Convex programming with fast proximal and linear operators
Wytock, Matt; Wang, Po-Wei; Kolter, J. Zico
2015-01-01
We present Epsilon, a system for general convex programming using fast linear and proximal operators. As with existing convex programming frameworks, users specify convex optimization problems using a natural grammar for mathematical expressions, composing functions in a way that is guaranteed to be convex by the rules of disciplined convex programming. Given such an input, the Epsilon compiler transforms the optimization problem into a mathematically equivalent form consisting only of functi...
Directory of Open Access Journals (Sweden)
Congying Han
2013-01-01
is proved that the new algorithm can terminate at an ε-optimal solution within O(1/ε iterations. Moreover, no line search is needed in this algorithm, and the global convergence can be proved under mild conditions. Numerical results are reported for solving quadratic programs arising from the training of support vector machines, which show that the new algorithm is efficient.
Solow, Daniel
2014-01-01
This text covers the basic theory and computation for a first course in linear programming, including substantial material on mathematical proof techniques and sophisticated computation methods. Includes Appendix on using Excel. 1984 edition.
Karloff, Howard
1991-01-01
To this reviewer’s knowledge, this is the first book accessible to the upper division undergraduate or beginning graduate student that surveys linear programming from the Simplex Method…via the Ellipsoid algorithm to Karmarkar’s algorithm. Moreover, its point of view is algorithmic and thus it provides both a history and a case history of work in complexity theory. The presentation is admirable; Karloff's style is informal (even humorous at times) without sacrificing anything necessary for understanding. Diagrams (including horizontal brackets that group terms) aid in providing clarity. The end-of-chapter notes are helpful...Recommended highly for acquisition, since it is not only a textbook, but can also be used for independent reading and study. —Choice Reviews The reader will be well served by reading the monograph from cover to cover. The author succeeds in providing a concise, readable, understandable introduction to modern linear programming. —Mathematics of Computing This is a textbook intend...
Tuey, R. C.
1972-01-01
Computer solutions of linear programming problems are outlined. Information covers vector spaces, convex sets, and matrix algebra elements for solving simultaneous linear equations. Dual problems, reduced cost analysis, ranges, and error analysis are illustrated.
Lawson, C. L.; Krogh, F. T.; Gold, S. S.; Kincaid, D. R.; Sullivan, J.; Williams, E.; Hanson, R. J.; Haskell, K.; Dongarra, J.; Moler, C. B.
1982-01-01
The Basic Linear Algebra Subprograms (BLAS) library is a collection of 38 FORTRAN-callable routines for performing basic operations of numerical linear algebra. BLAS library is portable and efficient source of basic operations for designers of programs involving linear algebriac computations. BLAS library is supplied in portable FORTRAN and Assembler code versions for IBM 370, UNIVAC 1100 and CDC 6000 series computers.
Linear Projective Program Syntax
Bergstra, J.A.; Bethke, I.
2004-01-01
Based on an extremely simple program notation more advanced program features can be developed in linear projective program syntax such as conditional statements, while loops, recursion, use of an evaluation stack, object classes, method calls etc. Taking care of a cumulative and bottom up
Linear programming using Matlab
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...
Klumpp, A. R.; Lawson, C. L.
1988-01-01
Routines provided for common scalar, vector, matrix, and quaternion operations. Computer program extends Ada programming language to include linear-algebra capabilities similar to HAS/S programming language. Designed for such avionics applications as software for Space Station.
Linear Programming and Network Flows
Bazaraa, Mokhtar S; Sherali, Hanif D
2011-01-01
The authoritative guide to modeling and solving complex problems with linear programming-extensively revised, expanded, and updated The only book to treat both linear programming techniques and network flows under one cover, Linear Programming and Network Flows, Fourth Edition has been completely updated with the latest developments on the topic. This new edition continues to successfully emphasize modeling concepts, the design and analysis of algorithms, and implementation strategies for problems in a variety of fields, including industrial engineering, management science, operations research
Ferencz, Donald C.; Viterna, Larry A.
1991-01-01
ALPS is a computer program which can be used to solve general linear program (optimization) problems. ALPS was designed for those who have minimal linear programming (LP) knowledge and features a menu-driven scheme to guide the user through the process of creating and solving LP formulations. Once created, the problems can be edited and stored in standard DOS ASCII files to provide portability to various word processors or even other linear programming packages. Unlike many math-oriented LP solvers, ALPS contains an LP parser that reads through the LP formulation and reports several types of errors to the user. ALPS provides a large amount of solution data which is often useful in problem solving. In addition to pure linear programs, ALPS can solve for integer, mixed integer, and binary type problems. Pure linear programs are solved with the revised simplex method. Integer or mixed integer programs are solved initially with the revised simplex, and the completed using the branch-and-bound technique. Binary programs are solved with the method of implicit enumeration. This manual describes how to use ALPS to create, edit, and solve linear programming problems. Instructions for installing ALPS on a PC compatible computer are included in the appendices along with a general introduction to linear programming. A programmers guide is also included for assistance in modifying and maintaining the program.
Elementary linear programming with applications
Kolman, Bernard
1995-01-01
Linear programming finds the least expensive way to meet given needs with available resources. Its results are used in every area of engineering and commerce: agriculture, oil refining, banking, and air transport. Authors Kolman and Beck present the basic notions of linear programming and illustrate how they are used to solve important common problems. The software on the included disk leads students step-by-step through the calculations. The Second Edition is completely revised and provides additional review material on linear algebra as well as complete coverage of elementary linear program
175 Years of Linear Programming
Indian Academy of Sciences (India)
The announcement, by L G Khachiyan, of the poly- nomial solvability of linear programming by the el- lipsoid method, followed by the probabilistic anal- yses of the simplex method in the early 1980's left researchers in linear programming with a dilemma. We had one method that was good in a theoreti- cal sense but poor in ...
Linear Programming across the Curriculum
Yoder, S. Elizabeth; Kurz, M. Elizabeth
2015-01-01
Linear programming (LP) is taught in different departments across college campuses with engineering and management curricula. Modeling an LP problem is taught in every linear programming class. As faculty teaching in Engineering and Management departments, the depth to which teachers should expect students to master this particular type of…
Linear programming foundations and extensions
Vanderbei, Robert J
2001-01-01
Linear Programming: Foundations and Extensions is an introduction to the field of optimization. The book emphasizes constrained optimization, beginning with a substantial treatment of linear programming, and proceeding to convex analysis, network flows, integer programming, quadratic programming, and convex optimization. The book is carefully written. Specific examples and concrete algorithms precede more abstract topics. Topics are clearly developed with a large number of numerical examples worked out in detail. Moreover, Linear Programming: Foundations and Extensions underscores the purpose of optimization: to solve practical problems on a computer. Accordingly, the book is coordinated with free efficient C programs that implement the major algorithms studied: -The two-phase simplex method; -The primal-dual simplex method; -The path-following interior-point method; -The homogeneous self-dual methods. In addition, there are online JAVA applets that illustrate various pivot rules and variants of the simplex m...
175 Years of Linear Programming
Indian Academy of Sciences (India)
The theory of flows in networks began to evolve in the early 1950's. The various linear optimisation questions that could be asked of flows in conserv- ing networks turned out to be neat combinatorial specialisations of linear programming. The simplex method (and its variants) turned out to have very pretty combinatorial ...
LINEAR AND NONLINEAR SEMIDEFINITE PROGRAMMING
Directory of Open Access Journals (Sweden)
Walter Gómez Bofill
2014-12-01
Full Text Available This paper provides a short introduction to optimization problems with semidefinite constraints. Basic duality and optimality conditions are presented. For linear semidefinite programming some advances by dealing with degeneracy and the semidefinite facial reduction are discussed. Two relatively recent areas of application are presented. Finally a short overview of relevant literature on algorithmic approaches for efficiently solving linear and nonlinear semidefinite programming is provided.
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 1999 pp 31-39. Fulltext. Click here to view fulltext PDF. Permanent link: http://www.ias.ac.in/article/fulltext/reso/004/05/0031-0039 ...
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)
The simplex method has been the veritable work- horse of linear programming for five decades now. An elegant geometric interpretation of the simplex method can be visualised by viewing the animation of the algorithm in a column space representation. In fact, it is this interpretation that explains why it is called the simplex ...
175 Years of Linear Programming
Indian Academy of Sciences (India)
in mathematical modeling. Solving such a system is the es- sential task of linear programming. We now describe an elegant syntactic method for this problem known as Fourier elimination. The essential idea in the variable elimination technique is to derive implied equations/inequalities in which one or more variables are ...
ALPS - A LINEAR PROGRAM SOLVER
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.
On the linear programming bound for linear Lee codes.
Astola, Helena; Tabus, Ioan
2016-01-01
Based on an invariance-type property of the Lee-compositions of a linear Lee code, additional equality constraints can be introduced to the linear programming problem of linear Lee codes. In this paper, we formulate this property in terms of an action of the multiplicative group of the field [Formula: see text] on the set of Lee-compositions. We show some useful properties of certain sums of Lee-numbers, which are the eigenvalues of the Lee association scheme, appearing in the linear programming problem of linear Lee codes. Using the additional equality constraints, we formulate the linear programming problem of linear Lee codes in a very compact form, leading to a fast execution, which allows to efficiently compute the bounds for large parameter values of the linear codes.
Solving Linear Fractional Multilevel Programs
Directory of Open Access Journals (Sweden)
Shifali Bhargava
2014-01-01
Full Text Available The linear fractional multilevel programming (LFMP problem has been studied and it has been proved that an optimal solution to this problem occurs at a boundary feasible extreme point. Hence the Kth-best algorithm can be proposed to solve the problem. This property can be applied to quasiconcave multilevel problems provided that the first (n - 1 level objective functions are explicitly quasimonotonic, otherwise it cannot be proved that there exists a boundary feasible extreme point that solves the LFMP problem. (original abstract
Ranking Forestry Investments With Parametric Linear Programming
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.
Index coding via linear programming
Blasiak, Anna; Lubetzky, Eyal
2010-01-01
Index Coding has received considerable attention recently motivated in part by applications such as fast video-on-demand and efficient communication in wireless networks and in part by its connection to Network Coding. The basic setting of Index Coding encodes the side-information relation, the problem input, as an undirected graph and the fundamental parameter is the broadcast rate $\\beta$, the average communication cost per bit for sufficiently long messages (i.e. the non-linear vector capacity). Recent nontrivial bounds on $\\beta$ were derived from the study of other Index Coding capacities (e.g. the scalar capacity $\\beta_1$) by Bar-Yossef et al (FOCS'06), Lubetzky and Stav (FOCS'07) and Alon et al (FOCS'08). However, these indirect bounds shed little light on the behavior of $\\beta$ and its exact value remained unknown for \\emph{any graph} where Index Coding is nontrivial. Our main contribution is a hierarchy of linear programs whose solutions trap $\\beta$ between them. This enables a direct information-...
Computer Program For Linear Algebra
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 algorithms and applications
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...
Investigating Integer Restrictions in Linear Programming
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…
Timetabling an Academic Department with Linear Programming.
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…
Formulating Linear and Integer Linear Programs: A Rogues' Gallery
Brown, Gerald; Robert F.
2007-01-01
INFORMS Transactions on Education, 7, 2007, pp. 153-159. The article of record as published may be located at http://dx.doi.org/10.1287/ited.7.2.153 The art of formulating linear and integer linear programs is, well, an art: It is hard to teach, and even harder to learn. To help demystify this art, we present a set of modeling building blocks that we call “formulettes.” Each formulette consists of a short verbal description that must be expressed in terms of variables and const...
On Solving Linear Complementarity Problems as Linear Programs.
