), which means that the resulting solutions are almost optimal. Our algorithms' effectiveness is demonstrated by presenting experimental results on a variety of low-level vision tasks, such as stereo matching, image restoration, image completion, and optical flow estimation, as well as on synthetic problems.

Prosthetic replacement for proximal humeral fractures.

Science.gov (United States)

Kontakis, George; Tosounidis, Theodoros; Galanakis, Ioannis; Megas, Panagiotis

2008-12-01

The ideal management of complex proximal humeral fractures continues to be debatable. Evolution of proximal humeral fracture management, during the past decade, led to the implementation of many innovations in surgical treatment. Even though the pendulum of treatment seems to swing towards new trends such as locked plating, hemiarthroplasty remains a valid and reliable option that serves the patient's needs well. Hemiarthroplasty is indicated for complex proximal humeral fractures in elderly patients with poor bone stock and when internal fixation is difficult or unreliable. Hemiarthroplasty provides a better result when it is performed early post-injury. Stem height, retroversion and tuberosity positioning are technical aspects of utmost importance. Additionally reverse total shoulder arthroplasty is an alternative new modality that can be used as a primary solution in selected patients with proximal humeral fracture treatment. Failed hemiarthroplasty and fracture sequelae can be successfully managed with reverse total shoulder arthroplasty. Individual decision-making and tailored treatment that takes into consideration the personality of the fracture and the patient's characteristics should be used.

Industrial Computed Tomography using Proximal Algorithm

KAUST Repository

Zang, Guangming

2016-04-14

In this thesis, we present ProxiSART, a flexible proximal framework for robust 3D cone beam tomographic reconstruction based on the Simultaneous Algebraic Reconstruction Technique (SART). We derive the proximal operator for the SART algorithm and use it for minimizing the data term in a proximal algorithm. We show the flexibility of the framework by plugging in different powerful regularizers, and show its robustness in achieving better reconstruction results in the presence of noise and using fewer projections. We compare our framework to state-of-the-art methods and existing popular software tomography reconstruction packages, on both synthetic and real datasets, and show superior reconstruction quality, especially from noisy data and a small number of projections.

Response Surface Method and Linear Programming in the development of mixed nectar of acceptability high and minimum cost

Directory of Open Access Journals (Sweden)

Enrique López Calderón

2012-06-01

Full Text Available The aim of this study was to develop a high acceptability mixed nectar and low cost. To obtain the nectar mixed considered different amounts of passion fruit, sweet pepino, sucrose, and completing 100% with water, following a two-stage design: screening (using a design of type 2 3 + 4 center points and optimization (using a design of type 2 2 + 2*2 + 4 center points; stages that allow explore a high acceptability formulation. Then we used the technique of Linear Programming to minimize the cost of high acceptability nectar. Result of this process was obtained a mixed nectar optimal acceptability (score of 7, when the formulation is between 9 and 14% of passion fruit, 4 and 5% of sucrose, 73.5% of sweet pepino juice and filling with water to the 100%. Linear Programming possible reduced the cost of nectar mixed with optimal acceptability at S/.174 for a production of 1000 L/day.

A linear programming approach for estimating the structure of a sparse linear genetic network from transcript profiling data

Directory of Open Access Journals (Sweden)

Chandra Nagasuma R

2009-02-01

Full Text Available Abstract Background A genetic network can be represented as a directed graph in which a node corresponds to a gene and a directed edge specifies the direction of influence of one gene on another. The reconstruction of such networks from transcript profiling data remains an important yet challenging endeavor. A transcript profile specifies the abundances of many genes in a biological sample of interest. Prevailing strategies for learning the structure of a genetic network from high-dimensional transcript profiling data assume sparsity and linearity. Many methods consider relatively small directed graphs, inferring graphs with up to a few hundred nodes. This work examines large undirected graphs representations of genetic networks, graphs with many thousands of nodes where an undirected edge between two nodes does not indicate the direction of influence, and the problem of estimating the structure of such a sparse linear genetic network (SLGN from transcript profiling data. Results The structure learning task is cast as a sparse linear regression problem which is then posed as a LASSO (l1-constrained fitting problem and solved finally by formulating a Linear Program (LP. A bound on the Generalization Error of this approach is given in terms of the Leave-One-Out Error. The accuracy and utility of LP-SLGNs is assessed quantitatively and qualitatively using simulated and real data. The Dialogue for Reverse Engineering Assessments and Methods (DREAM initiative provides gold standard data sets and evaluation metrics that enable and facilitate the comparison of algorithms for deducing the structure of networks. The structures of LP-SLGNs estimated from the INSILICO1, INSILICO2 and INSILICO3 simulated DREAM2 data sets are comparable to those proposed by the first and/or second ranked teams in the DREAM2 competition. The structures of LP-SLGNs estimated from two published Saccharomyces cerevisae cell cycle transcript profiling data sets capture known

Detection of avian influenza antigens in proximity fiber, droplet, and optical waveguide microfluidics

Science.gov (United States)

Yoon, Jeong-Yeol; Heinze, Brian C.; Gamboa, Jessica; You, David J.

2009-05-01

Virus antigens of avian influenza subtype H3N2 were detected on two different microfluidic platforms: microchannel and droplet. Latex immunoagglutination assays were performed using 920-nm highly carboxylated polystyrene beads that are conjugated with antibody to avian influenza virus. The bead suspension was merged with the solutions of avian influenza virus antigens in a Y-junction of a microchannel made by polydimethylsiloxane soft lithography. The resulting latex immunoagglutinations were measured with two optical fibers in proximity setup to detect 45° forward light scattering. Alternatively, 10 μL droplets of a bead suspension and an antigen solution were merged on a superhydrophobic surface (water contact angle = 155°), whose movement was guided by a metal wire, and 180° back light scattering is measured with a backscattering optical probe. Detection limits were 0.1 pg mL-1 for both microchannel with proximity fibers and droplet microfluidics, thanks to the use of micro-positioning stages to help generate reproducible optical signals. Additionally, optical waveguide was tested by constructing optical waveguide channels (filled with mineral oil) within a microfluidic device to detect the same light scattering. Detection limit was 0.1 ng mL-1 for an optical waveguide device, with a strong potential of improvement in the near future. The use of optical waveguide enabled smaller device setup, easier operation, smaller standard deviations and broader linear range of assay than proximity fiber microchannel and droplet microfluidics. Total assay time was less than 10 min.

Revised VESCAL: Vessel calibration data analysis program. Improvement of a model for non-linear parts of annular and slab tanks

International Nuclear Information System (INIS)

Yanagisawa, Hiroshi

1995-05-01

For the purpose of the nuclear material accountancy and control for NUCEF: the Nuclear Fuel Cycle Safety Engineering Research Facility, the vessel calibration data analysis program: VESCAL is revised, and a new model for non-linear parts of annular and slab tanks is added to the program. The new model has three unknown parameters, and liquid level is expressed as a square root function with respect to liquid volume. Using the new model, an accurate calibration function on the level and volume data for non-linear parts of annular and slab tanks can be obtained with the smaller number of unknown parameters, compared with a polynomial function model. As a result of benchmark tests for this revision, it was proved that numerical results computed with VESCAL well agreed with those by a statistical analysis program package which is widely used. In addition, the new model would be useful for carrying out data analyses on the vessel calibration at the other bulk handling facilities as well as at NUCEF. This paper describes summary of the program, computational methods and results of benchmark tests concerning this revision. (author)

Navigation Strategies for Primitive Solar System Body Rendezvous and Proximity Operations

Science.gov (United States)

Getzandanner, Kenneth M.

2011-01-01

A wealth of scientific knowledge regarding the composition and evolution of the solar system can be gained through reconnaissance missions to primitive solar system bodies. This paper presents analysis of a baseline navigation strategy designed to address the unique challenges of primitive body navigation. Linear covariance and Monte Carlo error analysis was performed on a baseline navigation strategy using simulated data from a· design reference mission (DRM). The objective of the DRM is to approach, rendezvous, and maintain a stable orbit about the near-Earth asteroid 4660 Nereus. The outlined navigation strategy and resulting analyses, however, are not necessarily limited to this specific target asteroid as they may he applicable to a diverse range of mission scenarios. The baseline navigation strategy included simulated data from Deep Space Network (DSN) radiometric tracking and optical image processing (OpNav). Results from the linear covariance and Monte Carlo analyses suggest the DRM navigation strategy is sufficient to approach and perform proximity operations in the vicinity of the target asteroid with meter-level accuracy.

Proximity sensor system development. CRADA final report

Energy Technology Data Exchange (ETDEWEB)

Haley, D.C. [Oak Ridge National Lab., TN (United States); Pigoski, T.M. [Merrit Systems, Inc. (United States)

1998-01-01

Lockheed Martin Energy Research Corporation (LMERC) and Merritt Systems, Inc. (MSI) entered into a Cooperative Research and Development Agreement (CRADA) for the development and demonstration of a compact, modular proximity sensing system suitable for application to a wide class of manipulator systems operated in support of environmental restoration and waste management activities. In teleoperated modes, proximity sensing provides the manipulator operator continuous information regarding the proximity of the manipulator to objects in the workspace. In teleoperated and robotic modes, proximity sensing provides added safety through the implementation of active whole arm collision avoidance capabilities. Oak Ridge National Laboratory (ORNL), managed by LMERC for the United States Department of Energy (DOE), has developed an application specific integrated circuit (ASIC) design for the electronics required to support a modular whole arm proximity sensing system based on the use of capacitive sensors developed at Sandia National Laboratories. The use of ASIC technology greatly reduces the size of the electronics required to support the selected sensor types allowing deployment of many small sensor nodes over a large area of the manipulator surface to provide maximum sensor coverage. The ASIC design also provides a communication interface to support sensor commands from and sensor data transmission to a distributed processing system which allows modular implementation and operation of the sensor system. MSI is a commercial small business specializing in proximity sensing systems based upon infrared and acoustic sensors.

Proximity sensor system development. CRADA final report

International Nuclear Information System (INIS)

Haley, D.C.; Pigoski, T.M.

1998-01-01

Lockheed Martin Energy Research Corporation (LMERC) and Merritt Systems, Inc. (MSI) entered into a Cooperative Research and Development Agreement (CRADA) for the development and demonstration of a compact, modular proximity sensing system suitable for application to a wide class of manipulator systems operated in support of environmental restoration and waste management activities. In teleoperated modes, proximity sensing provides the manipulator operator continuous information regarding the proximity of the manipulator to objects in the workspace. In teleoperated and robotic modes, proximity sensing provides added safety through the implementation of active whole arm collision avoidance capabilities. Oak Ridge National Laboratory (ORNL), managed by LMERC for the United States Department of Energy (DOE), has developed an application specific integrated circuit (ASIC) design for the electronics required to support a modular whole arm proximity sensing system based on the use of capacitive sensors developed at Sandia National Laboratories. The use of ASIC technology greatly reduces the size of the electronics required to support the selected sensor types allowing deployment of many small sensor nodes over a large area of the manipulator surface to provide maximum sensor coverage. The ASIC design also provides a communication interface to support sensor commands from and sensor data transmission to a distributed processing system which allows modular implementation and operation of the sensor system. MSI is a commercial small business specializing in proximity sensing systems based upon infrared and acoustic sensors

Locking plate fixation for proximal humerus fractures.

LENUS (Irish Health Repository)

Burke, Neil G

2012-02-01

Locking plates are increasingly used to surgically treat proximal humerus fractures. Knowledge of the bone quality of the proximal humerus is important. Studies have shown the medial and dorsal aspects of the proximal humeral head to have the highest bone strength, and this should be exploited by fixation techniques, particularly in elderly patients with osteoporosis. The goals of surgery for proximal humeral fractures should involve minimal soft tissue dissection and achieve anatomic reduction of the head complex with sufficient stability to allow for early shoulder mobilization. This article reviews various treatment options, in particular locking plate fixation. Locking plate fixation is associated with a high complication rate, such as avascular necrosis (7.9%), screw cutout (11.6%), and revision surgery (13.7%). These complications are frequently due to the varus deformation of the humeral head. Strategic screw placement in the humeral head would minimize the possibility of loss of fracture reduction and potential hardware complications. Locking plate fixation is a good surgical option for the management of proximal humerus fractures. Complications can be avoided by using better bone stock and by careful screw placement in the humeral head.

Proximal collagenous gastroenteritides:

DEFF Research Database (Denmark)

Nielsen, Ole Haagen; Riis, Lene Buhl; Danese, Silvio

2014-01-01

AIM: While collagenous colitis represents the most common form of the collagenous gastroenteritides, the collagenous entities affecting the proximal part of the gastrointestinal tract are much less recognized and possibly overlooked. The aim was to summarize the latest information through a syste...

Promoting proximal formative assessment with relational discourse

Science.gov (United States)

Scherr, Rachel E.; Close, Hunter G.; McKagan, Sarah B.

2012-02-01

The practice of proximal formative assessment - the continual, responsive attention to students' developing understanding as it is expressed in real time - depends on students' sharing their ideas with instructors and on teachers' attending to them. Rogerian psychology presents an account of the conditions under which proximal formative assessment may be promoted or inhibited: (1) Normal classroom conditions, characterized by evaluation and attention to learning targets, may present threats to students' sense of their own competence and value, causing them to conceal their ideas and reducing the potential for proximal formative assessment. (2) In contrast, discourse patterns characterized by positive anticipation and attention to learner ideas increase the potential for proximal formative assessment and promote self-directed learning. We present an analysis methodology based on these principles and demonstrate its utility for understanding episodes of university physics instruction.

Newborn screening for proximal urea cycle disorders: Current evidence supporting recommendations for newborn screening.

Science.gov (United States)

Merritt, J Lawrence; Brody, Linnea L; Pino, Gisele; Rinaldo, Piero

2018-04-20

Current newborn screening (NBS) for urea cycle disorders (UCD) is incomplete as only distal UCDs are included in most NBS programs by measuring elevated amino acid concentrations. NBS for the proximal UCDs involves the detection in NBS spots of low citrulline values, a finding which is often overlooked because it is considered to be inadequate. We retrospectively analyzed NBS blood spots from known UCD patients comparing the utility of the Region 4 Stork (R4S) interpretive tools to conventional cutoff based interpretation. This study shows the utility of R4S tools in detecting all UCDs, and provides evidence to support the nomination to add proximal UCDs to the recommended uniform screening panel. Copyright © 2018 Elsevier Inc. All rights reserved.

Psychological responses to the proximity of climate change

Science.gov (United States)

Brügger, Adrian; Dessai, Suraje; Devine-Wright, Patrick; Morton, Thomas A.; Pidgeon, Nicholas F.

2015-12-01

A frequent suggestion to increase individuals' willingness to take action on climate change and to support relevant policies is to highlight its proximal consequences, that is, those that are close in space and time. But previous studies that have tested this proximizing approach have not revealed the expected positive effects on individual action and support for addressing climate change. We present three lines of psychological reasoning that provide compelling arguments as to why highlighting proximal impacts of climate change might not be as effective a way to increase individual mitigation and adaptation efforts as is often assumed. Our contextualization of the proximizing approach within established psychological research suggests that, depending on the particular theoretical perspective one takes on this issue, and on specific individual characteristics suggested by these perspectives, proximizing can bring about the intended positive effects, can have no (visible) effect or can even backfire. Thus, the effects of proximizing are much more complex than is commonly assumed. Revealing this complexity contributes to a refined theoretical understanding of the role that psychological distance plays in the context of climate change and opens up further avenues for future research and for interventions.

Sequential computation of elementary modes and minimal cut sets in genome-scale metabolic networks using alternate integer linear programming.

Science.gov (United States)

Song, Hyun-Seob; Goldberg, Noam; Mahajan, Ashutosh; Ramkrishna, Doraiswami

2017-08-01

Elementary (flux) modes (EMs) have served as a valuable tool for investigating structural and functional properties of metabolic networks. Identification of the full set of EMs in genome-scale networks remains challenging due to combinatorial explosion of EMs in complex networks. It is often, however, that only a small subset of relevant EMs needs to be known, for which optimization-based sequential computation is a useful alternative. Most of the currently available methods along this line are based on the iterative use of mixed integer linear programming (MILP), the effectiveness of which significantly deteriorates as the number of iterations builds up. To alleviate the computational burden associated with the MILP implementation, we here present a novel optimization algorithm termed alternate integer linear programming (AILP). Our algorithm was designed to iteratively solve a pair of integer programming (IP) and linear programming (LP) to compute EMs in a sequential manner. In each step, the IP identifies a minimal subset of reactions, the deletion of which disables all previously identified EMs. Thus, a subsequent LP solution subject to this reaction deletion constraint becomes a distinct EM. In cases where no feasible LP solution is available, IP-derived reaction deletion sets represent minimal cut sets (MCSs). Despite the additional computation of MCSs, AILP achieved significant time reduction in computing EMs by orders of magnitude. The proposed AILP algorithm not only offers a computational advantage in the EM analysis of genome-scale networks, but also improves the understanding of the linkage between EMs and MCSs. The software is implemented in Matlab, and is provided as supplementary information . hyunseob.song@pnnl.gov. Supplementary data are available at Bioinformatics online. Published by Oxford University Press 2017. This work is written by US Government employees and are in the public domain in the US.

Critical Proximity as a Methodological Move in Techno-Anthropology

DEFF Research Database (Denmark)

Birkbak, Andreas; Petersen, Morten Krogh; Elgaard Jensen, Torben

2015-01-01

proximity.’ Critical proximity offers an alternative to critical distance, especially with respect to avoiding premature references to abstract panoramas such as democratization and capitalist exploitation in the quest to conduct ‘critical’ analysis. Critical proximity implies, instead, granting the beings...

European refining trends to 2030: The advent of multi-area linear programming

International Nuclear Information System (INIS)

Saint-Antonin, V.; Marion, P.

2011-01-01

The current high degree of uncertainty that pervades the global energy landscape is directly impacting on the oil industry, which is having to integrate growing mobility requirements in the context of energy transition due to the emergence of alternatives to petroleum fuels and restrictions on pollutant emissions. In this context, the study 'Raffinage 2030' (Refining 2030), carried out by IFPEN (the French Institute of Petroleum and New Energy Sources), is a prospective exercise for a better understanding of the balance between global supply and demand of petroleum products in order to shed light on the type and geographical location of necessary investments in refineries, as well as to assess the impact on these of the introduction of new fuels and more and more restrictions, such as environmental regulations. To this end, the refinery model used is one of linear programming, breaking the world down into nine geographical areas. This article introduces the programming model and its basic assumptions, before presenting the main lessons drawn om this study regarding the potential evolutions of the refining industry, in particular the European one, to face the market's long term trends. (authors)

An online re-linearization scheme suited for Model Predictive and Linear Quadratic Control

DEFF Research Database (Denmark)

Henriksen, Lars Christian; Poulsen, Niels Kjølstad

This technical note documents the equations for primal-dual interior-point quadratic programming problem solver used for MPC. The algorithm exploits the special structure of the MPC problem and is able to reduce the computational burden such that the computational burden scales with prediction...... horizon length in a linear way rather than cubic, which would be the case if the structure was not exploited. It is also shown how models used for design of model-based controllers, e.g. linear quadratic and model predictive, can be linearized both at equilibrium and non-equilibrium points, making...

Infiltrating/sealing proximal caries lesions

DEFF Research Database (Denmark)

Martignon, S; Ekstrand, K R; Gomez, J

2012-01-01

This randomized split-mouth controlled clinical trial aimed at assessing the therapeutic effects of infiltration vs. sealing for controlling caries progression on proximal surfaces. Out of 90 adult students/patients assessed at university clinics and agreeing to participate, 39, each with 3...... differences in lesion progression between infiltration and placebo (P = 0.0012) and between sealing and placebo (P = 0.0269). The study showed that infiltration and sealing are significantly better than placebo treatment for controlling caries progression on proximal lesions. No significant difference...

Proximal femoral fractures

DEFF Research Database (Denmark)

Palm, Henrik; Teixidor, Jordi

2015-01-01

searched the homepages of the national heath authorities and national orthopedic societies in West Europe and found 11 national or regional (in case of no national) guidelines including any type of proximal femoral fracture surgery. RESULTS: Pathway consensus is outspread (internal fixation for un...