1976-03-01
I,1 c, -, I - - -= 1. I NIRODU CIT I ON Et is a fair’ly well-known fa(t that if a lineas complemenl•arity problem has L solution) then it has a...W. Cottle, "Manifestations of the Schur complement," Linear Algebra and Its Applications, 8 (1974), 189-211. [6] R. W. Cottle and G. B. Dantzig...34Complementarity pivot theory of mathematical programming," Linear Algebra and Its Applications . (1968), 103-125. [7] R. W. Cottle, G. H. Golub and R. S
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...
Linear and integer programming made easy
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...
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.
The Use of Linear Programming for Prediction.
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)
Directory of Open Access Journals (Sweden)
Rashid Siti Raishan Mohd
2017-01-01
Full Text Available Torrefaction is one of the pretreatment processes to upgrade the chemical and physical properties of biomass for power production. In this study, four types of palm oil wastes were selected. The wastes, which consisted of oil palm frond (OPF, palm kernel shell (PKS, palm mesocarp fibre (PMF, and empty fruit bunch (EFB, were subjected to torrefaction process at different temperatures of 240°C, 270°C, 300°C, and 330°C for 30 min residence time. Based on the analysis of torrefied palm oil wastes, it was observed that there is a linear relationship between the properties of torrefied palm oil wastes and torrefaction temperature. Based on this, linear correlation model as a function of mass loss was developed to predict the energy yield (EY, calorific value (HHV, and proximate analysis. A reliable correlation model (R2 > 0.90 for predicting calorific value (HHV, fixed carbon (FC, and volatile matter (VM was obtained, indicating the developed linear model is indeed reliable. Meanwhile, an acceptable coefficient of determination (R2 ≈ 0.75 was obtained when the linear model is used to estimate the energy yield (EY and ash content (ASH. These developed linear correlation models are cost effective and can be used as a tool to predict the properties of palm oil wastes and to assess the suitability of biomass in torrefaction process.
Linear programming mathematics, theory and algorithms
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.
Towards a linear algebra of programming
Oliveira, José Nuno Fonseca
2012-01-01
The Algebra of Programming (AoP) is a discipline for programming from specifications using relation algebra. Specification vagueness and nondeterminism are captured by relations. (Final) implemen- tations are functions. Probabilistic functions are half way between relations and functions: they express the propensity, or like- lihood of ambiguous, multiple outputs. This paper puts forward a basis for a Linear Algebra of Programming (LAoP) extending standard AoP towards probabili...
Fuzzy linear programming for bulb production
Siregar, I.; Suantio, H.; Hanifiah, Y.; Muchtar, M. A.; Nasution, T. H.
2017-01-01
The research was conducted at a bulb company. This company has a high market demand. The increasing of the market demand has caused the company’s production could not fulfill the demand due to production planning is not optimal. Bulb production planning is researched with the aim to enable the company to fulfill the market demand in accordance with the limited resources available. From the data, it is known that the company cannot reach the market demand in the production of the Type A and Type B bulb. In other hands, the Type C bulb is produced exceeds market demand. By using fuzzy linear programming, then obtained the optimal production plans and to reach market demand. Completion of the simple method is done by using software LINGO 13. Application of fuzzy linear programming is being able to increase profits amounted to 7.39% of the ordinary concept of linear programming.
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 ...
Generalised Assignment Matrix Methodology in Linear Programming
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…
Linear Programming Approach to Sustainable Management of ...
African Journals Online (AJOL)
A linear programming (LP) model was used to prescribe timber harvest in the management of even-aged Gmelina arborea plantations in Omo Forest Reserve, Southwestern, Nigeria. The plantations now being managed for timber production are to be exploited within fifteen years based on a 5-year harvesting period.
A direct heuristic algorithm for linear programming
Indian Academy of Sciences (India)
The simplex method [6, 23] ± an exponential time (non-polynomial time) algorithm ± or its variation has been used and is being used to solve almost any linear programming problem (LPP) for the last four decades. In 1979, Khachiyan proposed the ellipsoid method ± the first polynomial-time (interior-point) algorithm ± to ...
Spline smoothing of histograms by linear programming
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.
Integrating Linear Programming and Analytical Hierarchical ...
African Journals Online (AJOL)
A comprehensive Linear Programming model established, including 106 variables and 43 ecological-socio-economic constraints. Land capability and suitability evaluation accomplished using ecological factors and Comparative Advantages of the uses and the factors, respectively. Analytical Hierarchical Process followed ...
Menu-Driven Solver Of Linear-Programming Problems
Viterna, L. A.; Ferencz, D.
1992-01-01
Program assists inexperienced user in formulating linear-programming problems. A Linear Program Solver (ALPS) computer program is full-featured LP analysis program. Solves plain linear-programming problems as well as more-complicated mixed-integer and pure-integer programs. Also contains efficient technique for solution of purely binary linear-programming problems. Written entirely in IBM's APL2/PC software, Version 1.01. Packed program contains licensed material, property of IBM (copyright 1988, all rights reserved).
A Decision Support System for Solving Linear Programming Problems
Nikolaos Ploskas; Nikolaos Samaras; Jason Papathanasiou
2014-01-01
Linear programming algorithms have been widely used in Decision Support Systems. These systems have incorporated linear programming algorithms for the solution of the given problems. Yet, the special structure of each linear problem may take advantage of different linear programming algorithms or different techniques used in these algorithms. This paper proposes a web-based DSS that assists decision makers in the solution of linear programming problems with a variety of linear programming alg...
Updating Linear Schedules with Lowest Cost: a Linear Programming Model
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.
Joint shape segmentation with linear programming
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.
Controller design approach based on linear programming.
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.
Fuzzy linear programming approach for solving transportation ...
Indian Academy of Sciences (India)
ALI EBRAHIMNEJAD
DEFINITION 2.3 ([28]). Let ˜AL ∈ FT N (wL) and ˜AU ∈ FT N (wU ). A level (wL, wU )- interval-valued trapezoidal fuzzy number ˜˜A, denoted by ˜˜A = [. ˜AL, ˜AU. ] = 〈. (aL ...... Appl. Math. Sci. 4(2): 79–90. [14] Kumar A and Kaur A 2010 Application of linear program- ming for solving fuzzy transportation problems. J. Appl. Math.
The NASA MLA program. [Multispectral Linear Array
Ando, K. J.
1983-01-01
The NASA Multispectral Linear Array (MLA) program is structured to provide for the evolutionary development of advanced sensor concepts, technologies, and scientific basis for future remote sensing missions. Program elements include the development of multispectral visible and shortwave infrared (SWIR) detector arrays, optics and on-board signal processing technologies, sensor design studies, and supporting research. The research consists of advanced airborne sensor development with data acquisitions, field measurements, and supporting science studies. At the present time, two instrument concepts, including an imaging spectrometer, are in development as payloads for a series of Shuttle remote sensing research flights beginning as early as 1987. Progressively more advanced capability instruments suitable for extended duration Shuttle, free flyer, and space platform missions in the 1990's are also being studied.
Robust Control Design via Linear Programming
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.
Stochastic linear programming models, theory, and computation
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...
User's manual for LINEAR, a FORTRAN program to derive linear aircraft models
Duke, Eugene L.; Patterson, Brian P.; Antoniewicz, Robert F.
1987-01-01
This report documents a FORTRAN program that provides a powerful and flexible tool for the linearization of aircraft models. The program LINEAR numerically determines a linear system model using nonlinear equations of motion and a user-supplied nonlinear aerodynamic model. The system model determined by LINEAR consists of matrices for both state and observation equations. The program has been designed to allow easy selection and definition of the state, control, and observation variables to be used in a particular model.
Formulated linear programming problems from game theory and its ...
African Journals Online (AJOL)
... using the primal and symmetric dual linear programming problem and its numerical illustration of the super linear programming problem using TORA package. Keywords: Game theory, linear programming, zero sum game, TORA package, computer. International Journal of Natural and Applied Sciences, 6(4): 413 - 422, ...
Tunjo Perić; Zoran Babić; Maid Omerović
2017-01-01
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 va...
User's manual for interactive LINEAR: A FORTRAN program to derive linear aircraft models
Antoniewicz, Robert F.; Duke, Eugene L.; Patterson, Brian P.
1988-01-01
An interactive FORTRAN program that provides the user with a powerful and flexible tool for the linearization of aircraft aerodynamic models is documented in this report. The program LINEAR numerically determines a linear system model using nonlinear equations of motion and a user-supplied linear or nonlinear aerodynamic model. The nonlinear equations of motion used are six-degree-of-freedom equations with stationary atmosphere and flat, nonrotating earth assumptions. The system model determined by LINEAR consists of matrices for both the state and observation equations. The program has been designed to allow easy selection and definition of the state, control, and observation variables to be used in a particular model.
DEFF Research Database (Denmark)
Ommen, Torben Schmidt; Markussen, Wiebke Brix; Elmegaard, Brian
2014-01-01
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...
Induction of Linear Temporal Logic Programs
Kolter, Robert
2017-01-01
We propose a framework for the synthesis of temporal logic programs which are formulated in a simple temporal logic programming language from both positive and negative examples. First we will prove that results from the theory of first order inductive logic programming carry over to the domain of temporal logic. After this we will show how programs formulated in the presented language can be generalized or specialized in order to satisfy the specification induced by the sets of examples.
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 ...
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.
Evaluating fuzzy inequalities and solving fully fuzzified linear fractional programs
Directory of Open Access Journals (Sweden)
Stanojević B.
2012-01-01
Full Text Available In our earlier articles, we proposed two methods for solving the fully fuzzified linear fractional programming (FFLFP problems. In this paper, we introduce a different approach of evaluating fuzzy inequalities between two triangular fuzzy numbers and solving FFLFP problems. First, using the Charnes-Cooper method, we transform the linear fractional programming problem into a linear one. Second, the problem of maximizing a function with triangular fuzzy value is transformed into a problem of deterministic multiple objective linear programming. Illustrative numerical examples are given to clarify the developed theory and the proposed algorithm.
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 ...
A Sawmill Manager Adapts To Change With Linear Programming
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.
Analytic central path, sensitivity analysis and parametric linear programming
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
Comparison of open-source linear programming solvers.
Energy Technology Data Exchange (ETDEWEB)
Gearhart, Jared Lee; Adair, Kristin Lynn; Durfee, Justin David.; Jones, Katherine A.; Martin, Nathaniel; Detry, Richard Joseph
2013-10-01
When developing linear programming models, issues such as budget limitations, customer requirements, or licensing may preclude the use of commercial linear programming solvers. In such cases, one option is to use an open-source linear programming solver. A survey of linear programming tools was conducted to identify potential open-source solvers. From this survey, four open-source solvers were tested using a collection of linear programming test problems and the results were compared to IBM ILOG CPLEX Optimizer (CPLEX) [1], an industry standard. The solvers considered were: COIN-OR Linear Programming (CLP) [2], [3], GNU Linear Programming Kit (GLPK) [4], lp_solve [5] and Modular In-core Nonlinear Optimization System (MINOS) [6]. As no open-source solver outperforms CPLEX, this study demonstrates the power of commercial linear programming software. CLP was found to be the top performing open-source solver considered in terms of capability and speed. GLPK also performed well but cannot match the speed of CLP or CPLEX. lp_solve and MINOS were considerably slower and encountered issues when solving several test problems.
Fuzzy variable linear programming with fuzzy technical coefficients
Directory of Open Access Journals (Sweden)
Sanwar Uddin Ahmad
2012-11-01
Full Text Available Normal 0 false false false EN-US X-NONE X-NONE Fuzzy linear programming is an application of fuzzy set theory in linear decision making problems and most of these problems are related to linear programming with fuzzy variables. In this paper an approximate but convenient method for solving these problems with fuzzy non-negative technical coefficient and without using the ranking functions, is proposed. With the help of numerical examples, the method is illustrated.
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
Linear System of Equations, Matrix Inversion, and Linear Programming Using MS Excel
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…
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.