Decomposition and (importance) sampling techniques for multi-stage stochastic linear programs

Energy Technology Data Exchange (ETDEWEB)

Infanger, G.

1993-11-01

The difficulty of solving large-scale multi-stage stochastic linear programs arises from the sheer number of scenarios associated with numerous stochastic parameters. The number of scenarios grows exponentially with the number of stages and problems get easily out of hand even for very moderate numbers of stochastic parameters per stage. Our method combines dual (Benders) decomposition with Monte Carlo sampling techniques. We employ importance sampling to efficiently obtain accurate estimates of both expected future costs and gradients and right-hand sides of cuts. The method enables us to solve practical large-scale problems with many stages and numerous stochastic parameters per stage. We discuss the theory of sharing and adjusting cuts between different scenarios in a stage. We derive probabilistic lower and upper bounds, where we use importance path sampling for the upper bound estimation. Initial numerical results turned out to be promising.

Highlights of the SLD Physics Program at the SLAC Linear Collider

International Nuclear Information System (INIS)

Willocq, Stephane

2001-01-01

Starting in 1989, and continuing through the 1990s, high-energy physics witnessed a flowering of precision measurements in general and tests of the standard model in particular, led by e + e - collider experiments operating at the Z 0 resonance. Key contributions to this work came from the SLD collaboration at the SLAC Linear Collider. By exploiting the unique capabilities of this pioneering accelerator and the SLD detector, including a polarized electron beam, exceptionally small beam dimensions, and a CCD pixel vertex detector, SLD produced a broad array of electroweak, heavy-flavor, and QCD measurements. Many of these results are one of a kind or represent the world's standard in precision. This article reviews the highlights of the SLD physics program, with an eye toward associated advances in experimental technique, and the contribution of these measurements to our dramatically improved present understanding of the standard model and its possible extensions

Consideration in selecting crops for the human-rated life support system: a Linear Programming model

Science.gov (United States)

Wheeler, E. F.; Kossowski, J.; Goto, E.; Langhans, R. W.; White, G.; Albright, L. D.; Wilcox, D.; Henninger, D. L. (Principal Investigator)

1996-01-01

A Linear Programming model has been constructed which aids in selecting appropriate crops for CELSS (Controlled Environment Life Support System) food production. A team of Controlled Environment Agriculture (CEA) faculty, staff, graduate students and invited experts representing more than a dozen disciplines, provided a wide range of expertise in developing the model and the crop production program. The model incorporates nutritional content and controlled-environment based production yields of carefully chosen crops into a framework where a crop mix can be constructed to suit the astronauts' needs. The crew's nutritional requirements can be adequately satisfied with only a few crops (assuming vitamin mineral supplements are provided) but this will not be satisfactory from a culinary standpoint. This model is flexible enough that taste and variety driven food choices can be built into the model.

Dual pathology proximal median nerve compression of the forearm.

LENUS (Irish Health Repository)

Murphy, Siun M

2013-12-01

We report an unusual case of synchronous pathology in the forearm- the coexistence of a large lipoma of the median nerve together with an osteochondroma of the proximal ulna, giving rise to a dual proximal median nerve compression. Proximal median nerve compression neuropathies in the forearm are uncommon compared to the prevalence of distal compression neuropathies (eg Carpal Tunnel Syndrome). Both neural fibrolipomas (Refs. 1,2) and osteochondromas of the proximal ulna (Ref. 3) in isolation are rare but well documented. Unlike that of a distal compression, a proximal compression of the median nerve will often have a definite cause. Neural fibrolipoma, also called fibrolipomatous hamartoma are rare, slow-growing, benign tumours of peripheral nerves, most often occurring in the median nerve of younger patients. To our knowledge, this is the first report of such dual pathology in the same forearm, giving rise to a severe proximal compression of the median nerve. In this case, the nerve was being pushed anteriorly by the osteochondroma, and was being compressed from within by the intraneural lipoma. This unusual case highlights the advantage of preoperative imaging as part of the workup of proximal median nerve compression.

Giant proximity effect and critical opalescence in EuS

Science.gov (United States)

Charlton, Timothy; Ramos, Silvia; Quintanilla, Jorge; Suter, Andreas; Moodera, Jagadeesh

2015-03-01

The proximity effect is a type of wetting phenomenon where an ordered state, usually magnetism or superconductivity, ``leaks'' from one material into an adjacent one over some finite distance. For superconductors, the characteristic range is of the order of the coherence length, usually hundreds of nm. Nevertheless much longer, ``giant'' proximity effects have been observed in cuprate perovskite junctions. Such giant proximity effects can be understood by taking into account the divergence of the pairing susceptibility in the non-superconducting material when it is itself close to a superconducting instability: a superconducting version of critical opalescence. Since critical opalescence occurs in all second order phase transitions, giant proximity effects are expected to be general, therefor there must be a giant ferromagnetic proximity effect. Compared to its superconducting counterpart, the giant ferromagnetic proximity effect has the advantage that the order parameter (magnetization) can be observed directly. We have fabricated Co/EuS thin films and measured the magnetization profiles as a function of temperature using the complementary techniques of low energy muon relaxation and polarized neutron reflectivity. Details of the proximity effect near TCEuS will be presented.

Drag reduction of a car model by linear genetic programming control

Science.gov (United States)

Li, Ruiying; Noack, Bernd R.; Cordier, Laurent; Borée, Jacques; Harambat, Fabien

2017-08-01

We investigate open- and closed-loop active control for aerodynamic drag reduction of a car model. Turbulent flow around a blunt-edged Ahmed body is examined at ReH≈ 3× 105 based on body height. The actuation is performed with pulsed jets at all trailing edges (multiple inputs) combined with a Coanda deflection surface. The flow is monitored with 16 pressure sensors distributed at the rear side (multiple outputs). We apply a recently developed model-free control strategy building on genetic programming in Dracopoulos and Kent (Neural Comput Appl 6:214-228, 1997) and Gautier et al. (J Fluid Mech 770:424-441, 2015). The optimized control laws comprise periodic forcing, multi-frequency forcing and sensor-based feedback including also time-history information feedback and combinations thereof. Key enabler is linear genetic programming (LGP) as powerful regression technique for optimizing the multiple-input multiple-output control laws. The proposed LGP control can select the best open- or closed-loop control in an unsupervised manner. Approximately 33% base pressure recovery associated with 22% drag reduction is achieved in all considered classes of control laws. Intriguingly, the feedback actuation emulates periodic high-frequency forcing. In addition, the control identified automatically the only sensor which listens to high-frequency flow components with good signal to noise ratio. Our control strategy is, in principle, applicable to all multiple actuators and sensors experiments.

Strong Proximities on Smooth Manifolds and Vorono\\" i Diagrams

OpenAIRE

Peters, J. F.; Guadagni, C.

2015-01-01

This article introduces strongly near smooth manifolds. The main results are (i) second countability of the strongly hit and far-miss topology on a family $\\mathcal{B}$ of subsets on the Lodato proximity space of regular open sets to which singletons are added, (ii) manifold strong proximity, (iii) strong proximity of charts in manifold atlases implies that the charts have nonempty intersection. The application of these results is given in terms of the nearness of atlases and charts of proxim...

Flow discharge prediction in compound channels using linear genetic programming

Science.gov (United States)

Azamathulla, H. Md.; Zahiri, A.

2012-08-01

SummaryFlow discharge determination in rivers is one of the key elements in mathematical modelling in the design of river engineering projects. Because of the inundation of floodplains and sudden changes in river geometry, flow resistance equations are not applicable for compound channels. Therefore, many approaches have been developed for modification of flow discharge computations. Most of these methods have satisfactory results only in laboratory flumes. Due to the ability to model complex phenomena, the artificial intelligence methods have recently been employed for wide applications in various fields of water engineering. Linear genetic programming (LGP), a branch of artificial intelligence methods, is able to optimise the model structure and its components and to derive an explicit equation based on the variables of the phenomena. In this paper, a precise dimensionless equation has been derived for prediction of flood discharge using LGP. The proposed model was developed using published data compiled for stage-discharge data sets for 394 laboratories, and field of 30 compound channels. The results indicate that the LGP model has a better performance than the existing models.

Integer Linear Programming for Constrained Multi-Aspect Committee Review Assignment

Science.gov (United States)

Karimzadehgan, Maryam; Zhai, ChengXiang

2011-01-01

Automatic review assignment can significantly improve the productivity of many people such as conference organizers, journal editors and grant administrators. A general setup of the review assignment problem involves assigning a set of reviewers on a committee to a set of documents to be reviewed under the constraint of review quota so that the reviewers assigned to a document can collectively cover multiple topic aspects of the document. No previous work has addressed such a setup of committee review assignments while also considering matching multiple aspects of topics and expertise. In this paper, we tackle the problem of committee review assignment with multi-aspect expertise matching by casting it as an integer linear programming problem. The proposed algorithm can naturally accommodate any probabilistic or deterministic method for modeling multiple aspects to automate committee review assignments. Evaluation using a multi-aspect review assignment test set constructed using ACM SIGIR publications shows that the proposed algorithm is effective and efficient for committee review assignments based on multi-aspect expertise matching. PMID:22711970

75 FR 5009 - Proximity Detection Systems for Underground Mines

Science.gov (United States)

2010-02-01

... Proximity Detection Systems for Underground Mines AGENCY: Mine Safety and Health Administration, Labor... information regarding whether the use of proximity detection systems would reduce the risk of accidents where... . Information on MSHA-approved proximity detection systems is available on the Internet at http://www.msha.gov...

Exact solutions to robust control problems involving scalar hyperbolic conservation laws using Mixed Integer Linear Programming

KAUST Repository

Li, Yanning

2013-10-01

This article presents a new robust control framework for transportation problems in which the state is modeled by a first order scalar conservation law. Using an equivalent formulation based on a Hamilton-Jacobi equation, we pose the problem of controlling the state of the system on a network link, using boundary flow control, as a Linear Program. Unlike many previously investigated transportation control schemes, this method yields a globally optimal solution and is capable of handling shocks (i.e. discontinuities in the state of the system). We also demonstrate that the same framework can handle robust control problems, in which the uncontrollable components of the initial and boundary conditions are encoded in intervals on the right hand side of inequalities in the linear program. The lower bound of the interval which defines the smallest feasible solution set is used to solve the robust LP (or MILP if the objective function depends on boolean variables). Since this framework leverages the intrinsic properties of the Hamilton-Jacobi equation used to model the state of the system, it is extremely fast. Several examples are given to demonstrate the performance of the robust control solution and the trade-off between the robustness and the optimality. © 2013 IEEE.