Generalized Transformation Techniques for Multi-Choice Linear Programming Problems
Directory of Open Access Journals (Sweden)
Srikumar ACHARYA
2013-01-01
Full Text Available The multi-choice programming allows the decision maker to consider multiple number of resources for each constraint or goal. Multi-choice linear programming problem can not be solved directly using the traditional linear programming technique. However, to deal with the multi-choice parameters, multiplicative terms of binary variables may be used in the transformed mathematical model. Recently, Biswal and Acharya (2009 have proposed a methodology to transform the multi-choice linear programming problem to an equivalent mathematical programming model, which can accommodate a maximum of eight goals in righthand side of any constraint. In this paper we present two models as generalized transformation of the multi-choice linear programming problem. Using any one of the transformation techniques a decision maker can handle a parameter with nite number of choices. Binary variables are introduced to formulate a non-linear mixed integer programming model. Using a non-linear programming software optimal solution of the proposed model can be obtained. Finally, a numerical example is presented to illustrate the transformation technique and the solution procedure.
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 s...... problems are solved by a Newton-type algorithm. Preliminary numerical results indicate that the new algorithm is promising.......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...
Piecewise linear actions and Zimmer's program
Ye, Shengkui
2013-01-01
We consider Zimmer's program of lattice actions on surfaces by PL homomorphisms. It is proved that when the surface is not the torus or Klein bottle the action of any finite-index subgroup of SL(n,Z), n>4, (more generally for any 2-big lattice), factors through a finite group action. The proof is based on an establishment of a PL version of Reeb-Thurston's stability.
Schultes, Marie Therese; Stefanek, Elisabeth; van de Schoot, Rens|info:eu-repo/dai/nl/304833207; 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
Large-scale linear programs in planning and prediction.
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 Programming and Its Application to Pattern Recognition Problems
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.
Linear programming with positive semi-definite matrices
Directory of Open Access Journals (Sweden)
J. B. Lasserre
1996-01-01
Full Text Available We consider the general linear programming problem over the cone of positive semi-definite matrices. We first provide a simple sufficient condition for existence of optimal solutions and absence of a duality gap without requiring existence of a strictly feasible solution. We then simply characterize the analogues of the standard concepts of linear programming, i.e., extreme points, basis, reduced cost, degeneracy, pivoting step as well as a Simplex-like algorithm.
EZLP: An Interactive Computer Program for Solving Linear Programming Problems. Final Report.
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,…
0-1 Integer Linear Programming with a Linear Number of Constraints
Impagliazzo, R; Lovett, S; Paturi, R.; Schneider, S.
2017-01-01
We give an exact algorithm for the 0-1 Integer Linear Programming problem with a linear number of constraints that improves over exhaustive search by an exponential factor. Specifically, our algorithm runs in time $2^{(1-\\text{poly}(1/c))n}$ where n is the number of variables and cn is the number of constraints. The key idea for the algorithm is a reduction to the Vector Domination problem and a new algorithm for that subproblem.
Linear Programming for Vocational Education Planning. Interim Report.
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…
Planning Student Flow with Linear Programming: A Tunisian Case Study.
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…
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
A Fuzzy Linear Programming Approach for Aggregate Production Planning
DEFF Research Database (Denmark)
Iris, Cagatay; Cevikcan, Emre
2014-01-01
and inventory costs, but also increase the level of service available to the customers. When maintaining APP, some of cost and demand parameters cannot be frequently determined as crisp values. Fuzzy logic is utilized in many engineering applications so as to handle imprecise data. This chapter provides...... 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...
An efficient linear programming method for Optimal Transportation
Oberman, Adam M.; Ruan, Yuanlong
2015-01-01
An efficient method for computing solutions to the Optimal Transportation (OT) problem with a wide class of cost functions is presented. The standard linear programming (LP) discretization of the continuous problem becomes intractible for moderate grid sizes. A grid refinement method results in a linear cost algorithm. Weak convergence of solutions is stablished. Barycentric projection of transference plans is used to improve the accuracy of solutions. The method is applied to more general pr...
Robust Sensitivity Analysis of the Optimal Value of Linear Programming
Xu, Guanglin; Burer, Samuel
2015-01-01
We propose a framework for sensitivity analysis of linear programs (LPs) in minimization form, allowing for simultaneous perturbations in the objective coefficients and right-hand sides, where the perturbations are modeled in a compact, convex uncertainty set. This framework unifies and extends multiple approaches for LP sensitivity analysis in the literature and has close ties to worst-case linear optimization and two-stage adaptive optimization. We define the minimum (best-case) and maximum...
Using linear programming to analyze and optimize stochastic flow lines
DEFF Research Database (Denmark)
Helber, Stefan; Schimmelpfeng, Katja; Stolletz, Raik
2011-01-01
, to determine a production rate estimate. As our methodology is purely numerical, it offers the full modeling flexibility of stochastic simulation with respect to the probability distribution of processing times. However, unlike discrete-event simulation models, it also offers the optimization power of linear......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....
LTP - A Tutorial Program for Analysis of Linear Two - Ports
Directory of Open Access Journals (Sweden)
J. Valsa
1993-12-01
Full Text Available The paper describes basic possibilities offered by the program LTP (Linear Two-Ports in teaching electrial networks theory. At the same time the most important algorithms used in the program are briefly described. The program LTP analyses immittance and transfer functions of two-ports in the domain of complex variable p, in the frequency domain and in the time domain. The results can be obtained in symbolic, semisymbolic and numerical form (with optional graphical representation of the numerical results. The program is user friendly and can be used easily by anyone.
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 combination reading program for capture gamma rays
Tanner, Allan B.
1971-01-01
This program computes a weighting function, Qj, which gives a scalar output value of unity when applied to the spectrum of a desired element and a minimum value (considering statistics) when applied to spectra of materials not containing the desired element. Intermediate values are obtained for materials containing the desired element, in proportion to the amount of the element they contain. The program is written in the BASIC language in a format specific to the Hewlett-Packard 2000A Time-Sharing System, and is an adaptation of an earlier program for linear combination reading for X-ray fluorescence analysis (Tanner and Brinkerhoff, 1971). Following the program is a sample run from a study of the application of the linear combination technique to capture-gamma-ray analysis for calcium (report in preparation).
Achievement test construction using 0-1 linear programming
Adema, J.J.; Adema, Jos J.; Boekkooi-Timminga, Ellen; van der Linden, Willem J.
1991-01-01
In educational testing the work of professional test agencies has shown a trend towards item banking. Achievement test construction is viewed as selecting items from a test item bank such that certain specifications are met. As the number of possible tests is large and practice usually imposes various constraints on the selection process, a mathematical programming approach is obvious. In this paper it is shown how to formulate achievement test construction as a 0¿1 linear programming problem...
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...
175 Years of Linear Programming-Pivots in Column Space
Indian Academy of Sciences (India)
Home; Journals; Resonance – Journal of Science Education; Volume 4; Issue 1. 175 Years of Linear Programming - Pivots in Column Space. Vijay Chandru M R Rao. Series Article Volume 4 Issue 1 January 1999 pp 8-22. Fulltext. Click here to view fulltext PDF. Permanent link:
Game Theory and its Relationship with Linear Programming Models ...
African Journals Online (AJOL)
Game theory, a branch of operations research, has been successfully applied to solve various categories of problems arising from human decisions making characterized by the complexity of situations and the limits of individual processing abilities. This paper shows that game theory and linear programming problem are ...
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:
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 ...
A mixed integer linear program for an integrated fishery | Hasan ...
African Journals Online (AJOL)
We develop a mixed integer linear programming (MILP) model to co-ordinate trawler scheduling, fishing, processing, 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 ...
A Partitioning and Bounded Variable Algorithm for Linear Programming
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…
Interior-Point Methods for Linear Programming: A Review
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…
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.
Formulated linear programming problems from game theory and its ...
African Journals Online (AJOL)
A good theoretical background is needed in interpreting optimal mixed strategies as proportion of time that a given player could utilize each of his/her pure strategies. It is also needed in interpreting how a two-person zero sum game could be reduced to a special linear programming problem, using the primal and symmetric ...
LCPT: a program for finding linear canonical transformations. [In MACSYMA
Energy Technology Data Exchange (ETDEWEB)
Char, B.W.; McNamara, B.
1979-05-21
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.
Adaptation-II of the surrogate methods for linear programming ...
African Journals Online (AJOL)
Adaptation-II of the surrogate methods for linear programming problems. SO Oko. Abstract. No Abstract. Global Journal of Mathematical Sciences Vol. 5(1) 2006: 63-71. Full Text: EMAIL FULL TEXT EMAIL FULL TEXT · DOWNLOAD FULL TEXT DOWNLOAD FULL TEXT · http://dx.doi.org/10.4314/gjmas.v5i1.21381.
Linear program differentiation for single-channel speech separation
DEFF Research Database (Denmark)
Pearlmutter, Barak A.; Olsson, Rasmus Kongsgaard
2006-01-01
. 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...
Linear decomposition approach for a class of nonconvex programming problems.
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.
Train repathing in emergencies based on fuzzy linear programming.
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.
Boolean Variables in Economic Models Solved by Linear Programming
Directory of Open Access Journals (Sweden)
Lixandroiu D.
2014-12-01
Full Text Available The article analyses the use of logical variables in economic models solved by linear programming. Focus is given to the presentation of the way logical constraints are obtained and of the definition rules based on predicate logic. Emphasis is also put on the possibility to use logical variables in constructing a linear objective function on intervals. Such functions are encountered when costs or unitary receipts are different on disjunct intervals of production volumes achieved or sold. Other uses of Boolean variables are connected to constraint systems with conditions and the case of a variable which takes values from a finite set of integers.
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.
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.
MAGDM linear-programming models with distinct uncertain preference structures.
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.
PENGEMBANGAN BAHAN AJAR PROGRAM LINEAR BERBASIS KONTEKSTUAL DAN ICT
Directory of Open Access Journals (Sweden)
Swaditya Rizki
2017-01-01
Full Text Available This study is a research and development (R & D. The model used in this research is to adapt the development of the 4D model (Define, Design, Develop, Disseminate developed by Thiagarajan. This study aims to generate the teaching materials based contextual and ICT are good at program linear and to determine the effectiveness of teaching materials based contextual and ICT at program linear on learning outcomes. Data collection instruments used in this study in the form of questionnaires, interviews, sheet validation, and matter. Data analysis techniques used in this research and development is a qualitative descriptive analysis technique to calculate the average, while for influence before and after treatment that uses the analysis of paired sample t-test. The conclusions obtained from the development are teaching materials based contextual and ICT are very valid and practical for use in the learning process. From the test results, it can be concluded that there is a very significant influence mathematics teaching materials based contextual and ICT on student learning outcomes. So, teaching materials based contextual and ICT is very effective for use in learning the material Program Linear
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…
A LINEAR-PROGRAMMING ALGORITHM FOR INVARIANT POLYHEDRAL-SETS OF DISCRETE-TIME LINEAR-SYSTEMS
TENDAM, AA; NIEUWENHUIS, JW
1995-01-01
In this paper we formulate necessary and sufficient conditions for an arbitrary polyhedral set to be a positively invariant set of a linear discrete-time system. Polyhedral cones and linear subspaces are included in the analysis. A linear programming algorithm is presented that enables practical
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...
Optimal traffic control in highway transportation networks using linear programming
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.
A recurrent neural network for solving bilevel linear programming problem.
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.
A linear programming approach for optimal contrast-tone mapping.
Wu, Xiaolin
2011-05-01
This paper proposes a novel algorithmic approach of image enhancement via optimal contrast-tone mapping. In a fundamental departure from the current practice of histogram equalization for contrast enhancement, the proposed approach maximizes expected contrast gain subject to an upper limit on tone distortion and optionally to other constraints that suppress artifacts. The underlying contrast-tone optimization problem can be solved efficiently by linear programming. This new constrained optimization approach for image enhancement is general, and the user can add and fine tune the constraints to achieve desired visual effects. Experimental results demonstrate clearly superior performance of the new approach over histogram equalization and its variants.