Exact solutions to robust control problems involving scalar hyperbolic conservation laws using Mixed Integer Linear Programming

KAUST Repository

Li, Yanning; Canepa, Edward S.; Claudel, Christian G.

2013-01-01

This article presents a new robust control framework for transportation problems in which the state is modeled by a first order scalar conservation law. Using an equivalent formulation based on a Hamilton-Jacobi equation, we pose the problem of controlling the state of the system on a network link, using boundary flow control, as a Linear Program. Unlike many previously investigated transportation control schemes, this method yields a globally optimal solution and is capable of handling shocks (i.e. discontinuities in the state of the system). We also demonstrate that the same framework can handle robust control problems, in which the uncontrollable components of the initial and boundary conditions are encoded in intervals on the right hand side of inequalities in the linear program. The lower bound of the interval which defines the smallest feasible solution set is used to solve the robust LP (or MILP if the objective function depends on boolean variables). Since this framework leverages the intrinsic properties of the Hamilton-Jacobi equation used to model the state of the system, it is extremely fast. Several examples are given to demonstrate the performance of the robust control solution and the trade-off between the robustness and the optimality. © 2013 IEEE.

Bimalleolar ankle fracture with proximal fibular fracture

NARCIS (Netherlands)

Colenbrander, R. J.; Struijs, P. A. A.; Ultee, J. M.

2005-01-01

A 56-year-old female patient suffered a bimalleolar ankle fracture with an additional proximal fibular fracture. This is an unusual fracture type, seldom reported in literature. It was operatively treated by open reduction and internal fixation of the lateral malleolar fracture. The proximal fibular

Use of Linear Programming to Develop Cost-Minimized Nutritionally Adequate Health Promoting Food Baskets.

Science.gov (United States)

Parlesak, Alexandr; Tetens, Inge; Dejgård Jensen, Jørgen; Smed, Sinne; Gabrijelčič Blenkuš, Mojca; Rayner, Mike; Darmon, Nicole; Robertson, Aileen

2016-01-01

Food-Based Dietary Guidelines (FBDGs) are developed to promote healthier eating patterns, but increasing food prices may make healthy eating less affordable. The aim of this study was to design a range of cost-minimized nutritionally adequate health-promoting food baskets (FBs) that help prevent both micronutrient inadequacy and diet-related non-communicable diseases at lowest cost. Average prices for 312 foods were collected within the Greater Copenhagen area. The cost and nutrient content of five different cost-minimized FBs for a family of four were calculated per day using linear programming. The FBs were defined using five different constraints: cultural acceptability (CA), or dietary guidelines (DG), or nutrient recommendations (N), or cultural acceptability and nutrient recommendations (CAN), or dietary guidelines and nutrient recommendations (DGN). The variety and number of foods in each of the resulting five baskets was increased through limiting the relative share of individual foods. The one-day version of N contained only 12 foods at the minimum cost of DKK 27 (€ 3.6). The CA, DG, and DGN were about twice of this and the CAN cost ~DKK 81 (€ 10.8). The baskets with the greater variety of foods contained from 70 (CAN) to 134 (DGN) foods and cost between DKK 60 (€ 8.1, N) and DKK 125 (€ 16.8, DGN). Ensuring that the food baskets cover both dietary guidelines and nutrient recommendations doubled the cost while cultural acceptability (CAN) tripled it. Use of linear programming facilitates the generation of low-cost food baskets that are nutritionally adequate, health promoting, and culturally acceptable.

Stochastic-based resource expansion planning for a grid-connected microgrid using interval linear programming

International Nuclear Information System (INIS)

Shaban Boloukat, Mohammad Hadi; Akbari Foroud, Asghar

2016-01-01

This paper represents a stochastic approach for long-term optimal resource expansion planning of a grid-connected microgrid (MG) containing different technologies as intermittent renewable energy resources, energy storage systems and thermal resources. Maximizing profit and reliability, along with minimizing investment and operation costs, are major objectives which have been considered in this model. Also, the impacts of intermittency and uncertainty in renewable energy resources were investigated. The interval linear programming (ILP) was applied for modelling inherent stochastic nature of the renewable energy resources. ILP presents some superiority in modelling of uncertainties in MG planning. The problem was formulated as a mixed-integer linear programming. It has been demonstrated previously that the benders decomposition (BD) served as an effective tool for solving such problems. BD divides the original problem into a master (investment) problem and operation and reliability subproblems. In this paper a multiperiod MG planning is presented, considering life time, maximum penetration limit of each technology, interest rate, capital recovery factor and investment fund. Real-time energy exchange with the utility is covered, with a consideration of variable tariffs at different load blocks. The presented approach can help MG planners to adopt best decision under various uncertainty levels based on their budgetary policies. - Highlights: • Considering uncertain nature of the renewable resources with applying ILP. • Considering the effect of intermittency of renewable in MG planning. • Multiobjective MG planning problem which covers cost, profit and reliability. • Multiperiod approach for MG planning considering life time and MPL of technologies. • Presenting real-time energy exchange with the utility considering variable tariffs.

Block level energy planning for domestic lighting - a multi-objective fuzzy linear programming approach

Energy Technology Data Exchange (ETDEWEB)

Jana, C. [Indian Inst. of Social Welfare and Business Management, Kolkata (India); Chattopadhyay, R.N. [Indian Inst. of Technology, Kharagpur (India). Rural Development Centre

2004-09-01

Creating provisions for domestic lighting is important for rural development. Its significance in rural economy is unquestionable since some activities, like literacy, education and manufacture of craft items and other cottage products are largely dependent on domestic lighting facilities for their progress and prosperity. Thus, in rural energy planning, domestic lighting remains a key sector for allocation of investments. For rational allocation, decision makers need alternative strategies for identifying adequate and proper investment structure corresponding to appropriate sources and precise devices. The present study aims at designing a model of energy utilisation by developing a decision support frame for an optimised solution to the problem, taking into consideration four sources and six devices suitable for the study area, namely Narayangarh Block of Midnapore District in India. Since the data available from rural and unorganised sectors are often ill-defined and subjective in nature, many coefficients are fuzzy numbers, and hence several constraints appear to be fuzzy expressions. In this study, the energy allocation model is initiated with three separate objectives for optimisation, namely minimising the total cost, minimising the use of non-local sources of energy and maximising the overall efficiency of the system. Since each of the above objective-based solutions has relevance to the needs of the society and economy, it is necessary to build a model that makes a compromise among the three individual solutions. This multi-objective fuzzy linear programming (MOFLP) model, solved in a compromising decision support frame, seems to be a more rational alternative than single objective linear programming model in rural energy planning. (author)

[Partial replantation following proximal limb injury].

Science.gov (United States)

Dubert, T; Malikov, S A; Dinh, A; Kupatadze, D D; Oberlin, C; Alnot, J Y; Nabokov, B B

2000-11-01

Proximal replantation is a technically feasible but life-threatening procedure. Indications must be restricted to patients in good condition with a good functional prognosis. The goal of replantation must be focused not only on reimplanting the amputated limb but also on achieving a good functional outcome. For the lower limb, simple terminalization remains the best choice in many cases. When a proximal amputation is not suitable for replantation, the main aim of the surgical procedure must be to reconstruct a stump long enough to permit fitting a prosthesis preserving the function of the adjacent joint. If the proximal stump beyond the last joint is very short, it may be possible to restore some length by partial replantation of spared tissues from the amputated part. We present here the results we obtained following this policy. This series included 16 cases of partial replantations, 14 involving the lower limb and 2 the upper limb. All were osteocutaneous microsurgical transfers. For the lower limb, all transfers recovered protective sensitivity following tibial nerve repair. The functional calcaeoplantar unit was used in 13 cases. The transfer of this specialized weight bearing tissue provided a stable distal surface making higher support unnecessary. In one case, we raised a 13-cm vascularized tibial segment covered with foot skin for additional length. For the upper limb, the osteocutaneous transfer, based on the radial artery, was not reinnervated, but this lack of sensitivity did not impair prosthesis fitting. One vascular failure was finally amputated. This was the only unsuccessful result. For all other patients, the surgical procedure facilitated prosthesis fitting and preserved the proximal joint function despite an initially very proximal amputation. The advantages of partial replantation are obvious compared with simple terminalization or secondary reconstruction. There is no secondary donor site and, because there is no major muscle mass in the

FPL-PELPS : a price endogenous linear programming system for economic modeling, supplement to PELPS III, version 1.1.

Science.gov (United States)

Patricia K. Lebow; Henry Spelter; Peter J. Ince

2003-01-01

This report provides documentation and user information for FPL-PELPS, a personal computer price endogenous linear programming system for economic modeling. Originally developed to model the North American pulp and paper industry, FPL-PELPS follows its predecessors in allowing the modeling of any appropriate sector to predict consumption, production and capacity by...

Linear Covariance Analysis For Proximity Operations Around Asteroid 2008 EV5

Science.gov (United States)

Wright, Cinnamon A.; Bhatt, Sagar; Woffinden, David; Strube, Matthew; D'Souza, Christopher; DeWeese, Keith

2015-01-01

The NASA initiative to collect an asteroid the Asteroid Robotic Redirect Mission (ARRM) is currently investigating the option of retrieving a boulder off an asteroid, demonstrating planetary defense with an enhanced gravity tractor technique and returning it to a lunar orbit. Techniques for accomplishing this are being investigated by the Satellite Servicing Capabilities Office (SSOO) and NASA GSFC in colloboration with JPL, NASA, JSC, LaRC, and Draper Laboratories Inc. Two critical phases of the mission are the descent to the boulder and the Enhanced Gravity Tractor-enhanced gravity tractor demonstration. A linear covariance analysis was done for these phases to assess the feasibility of these concepts with the proposed design of the sensor and actuaor suite of the Asteroid Redirect Vehicle (ARV). The sensor suite for this analysis will include a wide field of view camera, Lidar, and a MMU. The proposed asteroid of interest is currently the C-type asteroid 2008 EV5, a carbonaceous chondrite that is of high interest to the scientific community. This paper will present an overview of the analysis discuss sensor and actuator models and address the feasibility of descending to the boulder within the requirements as the feasibility of maintaining the halo orbit in order to demonstrate the Enhanced Gravity Tractor-enhanced gravity tractory technique.

Proximity functions for general right cylinders

International Nuclear Information System (INIS)

Kellerer, A.M.

1981-01-01

Distributions of distances between pairs of points within geometrical objects, or the closely related proximity functions and geometric reduction factors, have applications to dosimetric and microdosimetric calculations. For convex bodies these functions are linked to the chord-length distributions that result from random intersections by straight lines. A synopsis of the most important relations is given. The proximity functions and related functions are derived for right cylinders with arbitrary cross sections. The solution utilizes the fact that the squares of the distances between two random points are sums of independently distributed squares of distances parallel and perpendicular to the axis of the cylinder. Analogous formulas are derived for the proximity functions or geometric reduction factors for a cylinder relative to a point. This requires only a minor modification of the solution

Multi-task linear programming discriminant analysis for the identification of progressive MCI individuals.

Science.gov (United States)

Yu, Guan; Liu, Yufeng; Thung, Kim-Han; Shen, Dinggang

2014-01-01

Accurately identifying mild cognitive impairment (MCI) individuals who will progress to Alzheimer's disease (AD) is very important for making early interventions. Many classification methods focus on integrating multiple imaging modalities such as magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography (FDG-PET). However, the main challenge for MCI classification using multiple imaging modalities is the existence of a lot of missing data in many subjects. For example, in the Alzheimer's Disease Neuroimaging Initiative (ADNI) study, almost half of the subjects do not have PET images. In this paper, we propose a new and flexible binary classification method, namely Multi-task Linear Programming Discriminant (MLPD) analysis, for the incomplete multi-source feature learning. Specifically, we decompose the classification problem into different classification tasks, i.e., one for each combination of available data sources. To solve all different classification tasks jointly, our proposed MLPD method links them together by constraining them to achieve the similar estimated mean difference between the two classes (under classification) for those shared features. Compared with the state-of-the-art incomplete Multi-Source Feature (iMSF) learning method, instead of constraining different classification tasks to choose a common feature subset for those shared features, MLPD can flexibly and adaptively choose different feature subsets for different classification tasks. Furthermore, our proposed MLPD method can be efficiently implemented by linear programming. To validate our MLPD method, we perform experiments on the ADNI baseline dataset with the incomplete MRI and PET images from 167 progressive MCI (pMCI) subjects and 226 stable MCI (sMCI) subjects. We further compared our method with the iMSF method (using incomplete MRI and PET images) and also the single-task classification method (using only MRI or only subjects with both MRI and PET images

Multi-task linear programming discriminant analysis for the identification of progressive MCI individuals.

Directory of Open Access Journals (Sweden)

Guan Yu

Full Text Available Accurately identifying mild cognitive impairment (MCI individuals who will progress to Alzheimer's disease (AD is very important for making early interventions. Many classification methods focus on integrating multiple imaging modalities such as magnetic resonance imaging (MRI and fluorodeoxyglucose positron emission tomography (FDG-PET. However, the main challenge for MCI classification using multiple imaging modalities is the existence of a lot of missing data in many subjects. For example, in the Alzheimer's Disease Neuroimaging Initiative (ADNI study, almost half of the subjects do not have PET images. In this paper, we propose a new and flexible binary classification method, namely Multi-task Linear Programming Discriminant (MLPD analysis, for the incomplete multi-source feature learning. Specifically, we decompose the classification problem into different classification tasks, i.e., one for each combination of available data sources. To solve all different classification tasks jointly, our proposed MLPD method links them together by constraining them to achieve the similar estimated mean difference between the two classes (under classification for those shared features. Compared with the state-of-the-art incomplete Multi-Source Feature (iMSF learning method, instead of constraining different classification tasks to choose a common feature subset for those shared features, MLPD can flexibly and adaptively choose different feature subsets for different classification tasks. Furthermore, our proposed MLPD method can be efficiently implemented by linear programming. To validate our MLPD method, we perform experiments on the ADNI baseline dataset with the incomplete MRI and PET images from 167 progressive MCI (pMCI subjects and 226 stable MCI (sMCI subjects. We further compared our method with the iMSF method (using incomplete MRI and PET images and also the single-task classification method (using only MRI or only subjects with both MRI and

The systematic study of the influence of neutron excess on the fusion cross-sections using different proximity-type potentials

International Nuclear Information System (INIS)

Ghodsi, O.N.; Gharaei, R.

2012-01-01

Using different types of proximity potentials, we have examined the trend of variations of barrier characteristics (barrier height and its position) as well as fusion cross-sections for 50 isotopic systems including various collisions of C, O, Mg, Si, S, Ca, Ar, Ti and Ni nuclei with the 1 ≤ N/Z < 1.6 condition for compound systems. The results of our studies reveal that the relationships between the increase of barrier positions and the decrease of barrier heights are both linear with the increase of the N/Z ratio. Moreover, fusion cross-sections also enhance linearly with the increase of this ratio. (orig.)

Linear programming optimization of nuclear energy strategy with sodium-cooled fast reactors

International Nuclear Information System (INIS)

Lee, Je Whan; Jeong, Yong Hoon; Chang, Yoon Il; Chang, Soon Heung

2011-01-01

Nuclear power has become an essential part of electricity generation to meet the continuous growth of electricity demand. A Sodium-cooled Fast Reactor (SFR) was developed to extend uranium resource utilization under a growing nuclear energy scenario while concomitantly providing a nuclear waste management solution. Key questions in this scenario are when to introduce SFRs and how many reactors should be introduced. In this study, a methodology using Linear Programming is employed in order to quantify an optimized growth pattern of a nuclear energy system comprising light water reactors and SFRs. The optimization involves tradeoffs between SFR capital cost premiums and the total system U3O8 price premiums. Optimum nuclear growth patterns for several scenarios are presented, as well as sensitivity analyses of important input parameters

Linear Colliders

International Nuclear Information System (INIS)

Alcaraz, J.

2001-01-01

After several years of study e''+ e''- linear colliders in the TeV range have emerged as the major and optimal high-energy physics projects for the post-LHC era. These notes summarize the present status form the main accelerator and detector features to their physics potential. The LHC era. These notes summarize the present status, from the main accelerator and detector features to their physics potential. The LHC is expected to provide first discoveries in the new energy domain, whereas an e''+ e''- linear collider in the 500 GeV-1 TeV will be able to complement it to an unprecedented level of precision in any possible areas: Higgs, signals beyond the SM and electroweak measurements. It is evident that the Linear Collider program will constitute a major step in the understanding of the nature of the new physics beyond the Standard Model. (Author) 22 refs

Mixed integer linear programming for maximum-parsimony phylogeny inference.

Science.gov (United States)

Sridhar, Srinath; Lam, Fumei; Blelloch, Guy E; Ravi, R; Schwartz, Russell

2008-01-01

Reconstruction of phylogenetic trees is a fundamental problem in computational biology. While excellent heuristic methods are available for many variants of this problem, new advances in phylogeny inference will be required if we are to be able to continue to make effective use of the rapidly growing stores of variation data now being gathered. In this paper, we present two integer linear programming (ILP) formulations to find the most parsimonious phylogenetic tree from a set of binary variation data. One method uses a flow-based formulation that can produce exponential numbers of variables and constraints in the worst case. The method has, however, proven extremely efficient in practice on datasets that are well beyond the reach of the available provably efficient methods, solving several large mtDNA and Y-chromosome instances within a few seconds and giving provably optimal results in times competitive with fast heuristics than cannot guarantee optimality. An alternative formulation establishes that the problem can be solved with a polynomial-sized ILP. We further present a web server developed based on the exponential-sized ILP that performs fast maximum parsimony inferences and serves as a front end to a database of precomputed phylogenies spanning the human genome.

A linear programming model for protein inference problem in shotgun proteomics.

Science.gov (United States)

Huang, Ting; He, Zengyou

2012-11-15

Assembling peptides identified from tandem mass spectra into a list of proteins, referred to as protein inference, is an important issue in shotgun proteomics. The objective of protein inference is to find a subset of proteins that are truly present in the sample. Although many methods have been proposed for protein inference, several issues such as peptide degeneracy still remain unsolved. In this article, we present a linear programming model for protein inference. In this model, we use a transformation of the joint probability that each peptide/protein pair is present in the sample as the variable. Then, both the peptide probability and protein probability can be expressed as a formula in terms of the linear combination of these variables. Based on this simple fact, the protein inference problem is formulated as an optimization problem: minimize the number of proteins with non-zero probabilities under the constraint that the difference between the calculated peptide probability and the peptide probability generated from peptide identification algorithms should be less than some threshold. This model addresses the peptide degeneracy issue by forcing some joint probability variables involving degenerate peptides to be zero in a rigorous manner. The corresponding inference algorithm is named as ProteinLP. We test the performance of ProteinLP on six datasets. Experimental results show that our method is competitive with the state-of-the-art protein inference algorithms. The source code of our algorithm is available at: https://sourceforge.net/projects/prolp/. zyhe@dlut.edu.cn. Supplementary data are available at Bioinformatics Online.

Proximity effect at Millikelvin temperatures

International Nuclear Information System (INIS)

Mota, A.C.