Multispectral Linear Array (MLA) science and technology program
Barnes, W. L.
1982-01-01
A Goddard Space Flight Center program of science studies and technology development to provide the basis for future earth observation sensors employing multispectral linear array (MLA) technology is described. Establishment of MLA performance parameters and performance modeling make up the primary science activities. Critical technologies being developed include: short-wave infrared (SWIR) detector arrays, visible/and near infrared detector arrays, and passive cryogenic coolers. Supporting activities include: test and field instrument development, focal plane research and assessment laboratory, system simulation laboratory, calibration sources and techniques, optics, and thermal infrared arrays.
A new algorithm for solving linear programming problems
Directory of Open Access Journals (Sweden)
Andrés Leonardo Ramírez Leal
2012-08-01
Full Text Available Linear programming (LP is one of the most widely-applied techniques in operations research. Many methods have been developed and several others are being proposed for solving LP problems, including the famous simplex method and interior point algorithms. This study was aimed at introducing a new method for solving LP problems. The proposed algorithm starts from an interior point and then carries out orthogonal projections using parametric straight lines to move between the interior and polyhedron frontier defining the feasible region until reaching the extreme optimal point.
Hard disk drive seeking profile optimisation via linear programming
Zhang, Jun; Wang, Xudong
2011-04-01
In this article we develop an approach to design track-seeking controller for hard disk drive. We convert the current multi-sine seek approach to an equivalent linear programming problem that can be solved efficiently and accurately. We demonstrate the efficacy of this approach by numerical case studies that are otherwise infeasible in the current approach. We further derive the time optimal track seeking as a three-piece constant control. Our approach can also be extended to deal with other sophisticated requirements on smoothness, jerk and resonance.
Polymorphic Uncertain Linear Programming for Generalized Production Planning Problems
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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.
Analisis Optimalisasi Produksi dengan Linear Programming Melalui Metode Simpleks
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Teguh Sriwidadi
2013-11-01
Full Text Available PD Utama Jaya Plasindo is a trading company which processes plastic resin. In the daily process, the company has many problems or constraints in production planning. Uncertainty demand of goods fluctuation has effect on shortage or surplus production. Other problems are raw materials, machine work hour, labour work hour, and the demand of the products. Simplex Method of Linear Programming purposes to maximize profit in linear function, Profit = 37 A + 46 B + 38 C + 46 D and linear functions of the seven constraints, Raw materials = 7 A + 5,8 B + 8,6 C + 7,6 D ≤ 180.000 grams, Machine Work Hour = 2,5 A + 3 B + 2 C + 2,5 D ≤86.400 seconds, Labor Work Hour = 5 A + 5 B + 5 C + 5 D ≤ 115.200 seconds, Demands of GRX 25 = A ≤2400 pcs, demand of GTW 25 = B ≤ 7200 pcs, demand of GTX 25 = C ≤ 3000 pcs, and demand of GTX 25 M = D ≤ 6600 pcs. The total profit earned by PD Utama Jaya Plasindo from plastic buckle products is Rp 837,000.00 per day and for 20 efective days is Rp 16,752,000.00 with the assumption of profit is in accordance with fixed objective and constraint functions.
How to Use Linear Programming for Information System Performances Optimization
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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.
Assembling networks of microbial genomes using linear programming.
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.
AN APPLICATION FOR EFFICIENT TELECOMMUNICATION NETWORKS PROVISIONING USING LINEAR PROGRAMMING
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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.
Sakawa, M.; Kato, K.
2009-01-01
This paper considers stochastic two-level linear programming problems. Using the concept of chance constraints and probability maximization, original problems are transformed into deterministic ones. An interactive fuzzy programming method is presented for deriving a satisfactory solution efficiently with considerations of overall satisfactory balance.
Aether: Leveraging Linear Programming For Optimal Cloud Computing In Genomics.
Luber, Jacob M; Tierney, Braden T; Cofer, Evan M; Patel, Chirag J; Kostic, Aleksandar D
2017-12-08
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 (LP) 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 and aleksandar.kostic@joslin.harvard.edu. Supplementary data are available at Bioinformatics online.
Linear programming phase unwrapping for dual-wavelength digital holography.
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.
An integer linear programming for a comprehensive reverse supply chain
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Hoda Mahmoudi
2014-12-01
Full Text Available Reverse supply chain is a cycle of recovery for the products and materials used by the customers but can be returned to the chain performing some operations. Due to significance of reverse supply chain in the content of environmental and economical aspects, we formulate a mathematical model of reverse multi-layer multi-product supply chain for minimizing the total costs including returning, disassembly, processing, recycling, remanufacturing, and distribution centers. The presented model is an integer linear programming model being solved using Lingo 9 software. Numerical experiments are conducted to gain insight into the proposed model. The solutions provide a decision aid stream strengthening the concept of reverse supply network design and analysis for profit-making organization.
CONTRIBUTION OF A LINEAR PROGRAMMING VBA MODULE TO STUDENTS PEFORMANCE
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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.
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.
Interactive Multiobjective Fuzzy Random Linear Programming through Fractile Criteria
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Hitoshi Yano
2012-01-01
Full Text Available We propose an interactive fuzzy decision making method for multiobjective fuzzy random linear programming problems through fractile criteria optimization. In the proposed method, it is assumed that the decision maker has fuzzy goals for not only objective functions but also permissible probability levels in a fractile optimization model, and such fuzzy goals are quantified by eliciting the corresponding membership functions. Using the fuzzy decision, such two kinds of membership functions are integrated. In the integrated membership space, the satisfactory solution is obtained from among an extended Pareto optimal solution set through the interaction with the decision maker. An illustrative numerical example is provided to demonstrate the feasibility and efficiency of the proposed method.
Analyzing Nonblocking Switching Networks using Linear Programming (Duality)
Ngo, Hung Q; Le, Anh N; Nguyen, Thanh-Nhan
2012-01-01
The main task in analyzing a switching network design (including circuit-, multirate-, and photonic-switching) is to determine the minimum number of some switching components so that the design is non-blocking in some sense (e.g., strict- or wide-sense). We show that, in many cases, this task can be accomplished with a simple two-step strategy: (1) formulate a linear program whose optimum value is a bound for the minimum number we are seeking, and (2) specify a solution to the dual program, whose objective value by weak duality immediately yields a sufficient condition for the design to be non-blocking. We illustrate this technique through a variety of examples, ranging from circuit to multirate to photonic switching, from unicast to $f$-cast and multicast, and from strict- to wide-sense non-blocking. The switching architectures in the examples are of Clos-type and Banyan-type, which are the two most popular architectural choices for designing non-blocking switching networks. To prove the result in the multir...
Split diversity in constrained conservation prioritization using integer linear programming.
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.
A linear programming approach for placement of applicants to academic programs
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 ...
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...
Near-Regular Structure Discovery Using Linear Programming
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.
Fitting boxes to Manhattan scenes using linear integer programming
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.
Learning oncogenetic networks by reducing to mixed integer linear programming.
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.
Dense image registration through MRFs and efficient linear programming.
Glocker, Ben; Komodakis, Nikos; Tziritas, Georgios; Navab, Nassir; Paragios, Nikos
2008-12-01
In this paper, we introduce a novel and efficient approach to dense image registration, which does not require a derivative of the employed cost function. In such a context, the registration problem is formulated using a discrete Markov random field objective function. First, towards dimensionality reduction on the variables we assume that the dense deformation field can be expressed using a small number of control points (registration grid) and an interpolation strategy. Then, the registration cost is expressed using a discrete sum over image costs (using an arbitrary similarity measure) projected on the control points, and a smoothness term that penalizes local deviations on the deformation field according to a neighborhood system on the grid. Towards a discrete approach, the search space is quantized resulting in a fully discrete model. In order to account for large deformations and produce results on a high resolution level, a multi-scale incremental approach is considered where the optimal solution is iteratively updated. This is done through successive morphings of the source towards the target image. Efficient linear programming using the primal dual principles is considered to recover the lowest potential of the cost function. Very promising results using synthetic data with known deformations and real data demonstrate the potentials of our approach.
Maximum likelihood pedigree reconstruction using integer linear programming.
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.
Periodic inventory system in cafeteria using linear programming
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.
Optimizing Biorefinery Design and Operations via Linear Programming Models
Energy Technology Data Exchange (ETDEWEB)
Talmadge, Michael; Batan, Liaw; Lamers, Patrick; Hartley, Damon; Biddy, Mary; Tao, Ling; Tan, Eric
2017-03-28
The ability to assess and optimize economics of biomass resource utilization for the production of fuels, chemicals and power is essential for the ultimate success of a bioenergy industry. The team of authors, consisting of members from the National Renewable Energy Laboratory (NREL) and the Idaho National Laboratory (INL), has developed simple biorefinery linear programming (LP) models to enable the optimization of theoretical or existing biorefineries. The goal of this analysis is to demonstrate how such models can benefit the developing biorefining industry. It focuses on a theoretical multi-pathway, thermochemical biorefinery configuration and demonstrates how the biorefinery can use LP models for operations planning and optimization in comparable ways to the petroleum refining industry. Using LP modeling tools developed under U.S. Department of Energy's Bioenergy Technologies Office (DOE-BETO) funded efforts, the authors investigate optimization challenges for the theoretical biorefineries such as (1) optimal feedstock slate based on available biomass and prices, (2) breakeven price analysis for available feedstocks, (3) impact analysis for changes in feedstock costs and product prices, (4) optimal biorefinery operations during unit shutdowns / turnarounds, and (5) incentives for increased processing capacity. These biorefinery examples are comparable to crude oil purchasing and operational optimization studies that petroleum refiners perform routinely using LPs and other optimization models. It is important to note that the analyses presented in this article are strictly theoretical and they are not based on current energy market prices. The pricing structure assigned for this demonstrative analysis is consistent with $4 per gallon gasoline, which clearly assumes an economic environment that would favor the construction and operation of biorefineries. The analysis approach and examples provide valuable insights into the usefulness of analysis tools for
Very Low-Cost Nutritious Diet Plans Designed by Linear Programming.
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)
Development and validation of a general purpose linearization program for rigid aircraft models
Duke, E. L.; Antoniewicz, R. F.
1985-01-01
This paper discusses a FORTRAN program that provides the user with a powerful and flexible tool for the linearization of aircraft models. The program LINEAR numerically determines a linear systems model using nonlinear equations of motion and a user-supplied, nonlinear aerodynamic model. The system model determined by LINEAR consists of matrices for both the state and observation equations. The program has been designed to allow easy selection and definition of the state, control, and observation variables to be used in a particular model. Also, included in the report is a comparison of linear and nonlinear models for a high-performance aircraft.
Kusumawati, Rosita; Subekti, Retno
2017-04-01
Fuzzy bi-objective linear programming (FBOLP) model is bi-objective linear programming model in fuzzy number set where the coefficients of the equations are fuzzy number. This model is proposed to solve portfolio selection problem which generate an asset portfolio with the lowest risk and the highest expected return. FBOLP model with normal fuzzy numbers for risk and expected return of stocks is transformed into linear programming (LP) model using magnitude ranking function.
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.
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.
A two-phase linear programming approach for redundancy allocation problems
Directory of Open Access Journals (Sweden)
Hsieh Yi-Chih
2002-01-01
Full Text Available Provision of redundant components in parallel is an efficient way to increase the system reliability, however, the weight, volume and cost of the system will increase simultaneously. This paper proposes a new two-phase linear programming approach for solving the nonlinear redundancy allocation problems subject to multiple linear constraints. The first phase is used to approximately allocate the resource by using a general linear programming, while the second phase is used to re-allocate the slacks of resource by using a 0-1 integer linear programming. Numerical results demonstrate the effectiveness and efficiency of the proposed approach.
The essential multiobjectivity of linear programming | Stewart | ORiON
African Journals Online (AJOL)
It is argued that any non-trivial real world problems involve multiple objectives. The simplistic approach of combining objectives in linear form can generate highly misleading and biased results, and is poor operational research practice. Such biases are illustrated by means of a simple example, and it is demonstrated that ...
Fundamental solution of the problem of linear programming and method of its determination
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.
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)
Gorissen, B.L.; Blanc, J.P.C.; den Hertog, D.; Ben-Tal, A.
We propose a new way to derive tractable robust counterparts of a linear program based on the duality between the robust (“pessimistic”) primal problem and its “optimistic” dual. First we obtain a new convex reformulation of the dual problem of a robust linear program, and then show how to construct
Sensitivity analysis of linear programming problem through a recurrent neural network
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.
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.
Diet models with linear goal programming: impact of achievement functions
Gerdessen, J.C.; Vries, de J.H.M.
2015-01-01
Background/Objectives: Diet models based on goal programming (GP) are valuable tools in designing diets that comply with nutritional, palatability and cost constraints. Results derived from GP models are usually very sensitive to the type of achievement function that is chosen. This paper aims to
Potential function methods for approximately solving linear programming problems theory and practice
Bienstock, Daniel
2002-01-01
Potential Function Methods For Approximately Solving Linear Programming Problems breaks new ground in linear programming theory. The book draws on the research developments in three broad areas: linear and integer programming, numerical analysis, and the computational architectures which enable speedy, high-level algorithm design. During the last ten years, a new body of research within the field of optimization research has emerged, which seeks to develop good approximation algorithms for classes of linear programming problems. This work both has roots in fundamental areas of mathematical programming and is also framed in the context of the modern theory of algorithms. The result of this work, in which Daniel Bienstock has been very much involved, has been a family of algorithms with solid theoretical foundations and with growing experimental success. This book will examine these algorithms, starting with some of the very earliest examples, and through the latest theoretical and computational developments.
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.
A linear programming approach for placement of applicants to academic programs.
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.
An introduction to fuzzy linear programming problems theory, methods and applications
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.
Arc-Search Infeasible Interior-Point Algorithm for Linear Programming
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...
Multi-Objective Fuzzy Linear Programming In Agricultural Production Planning
Directory of Open Access Journals (Sweden)
H.M.I.U. Herath
2015-08-01
Full Text Available Abstract Modern agriculture is characterized by a series of conflicting optimization criteria that obstruct the decision-making process in the planning of agricultural production. Such criteria are usually net profit total cost total production etc. At the same time the decision making process in the agricultural production planning is often conducted with data that accidentally occur in nature or that are fuzzy not deterministic. Such data are the yields of various crops the prices of products and raw materials demand for the product the available quantities of production factors such as water labor etc. In this paper a fuzzy multi-criteria mathematical programming model is presented. This model is applied in a region of 10 districts in Sri Lanka where paddy is cultivated under irrigated and rain fed water in the two main seasons called Yala and Maha and the optimal production plan is achieved. This study was undertaken to find out the optimal allocation of land for paddy to get a better yield while satisfying the two conflicting objectives profit maximizing and cost minimizing subjected to the utilizing of water constraint and the demand constraint. Only the availability of land constraint is considered as a crisp in nature while objectives and other constraints are treated as fuzzy. It is observed that the MOFLP is an effective method to handle more than a single objective occurs in an uncertain vague environment.
Diet models with linear goal programming: impact of achievement functions.
Gerdessen, J C; de Vries, J H M
2015-11-01
Diet models based on goal programming (GP) are valuable tools in designing diets that comply with nutritional, palatability and cost constraints. Results derived from GP models are usually very sensitive to the type of achievement function that is chosen.This paper aims to provide a methodological insight into several achievement functions. It describes the extended GP (EGP) achievement function, which enables the decision maker to use either a MinSum achievement function (which minimizes the sum of the unwanted deviations) or a MinMax achievement function (which minimizes the largest unwanted deviation), or a compromise between both. An additional advantage of EGP models is that from one set of data and weights multiple solutions can be obtained. We use small numerical examples to illustrate the 'mechanics' of achievement functions. Then, the EGP achievement function is demonstrated on a diet problem with 144 foods, 19 nutrients and several types of palatability constraints, in which the nutritional constraints are modeled with fuzzy sets. Choice of achievement function affects the results of diet models. MinSum achievement functions can give rise to solutions that are sensitive to weight changes, and that pile all unwanted deviations on a limited number of nutritional constraints. MinMax achievement functions spread the unwanted deviations as evenly as possible, but may create many (small) deviations. EGP comprises both types of achievement functions, as well as compromises between them. It can thus, from one data set, find a range of solutions with various properties.
FSILP: fuzzy-stochastic-interval linear programming for supporting municipal solid waste management.
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.
Linearized Programming of Memristors for Artificial Neuro-Sensor Signal Processing.
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.
Linear genetic programming for time-series modelling of daily flow rate
Indian Academy of Sciences (India)
In this study linear genetic programming (LGP), which is a variant of Genetic Programming, and two versions of Neural Networks (NNs) are used in predicting time-series of daily flow rates at a station on Schuylkill River at Berne, PA, USA. Daily flow rate at present is being predicted based on different time-series scenarios.
Micosoft Excel Sensitivity Analysis for Linear and Stochastic Program Feed Formulation
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...
DEFF Research Database (Denmark)
Cetin, Bilge Kartal; Prasad, Neeli R.; Prasad, Ramjee
2011-01-01
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...... of the maximum lifetime routing problem that considers the operation modes of the node. Solution of the linear programming gives the upper analytical bound for the network lifetime. In order to illustrate teh application of the optimization model, we solved teh problem for different parameter settings...
Object matching using a locally affine invariant and linear programming techniques.
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.
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.
A novel recurrent neural network with finite-time convergence for linear programming.
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.
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
The Concept of Recoverable Robustness, Linear Programming Recovery, and Railway Applications
Liebchen, Christian; Lübbecke, Marco; Möhring, Rolf; Stiller, Sebastian
We present a new concept for optimization under uncertainty: recoverable robustness. A solution is recovery robust if it can be recovered by limited means in all likely scenarios. Specializing the general concept to linear programming we can show that recoverable robustness combines the flexibility of stochastic programming with the tractability and performances guarantee of the classical robust approach. We exemplify recoverable robustness in delay resistant, periodic and aperiodic timetabling problems, and train platforming.
DEFF Research Database (Denmark)
López, Maria del Pilar Heras; Thomas, Sarah; Kramer, Morten Mejlhede
2017-01-01
Although linear theory is often used to analyse wave energy devices, it is in many cases too simplistic. Many wave energy converters (WECs) exceed the key linear theory assumption of small amplitudes of motion, and require the inclusion of non-linear forces. A common approach is to use a hybrid...... frequency-time domain model based on the Cummins equation with hydro-dynamic inputs coming from linear wave theory (Ref. [1]). Published experimental data is sparse (Ref. [2]) and the suitability for the broad variety of WEC technologies has yet to be proven. This paper focuses on the challenges faced when...
The fastclime Package for Linear Programming and Large-Scale Precision Matrix Estimation in R.
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 L1 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.
Optimizing the herd calving pattern with linear programming and dynamic probabilistic simulation.
Jalvingh, A.W.; Dijkhuizen, A.A.; Arendonk, van J.A.M.
1994-01-01
Until recently, little attention has been paid to the influence of seasonal variation in performance and prices on the optimal calving pattern of a herd. A method was developed to determine the herd calving pattern that is farm-specific and optimal with use of linear programming. The required
Visual, Algebraic and Mixed Strategies in Visually Presented Linear Programming Problems.
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.)…
Nutrient density score of typical Indonesian foods and dietary formulation using linear programming.
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.
Secret Message Decryption: Group Consulting Projects Using Matrices and Linear Programming
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…
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.
Linear Programming Approaches for Power Savings in Software-defined Networks
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
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 (...
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
Linear circuit analysis program for IBM 1620 Monitor 2, 1311/1443 data processing system /CIRCS/
Hatfield, J.
1967-01-01
CIRCS is modification of IBSNAP Circuit Analysis Program, for use on smaller systems. This data processing system retains the basic dc, transient analysis, and FORTRAN 2 formats. It can be used on the IBM 1620/1311 Monitor I Mod 5 system, and solves a linear network containing 15 nodes and 45 branches.
A linear programming model of diet choice of free-living beavers
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,
Aggregation of spatial units in linear programming models to explore land use options.
Hijmans, R.J.; Ittersum, van M.K.
1996-01-01
Consequences of aggregating spatial units in an interactive multiple-goal linear programming (IMGLP) model are analysed for a schematized and an existing IMGLP model (GOAL) exploring land use options for the European Union. A discrimination was made between effects on objective functions for the
An interactive method to solve infeasibility in linear programming test assembling models
Huitzing, HA
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
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…
Snow, L. S.; Kuhn, A. E.
1975-01-01
Previous error analyses conducted by the Guidance and Dynamics Branch of NASA have used the Guidance Analysis Program (GAP) as the trajectory simulation tool. Plans are made to conduct all future error analyses using the Space Vehicle Dynamics Simulation (SVDS) program. A study was conducted to compare the inertial measurement unit (IMU) error simulations of the two programs. Results of the GAP/SVDS comparison are presented and problem areas encountered while attempting to simulate IMU errors, vehicle performance uncertainties and environmental uncertainties using SVDS are defined. An evaluation of the SVDS linear error analysis capability is also included.
Kraft, Kate H.; Shukla, Aseem R.; Canning, Douglas A.
2011-01-01
Hypospadias results from abnormal development of the penis that leaves the urethral meatus proximal to its normal glanular position. Meatal position may be located anywhere along the penile shaft, but more severe forms of hypospadias may have a urethral meatus located at the scrotum or perineum. The spectrum of abnormalities may also include ventral curvature of the penis, a dorsally redundant prepuce, and atrophic corpus spongiosum. Due to the severity of these abnormalities, proximal hypospadias often requires more extensive reconstruction in order to achieve an anatomically and functionally successful result. We review the spectrum of proximal hypospadias etiology, presentation, correction, and possible associated complications. PMID:21516286
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...... is significantly faster than several state-of-the-art IPMs based on sparse linear algebra, and 2) warm-start reduces the average number of iterations by 35-40%....
User's Guide to the Weighted-Multiple-Linear Regression Program (WREG version 1.0)
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.
Linear programming models and methods of matrix games with payoffs of triangular fuzzy numbers
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. .
SLFP: a stochastic linear fractional programming approach for sustainable waste management.
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.
A Two-Phase Support Method for Solving Linear Programs: Numerical Experiments
Directory of Open Access Journals (Sweden)
Mohand Bentobache
2012-01-01
Full Text Available We develop a single artificial variable technique to initialize the primal support method for solving linear programs with bounded variables. We first recall the full artificial basis technique, then we will present the proposed algorithm. In order to study the performances of the suggested algorithm, an implementation under the MATLAB programming language has been developed. Finally, we carry out an experimental study about CPU time and iterations number on a large set of the NETLIB test problems. These test problems are practical linear programs modelling various real-life problems arising from several fields such as oil refinery, audit staff scheduling, airline scheduling, industrial production and allocation, image restoration, multisector economic planning, and data fitting. It has been shown that our approach is competitive with our implementation of the primal simplex method and the primal simplex algorithm implemented in the known open-source LP solver LP_SOLVE.
National Research Council Canada - National Science Library
Lorenzo-Seva, Urbano; Ferrando, Pere J
2011-01-01
We provide an SPSS program that implements currently recommended techniques and recent developments for selecting variables in multiple linear regression analysis via the relative importance of predictors...
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.
LDRD final report on massively-parallel linear programming : the parPCx system.