1986-01-01

Proximity effects have been studied extensively for the past 25 years. Typically, they are in films several thousand angstroms thick at temperatures not so far below T/sub CNS/, the transition temperature of the NS system. Interesting is, however, the proximity effect at temperatures much lower than T/sub CNS/. In this case, the Cooper-pair amplitudes are not small and very long pair penetration lengths into the normal metal can be expected. Thus, we have observed pair penetration lengths. For these investigations very suitable specimens are commercial wires of one filament of NbTi or Nb embedded in a copper matrix. The reasons are the high transmission coefficient at the interface between the copper and the superconductor and the fact that the copper in these commercial wires is rather clean with electron free paths between 5 to 10 μm long. In this paper, the magnetic properties of thick proximity systems in the range of temperatures between T/sub CNS/ and 5 x 10/sup -4/ T/sub CNS/ in both low and high magnetic fields are discussed

Linearly Refined Session Types

Directory of Open Access Journals (Sweden)

Pedro Baltazar

2012-11-01

Full Text Available Session types capture precise protocol structure in concurrent programming, but do not specify properties of the exchanged values beyond their basic type. Refinement types are a form of dependent types that can address this limitation, combining types with logical formulae that may refer to program values and can constrain types using arbitrary predicates. We present a pi calculus with assume and assert operations, typed using a session discipline that incorporates refinement formulae written in a fragment of Multiplicative Linear Logic. Our original combination of session and refinement types, together with the well established benefits of linearity, allows very fine-grained specifications of communication protocols in which refinement formulae are treated as logical resources rather than persistent truths.

Dual pathology proximal median nerve compression of the forearm.

Science.gov (United States)

Murphy, Siun M; Browne, Katherine; Tuite, David J; O'Shaughnessy, Michael

2013-12-01

We report an unusual case of synchronous pathology in the forearm- the coexistence of a large lipoma of the median nerve together with an osteochondroma of the proximal ulna, giving rise to a dual proximal median nerve compression. Proximal median nerve compression neuropathies in the forearm are uncommon compared to the prevalence of distal compression neuropathies (eg Carpal Tunnel Syndrome). Both neural fibrolipomas (Refs. 1,2) and osteochondromas of the proximal ulna (Ref. 3) in isolation are rare but well documented. Unlike that of a distal compression, a proximal compression of the median nerve will often have a definite cause. Neural fibrolipoma, also called fibrolipomatous hamartoma are rare, slow-growing, benign tumours of peripheral nerves, most often occurring in the median nerve of younger patients. To our knowledge, this is the first report of such dual pathology in the same forearm, giving rise to a severe proximal compression of the median nerve. In this case, the nerve was being pushed anteriorly by the osteochondroma, and was being compressed from within by the intraneural lipoma. This unusual case highlights the advantage of preoperative imaging as part of the workup of proximal median nerve compression. Copyright © 2013 British Association of Plastic, Reconstructive and Aesthetic Surgeons. Published by Elsevier Ltd. All rights reserved.

Use of Linear Programming to Develop Cost-Minimized Nutritionally Adequate Health Promoting Food Baskets

DEFF Research Database (Denmark)

Parlesak, A.; Tetens, Inge; Dejgård Jensen, Jørgen

2016-01-01

programming. The FBs were defined using five different constraints: cultural acceptability (CA), or dietary guidelines (DG), or nutrient recommendations (N), or cultural acceptability and nutrient recommendations (CAN), or dietary guidelines and nutrient recommendations (DGN). The variety and number of foods...... in each of the resulting five baskets was increased through limiting the relative share of individual foods. The one-day version of N contained only 12 foods at the minimum cost of DKK 27 (€ 3.6). The CA, DG, and DGN were about twice of this and the CAN cost ~DKK 81 (€ 10.8). The baskets with the greater...... variety of foods contained from 70 (CAN) to 134 (DGN) foods and cost between DKK 60 (€ 8.1, N) and DKK 125 (€ 16.8, DGN). Ensuring that the food baskets cover both dietary guidelines and nutrient recommendations doubled the cost while cultural acceptability (CAN) tripled it. Use of linear programming...

New approach to solve symmetric fully fuzzy linear systems

Indian Academy of Sciences (India)

concepts of fuzzy set theory and then define a fully fuzzy linear system of equations. .... To represent the above problem as fully fuzzy linear system, we represent x .... Fully fuzzy linear systems can be solved by Linear programming approach, ...

A Test of a Linear Programming Model as an Optimal Solution to the Problem of Combining Methods of Reading Instruction

Science.gov (United States)

Mills, James W.; And Others

1973-01-01

The Study reported here tested an application of the Linear Programming Model at the Reading Clinic of Drew University. Results, while not conclusive, indicate that this approach yields greater gains in speed scores than a traditional approach for this population. (Author)

Highlights of the SLD Physics Program at the SLAC Linear Collider

Energy Technology Data Exchange (ETDEWEB)

Willocq, Stephane

2001-09-07

Starting in 1989, and continuing through the 1990s, high-energy physics witnessed a flowering of precision measurements in general and tests of the standard model in particular, led by e{sup +}e{sup -} collider experiments operating at the Z{sup 0} resonance. Key contributions to this work came from the SLD collaboration at the SLAC Linear Collider. By exploiting the unique capabilities of this pioneering accelerator and the SLD detector, including a polarized electron beam, exceptionally small beam dimensions, and a CCD pixel vertex detector, SLD produced a broad array of electroweak, heavy-flavor, and QCD measurements. Many of these results are one of a kind or represent the world's standard in precision. This article reviews the highlights of the SLD physics program, with an eye toward associated advances in experimental technique, and the contribution of these measurements to our dramatically improved present understanding of the standard model and its possible extensions.

An Approximate Redistributed Proximal Bundle Method with Inexact Data for Minimizing Nonsmooth Nonconvex Functions

Directory of Open Access Journals (Sweden)

Jie Shen

2015-01-01

Full Text Available We describe an extension of the redistributed technique form classical proximal bundle method to the inexact situation for minimizing nonsmooth nonconvex functions. The cutting-planes model we construct is not the approximation to the whole nonconvex function, but to the local convexification of the approximate objective function, and this kind of local convexification is modified dynamically in order to always yield nonnegative linearization errors. Since we only employ the approximate function values and approximate subgradients, theoretical convergence analysis shows that an approximate stationary point or some double approximate stationary point can be obtained under some mild conditions.

Method for linearizing the potentiometric curves of precipitation titration in nonaqueous and aqueous-organic solutions

International Nuclear Information System (INIS)

Bykova, L.N.; Chesnokova, O.Ya.; Orlova, M.V.

1995-01-01

The method for linearizing the potentiometric curves of precipitation titration is studied for its application in the determination of halide ions (Cl - , Br - , I - ) in dimethylacetamide, dimethylformamide, in which titration is complicated by additional equilibrium processes. It is found that the method of linearization permits the determination of the titrant volume at the end point of titration to high accuracy in the case of titration curves without a potential jump in the proximity of the equivalent point (5 x 10 -5 M). 3 refs., 2 figs., 3 tabs

Systems analysis on the condition of market penetration for hydrogen technologies using linear programming model

International Nuclear Information System (INIS)

Kato, K.; Ihara, S.

1993-01-01

Hydrogen is expected to be an important energy carrier, especially in the frame of global warming problem solution. The purpose of this study is to examine the condition of market penetration of hydrogen technologies in reducing CO 2 emissions. A multi-time-period linear programming model (MARKAL, Market Allocation)) is used to explore technology options and cost for meeting the energy demands while reducing CO 2 emissions from energy systems. The results show that hydrogen technologies become economical when CO 2 emissions are stringently constrained. 9 figs., 2 refs

Conditions for the Solvability of the Linear Programming Formulation for Constrained Discounted Markov Decision Processes

Energy Technology Data Exchange (ETDEWEB)

Dufour, F., E-mail: dufour@math.u-bordeaux1.fr [Institut de Mathématiques de Bordeaux, INRIA Bordeaux Sud Ouest, Team: CQFD, and IMB (France); Prieto-Rumeau, T., E-mail: tprieto@ccia.uned.es [UNED, Department of Statistics and Operations Research (Spain)

2016-08-15

We consider a discrete-time constrained discounted Markov decision process (MDP) with Borel state and action spaces, compact action sets, and lower semi-continuous cost functions. We introduce a set of hypotheses related to a positive weight function which allow us to consider cost functions that might not be bounded below by a constant, and which imply the solvability of the linear programming formulation of the constrained MDP. In particular, we establish the existence of a constrained optimal stationary policy. Our results are illustrated with an application to a fishery management problem.

Effect of age on proximal esophageal response to swallowing

Directory of Open Access Journals (Sweden)

Roberto Oliveira Dantas

2010-12-01

Full Text Available CONTEXT: It has been demonstrated that the ageing process affects esophageal motility. OBJECTIVES: To evaluate the effect of the age on the proximal esophageal response to wet swallows. METHOD: We measured the proximal esophageal response to swallows of a 5 mL bolus of water in 69 healthy volunteers, 20 of them aged 18-30 years (group I, 27 aged 31-50 years (group II, and 22 aged 51-74 years (group III. We used the manometric method with continuous perfusion. The proximal esophageal contractions were recorded 5 cm from a pharyngeal recording site located 1 cm above the upper esophageal sphincter. The time between the onset of the pharyngeal and of the proximal esophageal recording (pharyngeal-esophageal time and the amplitude, duration and area under the curve of the proximal esophageal contraction were measured. RESULTS: The pharyngeal-esophageal time was shorter in group I subjects than in group II and III subjects (P<0.05. The duration of proximal esophageal contractions was longer in group I than in groups II and III (P<0.001. There was no differences between groups in the amplitude or area under the curve of contractions. There were no differences between groups II and III for any of the measurements. CONCLUSION: We conclude that the age may affects the response of the proximal esophagus to wet swallows.

Duality in non-linear programming

Science.gov (United States)

Jeyalakshmi, K.

2018-04-01

In this paper we consider duality and converse duality for a programming problem involving convex objective and constraint functions with finite dimensional range. We do not assume any constraint qualification. The dual is presented by reducing the problem to a standard Lagrange multiplier problem.

Linear atrophy and vascular fragility following ultrasoundguided triamcinolone injection for DeQuervain tendonitis

OpenAIRE

Willardson, Hal B; Buck, Shannon; Neiner, James

2017-01-01

A 64 year-old woman presented with a one-yearhistory of purpuric, atrophic, linear patches alongthe left lateral forearm. The patient had receivedtwo ultrasound-guided triamcinolone injectionsone year earlier into her left extensor pollicis brevisand abductor pollicis longus tendon sheathsfor DeQuervain tendonitis. In the seven monthsfollowing the second injection, the patient developedatrophy, purpura, and telangiectasias starting at thesite of injection and extending proximally, followingth...