Energy Technology Data Exchange (ETDEWEB)
Parekh, Ojas (Emory University, Atlanta, GA); Phillips, Cynthia Ann; Boman, Erik Gunnar
2005-02-01
This report summarizes the research and development performed from October 2002 to September 2004 at Sandia National Laboratories under the Laboratory-Directed Research and Development (LDRD) project ''Massively-Parallel Linear Programming''. We developed a linear programming (LP) solver designed to use a large number of processors. LP is the optimization of a linear objective function subject to linear constraints. Companies and universities have expended huge efforts over decades to produce fast, stable serial LP solvers. Previous parallel codes run on shared-memory systems and have little or no distribution of the constraint matrix. We have seen no reports of general LP solver runs on large numbers of processors. Our parallel LP code is based on an efficient serial implementation of Mehrotra's interior-point predictor-corrector algorithm (PCx). The computational core of this algorithm is the assembly and solution of a sparse linear system. We have substantially rewritten the PCx code and based it on Trilinos, the parallel linear algebra library developed at Sandia. Our interior-point method can use either direct or iterative solvers for the linear system. To achieve a good parallel data distribution of the constraint matrix, we use a (pre-release) version of a hypergraph partitioner from the Zoltan partitioning library. We describe the design and implementation of our new LP solver called parPCx and give preliminary computational results. We summarize a number of issues related to efficient parallel solution of LPs with interior-point methods including data distribution, numerical stability, and solving the core linear system using both direct and iterative methods. We describe a number of applications of LP specific to US Department of Energy mission areas and we summarize our efforts to integrate parPCx (and parallel LP solvers in general) into Sandia's massively-parallel integer programming solver PICO (Parallel Interger and
Linear-phase approximation in the triangular facet near-field physical optics computer program
Imbriale, W. A.; Hodges, R. E.
1990-01-01
Analyses of reflector antenna surfaces use a computer program based on a discrete approximation of the radiation integral. The calculation replaces the actual surface with a triangular facet representation; the physical optics current is assumed to be constant over each facet. Described here is a method of calculation using linear-phase approximation of the surface currents of parabolas, ellipses, and shaped subreflectors and compares results with a previous program that used a constant-phase approximation of the triangular facets. The results show that the linear-phase approximation is a significant improvement over the constant-phase approximation, and enables computation of 100 to 1,000 lambda reflectors within a reasonable time on a Cray computer.
DEFF Research Database (Denmark)
Parlesak, A.; Tetens, Inge; Dejgård Jensen, Jørgen
2016-01-01
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...... 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...
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.
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.
Annular precision linear shaped charge flight termination system for the ODES program
Energy Technology Data Exchange (ETDEWEB)
Vigil, M.G.; Marchi, D.L.
1994-06-01
The work for the development of an Annular Precision Linear Shaped Charge (APLSC) Flight Termination System (FTS) for the Operation and Deployment Experiment Simulator (ODES) program is discussed and presented in this report. The Precision Linear Shaped Charge (PLSC) concept was recently developed at Sandia. The APLSC component is designed to produce a copper jet to cut four inch diameter holes in each of two spherical tanks, one containing fuel and the other an oxidizer that are hyperbolic when mixed, to terminate the ODES vehicle flight if necessary. The FTS includes two detonators, six Mild Detonating Fuse (MDF) transfer lines, a detonator block, detonation transfer manifold, and the APLSC component. PLSCs have previously been designed in ring components where the jet penetrating axis is either directly away or toward the center of the ring assembly. Typically, these PLSC components are designed to cut metal cylinders from the outside inward or from the inside outward. The ODES program requires an annular linear shaped charge. The (Linear Shaped Charge Analysis) LESCA code was used to design this 65 grain/foot APLSC and data comparing the analytically predicted to experimental data are presented. Jet penetration data are presented to assess the maximum depth and reproducibility of the penetration. Data are presented for full scale tests, including all FTS components, and conducted with nominal 19 inch diameter, spherical tanks.
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.
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....
A linear programming approach to characterizing norm bounded uncertainty from experimental data
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).
Dancing UAVs: Using linear programming to model movement behavior with safety requirements
Dinh, Hoang Tung; Cruz Torres, Mario Henrique; Holvoet, Tom
2017-01-01
In this paper we present the use of linear programming to systematically create control software for choreographed UAVs. This application requires the control of multiple UAVs where each UAV follows a predefined trajectory while simultaneously maintaining safety properties, such as keeping a safe distance between each other and geofencing. Modeling and incorporating safety requirements into the movement behavior of UAVs is the main motivation of our research. First, we describe an approach wh...
Mixed-Integer Linear Programming Models for Teaching Assistant Assignment and Extensions
Qu, Xiaobo; Yi, Wen; Wang, Tingsong; Wang, Shuaian; Xiao, Lin; Liu, Zhiyuan
2017-01-01
In this paper, we develop mixed-integer linear programming models for assigning the most appropriate teaching assistants to the tutorials in a department. The objective is to maximize the number of tutorials that are taught by the most suitable teaching assistants, accounting for the fact that different teaching assistants have different capabilities and each teaching assistant’s teaching load cannot exceed a maximum value. Moreover, with optimization models, the teaching load allocation, a t...
A new neural network model for solving random interval linear programming problems.
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.
A new one-layer neural network for linear and quadratic programming.
Gao, Xingbao; Liao, Li-Zhi
2010-06-01
In this paper, we present a new neural network for solving linear and quadratic programming problems in real time by introducing some new vectors. The proposed neural network is stable in the sense of Lyapunov and can converge to an exact optimal solution of the original problem when the objective function is convex on the set defined by equality constraints. Compared with existing one-layer neural networks for quadratic programming problems, the proposed neural network has the least neurons and requires weak stability conditions. The validity and transient behavior of the proposed neural network are demonstrated by some simulation results.
Energy Technology Data Exchange (ETDEWEB)
Dantzig, G.B.; Glynn, P.; Infanger, G.
1994-03-01
Planning under uncertainty is a fundamental problem of decision science where solution could advance man`s ability to plan, schedule, design, and control complex situations. Goal is to develop efficient methods for solving an important class of planning problems, namely linear programs whose parameters (coefficients, right hand sides) are not known with certainty. The research concentrated on theoretical tasks of decomposition and importance sampling techniques, implementation, and software development issues and on applications. Research is continuing on use of parallel processors for solving stochastic programs.
APPLYING ROBUST RANKING METHOD IN TWO PHASE FUZZY OPTIMIZATION LINEAR PROGRAMMING PROBLEMS (FOLPP
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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.
The Linear Programming to evaluate the performance of Oral Health in Primary Care.
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.
Calling the lp_solve Linear Program Software from R, S-PLUS and Excel
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Samuel E. Buttrey
2005-05-01
Full Text Available We present a link that allows R, S-PLUS and Excel to call the functions in the lp_solve system. lp_solve is free software (licensed under the GNU Lesser GPL that solves linear and mixed integer linear programs of moderate size (on the order of 10,000 variables and 50,000 constraints. R does not include this ability (though two add-on packages offer linear programs without integer variables, while S-PLUS users need to pay extra for the NuOPT library in order to solve these problems. Our link manages the interface between these statistical packages and lp_solve. Excel has a built-in add-in named Solver that is capable of solving mixed integer programs, but only with fewer than 200 variables. This link allows Excel users to handle substantially larger problems at no extra cost. While our primary concern has been the Windows operating system, the package has been tested on some Unix-type systems as well.
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
IESIP - AN IMPROVED EXPLORATORY SEARCH TECHNIQUE FOR PURE INTEGER LINEAR PROGRAMMING PROBLEMS
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.
Automated design and optimization of flexible booster autopilots via linear programming, volume 1
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.
Directory of Open Access Journals (Sweden)
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.
Wavelet-linear genetic programming: A new approach for modeling monthly streamflow
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.
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.
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
LPmerge: an R package for merging genetic maps by linear programming.
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.
On Implicit Active Constraints in Linear Semi-Infinite Programs with Unbounded Coefficients
Energy Technology Data Exchange (ETDEWEB)
Goberna, M. A., E-mail: mgoberna@ua.es [Alicante University, Dep. of Statistics and Operations Research (Spain); Lancho, G. A., E-mail: lanchoga@mixteco.utm.mx [Universidad Tecnologica de Mixteca, Instituto de Fisica y Matematicas (Mexico); Todorov, M. I., E-mail: maxim.todorov@udlap.mx [UDLA, Dep. of Physics and Mathematics (Mexico); Vera de Serio, V. N., E-mail: vvera@uncu.edu.ar [Universidad Nacional de Cuyo, Facultad de Ciencias Economicas, Instituto de Ciencias Basicas (Argentina)
2011-04-15
The concept of implicit active constraints at a given point provides useful local information about the solution set of linear semi-infinite systems and about the optimal set in linear semi-infinite programming provided the set of gradient vectors of the constraints is bounded, commonly under the additional assumption that there exists some strong Slater point. This paper shows that the mentioned global boundedness condition can be replaced by a weaker local condition (LUB) based on locally active constraints (active in a ball of small radius whose center is some nominal point), providing geometric information about the solution set and Karush-Kuhn-Tucker type conditions for the optimal solution to be strongly unique. The maintaining of the latter property under sufficiently small perturbations of all the data is also analyzed, giving a characterization of its stability with respect to these perturbations in terms of the strong Slater condition, the so-called Extended-Nuernberger condition, and the LUB condition.
Solutions to estimation problems for scalar hamilton-jacobi equations using linear programming
Claudel, Christian G.
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.
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 Â© 2011 Elsevier Ltd. All rights reserved.
Directory of Open Access Journals (Sweden)
He-Yau Kang
2016-12-01
Full Text Available Meeting the demand of energy is a challenge for many countries these days, and generating electricity from renewable resources has become a main trend for future economic development. The construction of a renewable energy plant is costly and timely; therefore, a good project management model is essential. In this paper, a fuzzy multiple objective linear programming (FMOLP model is constructed based on program evaluation and review technique (PERT first. With the consideration of the different degrees of importance of the multiple objectives, a fuzzy multiple weighted-objective linear programming (FMWOLP model is constructed next. Through each proposed model, a compromise solution can be devised to maximize the total degree of satisfaction while considering multiple objectives. The results can provide references for the management on what activities and how long these activities should be crashed, how much the total project cost should be, and how long the total project duration time should be. Finally, the proposed models are applied to a case study of a wind turbine construction in Taiwan.
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.
INFORMATION SECURITY RISKS OPTIMIZATION IN CLOUDY SERVICES ON THE BASIS OF LINEAR PROGRAMMING
Directory of Open Access Journals (Sweden)
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.
An improved multiple linear regression and data analysis computer program package
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.
A web portal for classification of expression data using maximal margin linear programming.
Antonov, Alexey V; Tetko, Igor V; Prokopenko, Volodymyr V; Kosykh, Denis; Mewes, Hans W
2004-11-22
The Maximal Margin (MAMA) linear programming classification algorithm has recently been proposed and tested for cancer classification based on expression data. It demonstrated sound performance on publicly available expression datasets. We developed a web interface to allow potential users easy access to the MAMA classification tool. Basic and advanced options provide flexibility in exploitation. The input data format is the same as that used in most publicly available datasets. This makes the web resource particularly convenient for non-expert machine learning users working in the field of expression data analysis.
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.
Directory of Open Access Journals (Sweden)
Alberto Dolara
2017-02-01
Full Text Available This paper presents a comparison of optimization methods applied to islanded micro-grids including renewable energy sources, diesel generators and battery energy storage systems. In particular, a comparative analysis between an optimization model based on linear programming and a model based on mixed integer programming has been carried out. The general formulation of these models has been presented and applied to a real case study micro-grid installed in Somalia. The case study is an islanded micro-grid supplying the city of Garowe by means of a hybrid power plant, consisting of diesel generators, photovoltaic systems and batteries. In both models the optimization is based on load demand and renewable energy production forecast. The optimized control of the battery state of charge, of the spinning reserve and diesel generators allows harvesting as much renewable power as possible or to minimize the use of fossil fuels in energy production.
Consideration in selecting crops for the human-rated life support system: a linear programming model
Wheeler, E. F.; Kossowski, J.; Goto, E.; Langhans, R. W.; White, G.; Albright, L. D.; Wilcox, D.
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.
Consideration in selecting crops for the human-rated life support system: a Linear Programming model
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.
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.
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.
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.
Fan, Yurui; Huang, Guohe; Veawab, Amornvadee
2012-01-01
In this study, a generalized fuzzy linear programming (GFLP) method was developed to deal with uncertainties expressed as fuzzy sets that exist in the constraints and objective function. A stepwise interactive algorithm (SIA) was advanced to solve GFLP model and generate solutions expressed as fuzzy sets. To demonstrate its application, the developed GFLP method was applied to a regional sulfur dioxide (SO2) control planning model to identify effective SO2 mitigation polices with a minimized system performance cost under uncertainty. The results were obtained to represent the amount of SO2 allocated to different control measures from different sources. Compared with the conventional interval-parameter linear programming (ILP) approach, the solutions obtained through GFLP were expressed as fuzzy sets, which can provide intervals for the decision variables and objective function, as well as related possibilities. Therefore, the decision makers can make a tradeoff between model stability and the plausibility based on solutions obtained through GFLP and then identify desired policies for SO2-emission control under uncertainty.
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.
Directory of Open Access Journals (Sweden)
Warid Warid
Full Text Available 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.
Drag reduction of a car model by linear genetic programming control
Li, Ruiying; Cordier, Laurent; Borée, Jacques; Harambat, Fabien; Kaiser, Eurika; Duriez, Thomas
2016-01-01
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 $Re_{H}\\approx3\\times10^{5}$ based on body height. The actuation is performed with pulsed jets at all trailing edges combined with a Coanda deflection surface. The flow is monitored with pressure sensors distributed at the rear side. We apply a model-free control strategy building on Dracopoulos & Kent (Neural Comput. & Applic., vol. 6, 1997, pp. 214-228) and Gautier et al. (J. Fluid Mech., vol. 770, 2015, pp. 442-457). The optimized control laws comprise periodic forcing, multi-frequency forcing and sensor-based feedback including also time-history information feedback and combination thereof. Key enabler is linear genetic programming as simple and efficient framework for multiple inputs (actuators) and multiple outputs (sensors). The proposed linear genetic programming control can select the best open- or closed-loop control in an unsupervis...
Linear programming analysis of the R-parity violation within EDM-constraints
Yamanaka, Nodoka; Sato, Toru; Kubota, Takahiro
2014-12-01
The constraint on the R-parity violating supersymmetric interactions is discussed in the light of current experimental data of the electric dipole moment of neutron, 129Xe , 205Tl, and 199Hg atoms, and YbF and ThO molecules. To investigate the constraints without relying upon the assumption of the dominance of a particular combination of couplings over all the rest, an extensive use is made of the linear programming method in the scan of the parameter space. We give maximally possible values for the EDMs of the proton, deuteron, 3He nucleus, 211Rn, 225Ra, 210Fr, and the R-correlation of the neutron beta decay within the constraints from the current experimental data of the EDMs of neutron, 129Xe, 205Tl, and 199Hg atoms, and YbF and ThO molecules using the linear programming method. It is found that the R-correlation of the neutron beta decay and hadronic EDMs are very useful observables to constrain definite regions of the parameter space of the R-parity violating supersymmetry.
Energy Technology Data Exchange (ETDEWEB)
Matthew J. Tonkin; Claire R. Tiedeman; D. Matthew Ely; and Mary C. Hill
2007-08-16
The OPR-PPR program calculates the Observation-Prediction (OPR) and Parameter-Prediction (PPR) statistics that can be used to evaluate the relative importance of various kinds of data to simulated predictions. The data considered fall into three categories: (1) existing observations, (2) potential observations, and (3) potential information about parameters. The first two are addressed by the OPR statistic; the third is addressed by the PPR statistic. The statistics are based on linear theory and measure the leverage of the data, which depends on the location, the type, and possibly the time of the data being considered. For example, in a ground-water system the type of data might be a head measurement at a particular location and time. As a measure of leverage, the statistics do not take into account the value of the measurement. As linear measures, the OPR and PPR statistics require minimal computational effort once sensitivities have been calculated. Sensitivities need to be calculated for only one set of parameter values; commonly these are the values estimated through model calibration. OPR-PPR can calculate the OPR and PPR statistics for any mathematical model that produces the necessary OPR-PPR input files. In this report, OPR-PPR capabilities are presented in the context of using the ground-water model MODFLOW-2000 and the universal inverse program UCODE_2005. The method used to calculate the OPR and PPR statistics is based on the linear equation for prediction standard deviation. Using sensitivities and other information, OPR-PPR calculates (a) the percent increase in the prediction standard deviation that results when one or more existing observations are omitted from the calibration data set; (b) the percent decrease in the prediction standard deviation that results when one or more potential observations are added to the calibration data set; or (c) the percent decrease in the prediction standard deviation that results when potential information on one
Tonkin, Matthew J.; Tiedeman, Claire R.; Ely, D. Matthew; Hill, Mary C.
2007-01-01
The OPR-PPR program calculates the Observation-Prediction (OPR) and Parameter-Prediction (PPR) statistics that can be used to evaluate the relative importance of various kinds of data to simulated predictions. The data considered fall into three categories: (1) existing observations, (2) potential observations, and (3) potential information about parameters. The first two are addressed by the OPR statistic; the third is addressed by the PPR statistic. The statistics are based on linear theory and measure the leverage of the data, which depends on the location, the type, and possibly the time of the data being considered. For example, in a ground-water system the type of data might be a head measurement at a particular location and time. As a measure of leverage, the statistics do not take into account the value of the measurement. As linear measures, the OPR and PPR statistics require minimal computational effort once sensitivities have been calculated. Sensitivities need to be calculated for only one set of parameter values; commonly these are the values estimated through model calibration. OPR-PPR can calculate the OPR and PPR statistics for any mathematical model that produces the necessary OPR-PPR input files. In this report, OPR-PPR capabilities are presented in the context of using the ground-water model MODFLOW-2000 and the universal inverse program UCODE_2005. The method used to calculate the OPR and PPR statistics is based on the linear equation for prediction standard deviation. Using sensitivities and other information, OPR-PPR calculates (a) the percent increase in the prediction standard deviation that results when one or more existing observations are omitted from the calibration data set; (b) the percent decrease in the prediction standard deviation that results when one or more potential observations are added to the calibration data set; or (c) the percent decrease in the prediction standard deviation that results when potential information on one
A novel approach based on preference-based index for interval bilevel linear programming problem.
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.
National Research Council Canada - National Science Library
Thawley, David
2003-01-01
.... When historical data exists on evaluation measures and performance of alternatives, linear programming and genetic algorithm based optimization may be used to derive historically optimal weights for a hierarchy...
Nidumolu, U.B.; Keulen, van H.; Lubbers, M.T.M.H.; Mapfumo, P.
2007-01-01
An Interactive Multiple Goal Linear Programming (IMGLP) model is developed that considers objectives of multiple stakeholders, i.e. different farmer groups, district agricultural officers and agricultural scientists for agricultural land use analysis. The analysis focuses on crop selection;
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…
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...
Sun, Wei; Huang, Guo H; Lv, Ying; Li, Gongchen
2012-06-01
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 its effectiveness for providing more satisfactory interval solutions than IPFP3. Following its first application to waste management, the IPFP can be potentially applied to other environmental problems under multiple complexities. Copyright © 2012 Elsevier Ltd. All rights reserved.
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.
Ghadie, Mohamed A; Japkowicz, Nathalie; Perkins, Theodore J
2015-08-15
Stem cell differentiation is largely guided by master transcriptional regulators, but it also depends on the expression of other types of genes, such as cell cycle genes, signaling genes, metabolic genes, trafficking genes, etc. Traditional approaches to understanding gene expression patterns across multiple conditions, such as principal components analysis or K-means clustering, can group cell types based on gene expression, but they do so without knowledge of the differentiation hierarchy. Hierarchical clustering can organize cell types into a tree, but in general this tree is different from the differentiation hierarchy itself. Given the differentiation hierarchy and gene expression data at each node, we construct a weighted Euclidean distance metric such that the minimum spanning tree with respect to that metric is precisely the given differentiation hierarchy. We provide a set of linear constraints that are provably sufficient for the desired construction and a linear programming approach to identify sparse sets of weights, effectively identifying genes that are most relevant for discriminating different parts of the tree. We apply our method to microarray gene expression data describing 38 cell types in the hematopoiesis hierarchy, constructing a weighted Euclidean metric that uses just 175 genes. However, we find that there are many alternative sets of weights that satisfy the linear constraints. Thus, in the style of random-forest training, we also construct metrics based on random subsets of the genes and compare them to the metric of 175 genes. We then report on the selected genes and their biological functions. Our approach offers a new way to identify genes that may have important roles in stem cell differentiation. tperkins@ohri.ca Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Directory of Open Access Journals (Sweden)
Clemens Posten
2013-10-01
Full Text Available The unicellular microalga Phaeodactylum tricornutum exhibits the ability to accumulate triacylglycerols to a high specific content when nutrients are limited in the culture medium. Therefore, the organism is a promising candidate for biodiesel production. Mathematical modeling can substantially contribute to process development and optimization of algae cultivation on different levels. In our work we describe a linear programming approach to model and simulate the growth and storage molecule accumulation of P. tricornutum. The model is based on mass and energy balances and shows that the organism realizes the inherent drive for maximization of energy to biomass conversion and growth. The model predicts that under nutrient limiting conditions both storage carbohydrates and lipids are synthesized simultaneously but at different rates. The model was validated with data gained from batch growth experiments.
Linear programming to build food-based dietary guidelines: Romanian food baskets
DEFF Research Database (Denmark)
Parlesak, Alexandr; Robertson, Aileen; Hondru, Gabriela
As in many Member States of the WHO European Region, Romania is seeing an increase in the prevalence of overweight and obesity, particularly among children and adolescents. This is a major risk factor for the development of noncommunicable diseases (NCDs), and innovative approaches using a (“heal......As in many Member States of the WHO European Region, Romania is seeing an increase in the prevalence of overweight and obesity, particularly among children and adolescents. This is a major risk factor for the development of noncommunicable diseases (NCDs), and innovative approaches using......, potatoes and fish and considerably less meat, fats, oils and sugar. In conclusion, the linear programming methodology can facilitate the development of national dietary recommendations that meet both recommended nutrient intake values and WHO food-based dietary guidelines in a cost-efficient manner. How...
Directory of Open Access Journals (Sweden)
Ibnu Fazar
2016-02-01
Full Text Available Kegiatan pembelajaran merupakan kegiatan yang paling pokok dalam keseluruhan proses pendidikan. Penggunaan media teknologi dalam pembelajaran memungkinkan berlangsungnya proses pembelajaran secara individual (individual learning dengan menumbuhkan kemandirian dalam proses belajar, sehingga siswa akan mengalami proses yang jauh lebih bermakna dibandingkan dengan pembelajaran konvensional. Salah satu solusinya adalah pembelajaran menggunakan aplikasi GeoGebra berbantuan Android. Dari hasil penelitian diperoleh data observasi keaktifan siswa rata-rata 86,09 dengan kategori sangat baik. Dari minat siswa 90,32% kategori sangat berminat dan 9,68% kategori berminat. Dari hasil tes diperoleh 38,72% kategori sangat baik, 48,38% kategori baik, dan 12,90% kategori cukup. Dengan demikian pengembangan Lembar Aktivitas Siswa (LAS pada pokok bahasan program linear menggunakan aplikasi GeoGebra berbantuan android yang dikembangkan memiliki efek potensial terhadap peningkatan kemampuan pemahaman siswa dan bahan ajar yang dihasilkan telah dinyatakan valid, praktis, dan mempunyai efek potensial terhadap pemaham konsep matematika.