Maximum likelihood pedigree reconstruction using integer linear programming.

Science.gov (United States)

Cussens, James; Bartlett, Mark; Jones, Elinor M; Sheehan, Nuala A

2013-01-01

Large population biobanks of unrelated individuals have been highly successful in detecting common genetic variants affecting diseases of public health concern. However, they lack the statistical power to detect more modest gene-gene and gene-environment interaction effects or the effects of rare variants for which related individuals are ideally required. In reality, most large population studies will undoubtedly contain sets of undeclared relatives, or pedigrees. Although a crude measure of relatedness might sometimes suffice, having a good estimate of the true pedigree would be much more informative if this could be obtained efficiently. Relatives are more likely to share longer haplotypes around disease susceptibility loci and are hence biologically more informative for rare variants than unrelated cases and controls. Distant relatives are arguably more useful for detecting variants with small effects because they are less likely to share masking environmental effects. Moreover, the identification of relatives enables appropriate adjustments of statistical analyses that typically assume unrelatedness. We propose to exploit an integer linear programming optimisation approach to pedigree learning, which is adapted to find valid pedigrees by imposing appropriate constraints. Our method is not restricted to small pedigrees and is guaranteed to return a maximum likelihood pedigree. With additional constraints, we can also search for multiple high-probability pedigrees and thus account for the inherent uncertainty in any particular pedigree reconstruction. The true pedigree is found very quickly by comparison with other methods when all individuals are observed. Extensions to more complex problems seem feasible. © 2012 Wiley Periodicals, Inc.

SIGMA1-2007, Doppler Broadening ENDF Format Linear-Linear. Interpolated Point Cross Section

International Nuclear Information System (INIS)

2007-01-01

1 - Description of problem or function: SIGMA-1 Doppler broadens evaluated Cross sections given in the linear-linear interpolation form of the ENDF/B Format to one final temperature. The data is Doppler broadened, thinned, and output in the ENDF/B Format. IAEA0854/15: This version include the updates up to January 30, 2007. Changes in ENDF/B-VII Format and procedures, as well as the evaluations themselves, make it impossible for versions of the ENDF/B pre-processing codes earlier than PREPRO 2007 (2007 Version) to accurately process current ENDF/B-VII evaluations. The present code can handle all existing ENDF/B-VI evaluations through release 8, which will be the last release of ENDF/B-VI. 2 - Modifications from previous versions: Sigma-1 VERS. 2007-1 (Jan. 2007): checked against all ENDF/B-VII; increased page size from 60,000 to 360,000 energy points 3 - Method of solution: The energy grid is selected to ensure that the broadened data is linear-linear interpolable. SIGMA-1 starts from the free-atom Doppler broadening equations and adds the assumptions of linear data within the table and constant data outside the range of the table. If the Original data is not at zero Kelvin, the data is broadened by the effective temperature difference to the final temperature. If the data is already at a temperature higher than the final temperature, Doppler broadening is not performed. 4 - Restrictions on the complexity of the problem: The input to SIGMA-1 must be data which vary linearly in energy and cross section between tabulated points. The LINEAR program provides such data. LINEAR uses only the ENDF/B BCD Format tape and copies all sections except File 3 as read. Since File 3 data are in identical Format for ENDF/B Versions I through VI, the program can be used with all these versions. - The present version Doppler broadens only to one final temperature

Decoherence of histories and hydrodynamic equations for a linear oscillator chain

International Nuclear Information System (INIS)

Halliwell, J.J.

2003-01-01

We investigate the decoherence of histories of local densities for linear oscillators models. It is shown that histories of local number, momentum and energy density are approximately decoherent, when coarse grained over sufficiently large volumes. Decoherence arises directly from the proximity of these variables to exactly conserved quantities (which are exactly decoherent), and not from environmentally induced decoherence. We discuss the approach to local equilibrium and the subsequent emergence of hydrodynamic equations for the local densities

PROXIMAL: a method for Prediction of Xenobiotic Metabolism.

Science.gov (United States)

Yousofshahi, Mona; Manteiga, Sara; Wu, Charmian; Lee, Kyongbum; Hassoun, Soha

2015-12-22

Contamination of the environment with bioactive chemicals has emerged as a potential public health risk. These substances that may cause distress or disease in humans can be found in air, water and food supplies. An open question is whether these chemicals transform into potentially more active or toxic derivatives via xenobiotic metabolizing enzymes expressed in the body. We present a new prediction tool, which we call PROXIMAL (Prediction of Xenobiotic Metabolism) for identifying possible transformation products of xenobiotic chemicals in the liver. Using reaction data from DrugBank and KEGG, PROXIMAL builds look-up tables that catalog the sites and types of structural modifications performed by Phase I and Phase II enzymes. Given a compound of interest, PROXIMAL searches for substructures that match the sites cataloged in the look-up tables, applies the corresponding modifications to generate a panel of possible transformation products, and ranks the products based on the activity and abundance of the enzymes involved. PROXIMAL generates transformations that are specific for the chemical of interest by analyzing the chemical's substructures. We evaluate the accuracy of PROXIMAL's predictions through case studies on two environmental chemicals with suspected endocrine disrupting activity, bisphenol A (BPA) and 4-chlorobiphenyl (PCB3). Comparisons with published reports confirm 5 out of 7 and 17 out of 26 of the predicted derivatives for BPA and PCB3, respectively. We also compare biotransformation predictions generated by PROXIMAL with those generated by METEOR and Metaprint2D-react, two other prediction tools. PROXIMAL can predict transformations of chemicals that contain substructures recognizable by human liver enzymes. It also has the ability to rank the predicted metabolites based on the activity and abundance of enzymes involved in xenobiotic transformation.

Optimal Airport Surface Traffic Planning Using Mixed-Integer Linear Programming

Directory of Open Access Journals (Sweden)

P. C. Roling

2008-01-01

Full Text Available We describe an ongoing research effort pertaining to the development of a surface traffic automation system that will help controllers to better coordinate surface traffic movements related to arrival and departure traffic. More specifically, we describe the concept for a taxi-planning support tool that aims to optimize the routing and scheduling of airport surface traffic in such a way as to deconflict the taxi plans while optimizing delay, total taxi-time, or some other airport efficiency metric. Certain input parameters related to resource demand, such as the expected landing times and the expected pushback times, are rather difficult to predict accurately. Due to uncertainty in the input data driving the taxi-planning process, the taxi-planning tool is designed such that it produces solutions that are robust to uncertainty. The taxi-planning concept presented herein, which is based on mixed-integer linear programming, is designed such that it is able to adapt to perturbations in these input conditions, as well as to account for failure in the actual execution of surface trajectories. The capabilities of the tool are illustrated in a simple hypothetical airport.

Learning oncogenetic networks by reducing to mixed integer linear programming.

Science.gov (United States)

Shahrabi Farahani, Hossein; Lagergren, Jens

2013-01-01

Cancer can be a result of accumulation of different types of genetic mutations such as copy number aberrations. The data from tumors are cross-sectional and do not contain the temporal order of the genetic events. Finding the order in which the genetic events have occurred and progression pathways are of vital importance in understanding the disease. In order to model cancer progression, we propose Progression Networks, a special case of Bayesian networks, that are tailored to model disease progression. Progression networks have similarities with Conjunctive Bayesian Networks (CBNs) [1],a variation of Bayesian networks also proposed for modeling disease progression. We also describe a learning algorithm for learning Bayesian networks in general and progression networks in particular. We reduce the hard problem of learning the Bayesian and progression networks to Mixed Integer Linear Programming (MILP). MILP is a Non-deterministic Polynomial-time complete (NP-complete) problem for which very good heuristics exists. We tested our algorithm on synthetic and real cytogenetic data from renal cell carcinoma. We also compared our learned progression networks with the networks proposed in earlier publications. The software is available on the website https://bitbucket.org/farahani/diprog.

Discovery of Boolean metabolic networks: integer linear programming based approach.

Science.gov (United States)

Qiu, Yushan; Jiang, Hao; Ching, Wai-Ki; Cheng, Xiaoqing

2018-04-11

Traditional drug discovery methods focused on the efficacy of drugs rather than their toxicity. However, toxicity and/or lack of efficacy are produced when unintended targets are affected in metabolic networks. Thus, identification of biological targets which can be manipulated to produce the desired effect with minimum side-effects has become an important and challenging topic. Efficient computational methods are required to identify the drug targets while incurring minimal side-effects. In this paper, we propose a graph-based computational damage model that summarizes the impact of enzymes on compounds in metabolic networks. An efficient method based on Integer Linear Programming formalism is then developed to identify the optimal enzyme-combination so as to minimize the side-effects. The identified target enzymes for known successful drugs are then verified by comparing the results with those in the existing literature. Side-effects reduction plays a crucial role in the study of drug development. A graph-based computational damage model is proposed and the theoretical analysis states the captured problem is NP-completeness. The proposed approaches can therefore contribute to the discovery of drug targets. Our developed software is available at " http://hkumath.hku.hk/~wkc/APBC2018-metabolic-network.zip ".

The developmental spectrum of proximal radioulnar synostosis

Energy Technology Data Exchange (ETDEWEB)

Elliott, Alison M. [University of Manitoba, Winnipeg Regional Health Association Program of Genetics and Metabolism, Winnipeg, MB (Canada); University of Manitoba, Department of Paediatrics and Child Health, Winnipeg, MB (Canada); University of Manitoba, Department of Biochemistry and Medical Genetics, Winnipeg, MB (Canada); University of Manitoba, WRHA Program of Genetics and Metabolism, Departments of Paediatrics and Child Health, Biochemistry and Medical Genetics, Winnipeg, MB (Canada); Kibria, Lisa [University of Manitoba, Department of School of Medical Rehabilitation, Winnipeg, MB (Canada); Reed, Martin H. [University of Manitoba, Department of Paediatrics and Child Health, Winnipeg, MB (Canada); University of Manitoba, Department of Biochemistry and Medical Genetics, Winnipeg, MB (Canada); University of Manitoba, Department of Diagnostic Imaging, Winnipeg, MB (Canada)

2010-01-15

Proximal radioulnar synostosis is a rare upper limb malformation. The elbow is first identifiable at 35 days (after conception), at which stage the cartilaginous anlagen of the humerus, radius and ulna are continuous. Subsequently, longitudinal segmentation produces separation of the distal radius and ulna. However, temporarily, the proximal ends are united and continue to share a common perichondrium. We investigated the hypothesis that posterior congenital dislocation of the radial head and proximal radioulnar fusion are different clinical manifestations of the same primary developmental abnormality. Records were searched for ''proximal radioulnar fusion/posterior radial head dislocation'' in patients followed at the local Children's Hospital and Rehabilitation Centre for Children. Relevant radiographic, demographic and clinical data were recorded. Ethics approval was obtained through the University Research Ethics Board. In total, 28 patients met the inclusion criteria. The majority of patients (16) had bilateral involvement; eight with posterior dislocation of the radial head only; five had posterior radial head dislocation with radioulnar fusion and two had radioulnar fusion without dislocation. One patient had bilateral proximal radioulnar fusion and posterior dislocation of the left radial head. Nine patients had only left-sided involvement, and three had only right-sided involvement.The degree of proximal fusion varied, with some patients showing 'complete' proximal fusion and others showing fusion that occurred slightly distal to the radial head: 'partially separated.' Associated disorders in our cohort included Poland syndrome (two patients), Cornelia de Lange syndrome, chromosome anomalies (including tetrasomy X) and Cenani Lenz syndactyly. The suggestion of a developmental relationship between posterior dislocation of the radial head and proximal radioulnar fusion is supported by the fact that both anomalies

NEAR-INFRARED LINEAR POLARIZATION OF ULTRACOOL DWARFS

International Nuclear Information System (INIS)

Zapatero Osorio, M. R.; Bejar, V. J. S.; Rebolo, R.; Acosta-Pulido, J. A.; Manchado, A.; Pena Ramirez, K.; Goldman, B.; Caballero, J. A.

2011-01-01

We report on near-infrared J- and H-band linear polarimetric photometry of eight ultracool dwarfs (two late-M, five L0-L7.5, and one T2.5) with known evidence for photometric variability due to dust clouds, anomalous red infrared colors, or low-gravity atmospheres. The polarimetric data were acquired with the LIRIS instrument on the William Herschel Telescope. We also provide mid-infrared photometry in the interval 3.4-24 μm for some targets obtained with Spitzer and WISE, which has allowed us to confirm the peculiar red colors of five sources in the sample. We can impose modest upper limits of 0.9% and 1.8% on the linear polarization degree for seven targets with a confidence of 99%. Only one source, 2MASS J02411151-0326587 (L0), appears to be strongly polarized (P ∼ 3%) in the J band with a significance level of P/σ P ∼ 10. The likely origin of its linearly polarized light and rather red infrared colors may reside in a surrounding disk with an asymmetric distribution of grains. Given its proximity (66 ± 8 pc), this object becomes an excellent target for the direct detection of the disk.

Enhancement of Linear Circuit Program

DEFF Research Database (Denmark)

Gaunholt, Hans; Dabu, Mihaela; Beldiman, Octavian

1996-01-01

In this report a preliminary user friendly interface has been added to the LCP2 program making it possible to describe an electronic circuit by actually drawing the circuit on the screen. Component values and other options and parameters can easily be set by the aid of the interface. The interface...

An anatomical study of the proximal aspect of the medial femoral condyle to define the proximal-distal condylar length

Directory of Open Access Journals (Sweden)

Chia-Ming Chang

2017-01-01

Full Text Available Objective: Despite its possible role in knee arthroplasty, the proximal-distal condylar length (PDCL of the femur has never been reported in the literature. We conducted an anatomic study of the proximal aspect of the medial femoral condyle to propose a method for measuring the PDCL. Materials and Methods: Inspection of dried bone specimens was carried out to assure the most proximal condylar margin (MPCM as the eligible starting point to measure the PDCL. Simulation surgery was performed on seven pairs of cadaveric knees to verify the clinical application of measuring the PDCL after locating the MPCM. Interobserver reliability of this procedure was also analyzed. Results: Observation of the bone specimens showed that the MPCM is a concavity formed by the junction of the distal end of the supracondylar ridge and the proximal margin of the medial condyle. This anatomically distinctive structure made the MPCM an unambiguous landmark. The cadaveric simulation surgical dissection demonstrated that the MPCM is easily accessed in a surgical setting, making the measurement of the PDCL plausible. The intraclass correlation coefficient was 0.78, indicating good interobserver reliability for this technique. Conclusion: This study has suggested that the PDCL can be measured based on the MPCM in a surgical setting. PDCL measurement might be useful in joint line position management, selection of femoral component sizes, and other applications related to the proximal-distal dimension of the knee. Further investigation is required.

Nonlinear quasi-static finite element simulations predict in vitro strength of human proximal femora assessed in a dynamic sideways fall setup.

Science.gov (United States)

Varga, Peter; Schwiedrzik, Jakob; Zysset, Philippe K; Fliri-Hofmann, Ladina; Widmer, Daniel; Gueorguiev, Boyko; Blauth, Michael; Windolf, Markus

2016-04-01

Osteoporotic proximal femur fractures are caused by low energy trauma, typically when falling on the hip from standing height. Finite element simulations, widely used to predict the fracture load of femora in fall, usually include neither mass-related inertial effects, nor the viscous part of bone׳s material behavior. The aim of this study was to elucidate if quasi-static non-linear homogenized finite element analyses can predict in vitro mechanical properties of proximal femora assessed in dynamic drop tower experiments. The case-specific numerical models of 13 femora predicted the strength (R(2)=0.84, SEE=540N, 16.2%), stiffness (R(2)=0.82, SEE=233N/mm, 18.0%) and fracture energy (R(2)=0.72, SEE=3.85J, 39.6%); and provided fair qualitative matches with the fracture patterns. The influence of material anisotropy was negligible for all predictions. These results suggest that quasi-static homogenized finite element analysis may be used to predict mechanical properties of proximal femora in the dynamic sideways fall situation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Evaluation and Management of Proximal Humerus Fractures

Directory of Open Access Journals (Sweden)

Ekaterina Khmelnitskaya

2012-01-01

Full Text Available Proximal humerus fractures are common injuries, especially among older osteoporotic women. Restoration of function requires a thorough understanding of the neurovascular, musculotendinous, and bony anatomy. This paper addresses the relevant anatomy and highlights various management options, including indication for arthroplasty. In the vast majority of cases, proximal humerus fractures may be treated nonoperatively. In the case of displaced fractures, when surgical intervention may be pursued, numerous constructs have been investigated. Of these, the proximal humerus locking plate is the most widely used. Arthroplasty is generally reserved for comminuted 4-part fractures, head-split fractures, or fractures with significant underlying arthritic changes. Reverse total shoulder arthroplasty is reserved for patients with a deficient rotator cuff, or highly comminuted tuberosities.

The Life Saving Effects of Hospital Proximity

DEFF Research Database (Denmark)

Bertoli, Paola; Grembi, Veronica

We assess the lifesaving effect of hospital proximity using data on fatality rates of road-traffic accidents. While most of the literature on this topic is based on changes in distance to the nearest hospital triggered by hospital closures and use OLS estimates, our identification comes from......) increases the fatality rate by 13.84% on the sample average. This is equal to a 0.92 additional death per every 100 accidents. We show that OLS estimates provide a downward biased measure of the real effect of hospital proximity because they do not fully solve spatial sorting problems. Proximity matters...... more when the road safety is low; the emergency service is not properly organized, and the nearest hospital has lower quality standards....

Momentum and Stochastic Momentum for Stochastic Gradient, Newton, Proximal Point and Subspace Descent Methods

KAUST Repository

Loizou, Nicolas

2017-12-27

In this paper we study several classes of stochastic optimization algorithms enriched with heavy ball momentum. Among the methods studied are: stochastic gradient descent, stochastic Newton, stochastic proximal point and stochastic dual subspace ascent. This is the first time momentum variants of several of these methods are studied. We choose to perform our analysis in a setting in which all of the above methods are equivalent. We prove global nonassymptotic linear convergence rates for all methods and various measures of success, including primal function values, primal iterates (in L2 sense), and dual function values. We also show that the primal iterates converge at an accelerated linear rate in the L1 sense. This is the first time a linear rate is shown for the stochastic heavy ball method (i.e., stochastic gradient descent method with momentum). Under somewhat weaker conditions, we establish a sublinear convergence rate for Cesaro averages of primal iterates. Moreover, we propose a novel concept, which we call stochastic momentum, aimed at decreasing the cost of performing the momentum step. We prove linear convergence of several stochastic methods with stochastic momentum, and show that in some sparse data regimes and for sufficiently small momentum parameters, these methods enjoy better overall complexity than methods with deterministic momentum. Finally, we perform extensive numerical testing on artificial and real datasets, including data coming from average consensus problems.

Momentum and Stochastic Momentum for Stochastic Gradient, Newton, Proximal Point and Subspace Descent Methods

KAUST Repository

Loizou, Nicolas; Richtarik, Peter

2017-01-01

In this paper we study several classes of stochastic optimization algorithms enriched with heavy ball momentum. Among the methods studied are: stochastic gradient descent, stochastic Newton, stochastic proximal point and stochastic dual subspace ascent. This is the first time momentum variants of several of these methods are studied. We choose to perform our analysis in a setting in which all of the above methods are equivalent. We prove global nonassymptotic linear convergence rates for all methods and various measures of success, including primal function values, primal iterates (in L2 sense), and dual function values. We also show that the primal iterates converge at an accelerated linear rate in the L1 sense. This is the first time a linear rate is shown for the stochastic heavy ball method (i.e., stochastic gradient descent method with momentum). Under somewhat weaker conditions, we establish a sublinear convergence rate for Cesaro averages of primal iterates. Moreover, we propose a novel concept, which we call stochastic momentum, aimed at decreasing the cost of performing the momentum step. We prove linear convergence of several stochastic methods with stochastic momentum, and show that in some sparse data regimes and for sufficiently small momentum parameters, these methods enjoy better overall complexity than methods with deterministic momentum. Finally, we perform extensive numerical testing on artificial and real datasets, including data coming from average consensus problems.