Optimal local dimming for LED-backlit LCD displays via linear programming
DEFF Research Database (Denmark)
Shu, Xiao; Wu, Xiaolin; Forchhammer, Søren
2012-01-01
LED-backlit LCD displays hold the promise of improving the image quality while reducing the energy consumption with signal-dependent local dimming. To fully realize such potentials we propose a novel local dimming technique that jointly optimizes the intensities of LED backlights and the attenuat......LED-backlit LCD displays hold the promise of improving the image quality while reducing the energy consumption with signal-dependent local dimming. To fully realize such potentials we propose a novel local dimming technique that jointly optimizes the intensities of LED backlights...... 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...
A minimax technique for time-domain design of preset digital equalizers using linear programming
Vaughn, G. L.; Houts, R. C.
1975-01-01
A linear programming technique is presented for the design of a preset finite-impulse response (FIR) digital filter to equalize the intersymbol interference (ISI) present in a baseband channel with known impulse response. A minimax technique is used which minimizes the maximum absolute error between the actual received waveform and a specified raised-cosine waveform. Transversal and frequency-sampling FIR digital filters are compared as to the accuracy of the approximation, the resultant ISI and the transmitted energy required. The transversal designs typically have slightly better waveform accuracy for a given distortion; however, the frequency-sampling equalizer uses fewer multipliers and requires less transmitted energy. A restricted transversal design is shown to use the least number of multipliers at the cost of a significant increase in energy and loss of waveform accuracy at the receiver.
Xia, Bisheng; Qian, Xin; Yao, Hong
2017-11-01
Although the risk-explicit interval linear programming (REILP) model has solved the problem of having interval solutions, it has an equity problem, which can lead to unbalanced allocation between different decision variables. Therefore, an improved REILP model is proposed. This model adds an equity objective function and three constraint conditions to overcome this equity problem. In this case, pollution reduction is in proportion to pollutant load, which supports balanced development between different regional economies. The model is used to solve the problem of pollution load allocation in a small transboundary watershed. Compared with the REILP original model result, our model achieves equity between the upstream and downstream pollutant loads; it also overcomes the problem of greatest pollution reduction, where sources are nearest to the control section. The model provides a better solution to the problem of pollution load allocation than previous versions.
Approximating high-dimensional dynamics by barycentric coordinates with linear programming.
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.
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.
Directory of Open Access Journals (Sweden)
Christian John Etwire
2015-03-01
Full Text Available Abstract This paper examines further a Mixed Integer Linear Programming model constructed for optimal hydrothermal energy generation for Ghana as in 1. Post Optimal Analysis is carried out on the model in order to assess its stability to slight variations of some input parameters such as minimum level running costs extra hourly running costs above minimum level and start up costs of each generator on one hand and load demands and reserve margins on the other. The results show that the firm could minimize its cost of power generation if its input parameters were comparable to those lying between the 10 percent and -10 percent range.The10 percent and -10 percent range yielded a range of investment plans for the firmand also provided a basis for the selection of the best optimal solution.
Mixed-Integer Linear Programming Models for Teaching Assistant Assignment and Extensions
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Xiaobo Qu
2017-01-01
Full Text Available In this paper, we develop mixed-integer linear programming models for assigning the most appropriate teaching assistants to the tutorials in a department. The objective is to maximize the number of tutorials that are taught by the most suitable teaching assistants, accounting for the fact that different teaching assistants have different capabilities and each teaching assistant’s teaching load cannot exceed a maximum value. Moreover, with optimization models, the teaching load allocation, a time-consuming process, does not need to be carried out in a manual manner. We have further presented a number of extensions that capture more practical considerations. Extensive numerical experiments show that the optimization models can be solved by an off-the-shelf solver and used by departments in universities.
Pengembangan Aplikasi Simulasi Perdagangan Saham dengan Sector Rotation dan Linear Programming
Directory of Open Access Journals (Sweden)
Tomy G. Soemapradja
2014-05-01
Full Text Available In strategic development a university will shift from teaching university to research university. It is because academic outcomes will be more useful if they can be commercialized by industries, which help improve the ranking of a university. The development of capital market and management measures of Indonesia Stock Exchange during the last 8 years aiming at academicians in order to identify and be interested in investing in the stock market needs to be observed. That is by providing a simulation so that more students can improve the competition at their graduation. The involvement of industry selection strategy and portfolio management will be required so that the expertise and ability to manage investments in the capital market can be better. So, it necessarily requires a development of simulation application of stock trading with business rotation and linear programming.
Control allocation of ASV based on linear programming and fuzzy logic
Chi, Pei; Chen, Zongji; Zhou, Rui
2006-11-01
Future Aero Space Vehicle flies through both the atmospheric and extra atmospheric fields, which implies the autonomy and adaptability to the uncertainties from the system faults and changing environments. Algorithms based on fuzzy logic and linear programming are presented, which can implement the autonomous control reconfigurations under uncertainties via the redundant actuators. The compensation branch minimizes the difference between the desired control objectives and the actual achievable control if the control power is deficient. Otherwise the optimization branch optimizes some sub-objectives by utilizing the excess control power. The fuzzy logic-based regulator tunes the weight vector of the objective functions by the expert rules to obtain the optimized allocation results under various environments with considerations of the control effectiveness. It is illustrated that the algorithms can satisfy the control performance, save the fuel and smooth the allocation output.
Directory of Open Access Journals (Sweden)
2006-01-01
Full Text Available This paper studies controller design for feedback systems in the presence of asymmetrically bounded signals, using a case study. An asymmetric objective functional is used to consider the asymmetrically bounded signals, which makes possible to derive a linear programming problem. Solving this LP makes possible to design controllers that minimize certain outputs, fulfilling at the same time hard constraints on certain signals. The method is presented by application to a hydrogen reformer, a system in petrochemical plants that produces hydrogen from hydrocarbons: a mixed sensitivity problem is stated and solved, with an additional constraint given by the asymmetric limitations on the magnitude and rate of the control signal, and the asymmetricity in the disturbances.
Neji, Radhouène; Besbes, Ahmed; Komodakis, Nikos; Deux, Jean-François; Maatouk, Mezri; Rahmouni, Alain; Bassez, Guillaume; Fleury, Gilles; Paragios, Nikos
2009-01-01
In this paper, we present a manifold clustering method fo the classification of fibers obtained from diffusion tensor images (DTI) of the human skeletal muscle. Using a linear programming formulation of prototype-based clustering, we propose a novel fiber classification algorithm over manifolds that circumvents the necessity to embed the data in low dimensional spaces and determines automatically the number of clusters. Furthermore, we propose the use of angular Hilbertian metrics between multivariate normal distributions to define a family of distances between tensors that we generalize to fibers. These metrics are used to approximate the geodesic distances over the fiber manifold. We also discuss the case where only geodesic distances to a reduced set of landmark fibers are available. The experimental validation of the method is done using a manually annotated significant dataset of DTI of the calf muscle for healthy and diseased subjects.
Techniques that strive to combat the influence of degeneracy in linear programming problems
Directory of Open Access Journals (Sweden)
J.H. Nel
2003-12-01
Full Text Available Degeneracy can cause enormous problems when solving large scale linear programming problems. This is not only because there is a possibility that the problem can cycle, but also because a large number of iterations can be executed that do not improve the objective. In this article a procedure which utilises derived reduced costs is discussed. The derived reduced cost of a non- basic variable is defined in such a way that it makes the introduction to the non-basic variable into the basis unattractive if such a decision fails to improve the objective. The procedure deliberately strives to combat degeneracy using derived reduced costs, but it also utilises the advantageous properties of the classical gradient methods.
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Tumpal Sihombing
2013-01-01
Full Text Available The world is entering the era of recession when the trend is bearish and market is not so favorable. The capital markets in every major country were experiencing great amount of loss and people suffered in their investment. The Jakarta Composite Index (JCI has shown a great downturn for the past one year but the trend bearish year of the JCI. Therefore, rational investors should consider restructuring their portfolio to set bigger proportion in bonds and cash instead of stocks. Investors can apply modern portfolio theory by Harry Markowitz to find the optimum asset allocation for their portfolio. Higher return is always associated with higher risk. This study shows investors how to find out the lowest risk of a portfolio investment by providing them with several structures of portfolio weighting. By this way, investor can compare and make the decision based on risk-return consideration and opportunity cost as well. Keywords: Modern portfolio theory, Monte Carlo, linear programming
Baran, Richard; Northen, Trent R
2013-10-15
Untargeted metabolite profiling using liquid chromatography and mass spectrometry coupled via electrospray ionization is a powerful tool for the discovery of novel natural products, metabolic capabilities, and biomarkers. However, the elucidation of the identities of uncharacterized metabolites from spectral features remains challenging. A critical step in the metabolite identification workflow is the assignment of redundant spectral features (adducts, fragments, multimers) and calculation of the underlying chemical formula. Inspection of the data by experts using computational tools solving partial problems (e.g., chemical formula calculation for individual ions) can be performed to disambiguate alternative solutions and provide reliable results. However, manual curation is tedious and not readily scalable or standardized. Here we describe an automated procedure for the robust automated mass spectra interpretation and chemical formula calculation using mixed integer linear programming optimization (RAMSI). Chemical rules among related ions are expressed as linear constraints and both the spectra interpretation and chemical formula calculation are performed in a single optimization step. This approach is unbiased in that it does not require predefined sets of neutral losses and positive and negative polarity spectra can be combined in a single optimization. The procedure was evaluated with 30 experimental mass spectra and was found to effectively identify the protonated or deprotonated molecule ([M + H](+) or [M - H](-)) while being robust to the presence of background ions. RAMSI provides a much-needed standardized tool for interpreting ions for subsequent identification in untargeted metabolomics workflows.
Optimisation of substrate blends in anaerobic co-digestion using adaptive linear programming.
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.
Linear programming: an alternative approach for developing formulations for emergency food products.
Sheibani, Ershad; Dabbagh Moghaddam, Arasb; Sharifan, Anousheh; Afshari, Zahra
2017-08-04
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.
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.
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
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
Directory of Open Access Journals (Sweden)
Alexandr Parlesak
Full Text Available 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.
Nowak, Christoph; Heinrichs, Nina
2008-01-01
A meta-analysis encompassing all studies evaluating the impact of the Triple P-Positive Parenting Program on parent and child outcome measures was conducted in an effort to identify variables that moderate the program's effectiveness. Hierarchical linear models (HLM) with three levels of data were employed to analyze effect sizes. The results (N =…
Drag reduction of a car model by linear genetic programming control
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.
Wei, Peng; Sridhar, Banavar; Chen, Neil Yi-Nan; Sun, Dengfent
2012-01-01
A class of strategies has been proposed to reduce contrail formation in the United States airspace. A 3D grid based on weather data and the cruising altitude level of aircraft is adjusted to avoid the persistent contrail potential area with the consideration to fuel-efficiency. In this paper, the authors introduce a contrail avoidance strategy on 3D grid by considering additional operationally feasible constraints from an air traffic controller's aspect. First, shifting too many aircraft to the same cruising level will make the miles-in-trail at this level smaller than the safety separation threshold. Furthermore, the high density of aircraft at one cruising level may exceed the workload for the traffic controller. Therefore, in our new model we restrict the number of total aircraft at each level. Second, the aircraft count variation for successive intervals cannot be too drastic since the workload to manage climbing/descending aircraft is much larger than managing cruising aircraft. The contrail reduction is formulated as an integer-programming problem and the problem is shown to have the property of total unimodularity. Solving the corresponding relaxed linear programming with the simplex method provides an optimal and integral solution to the problem. Simulation results are provided to illustrate the methodology.
Li, Yanning
2014-03-01
This article presents a new optimal control framework for transportation networks in which the state is modeled by a first order scalar conservation law. Using an equivalent formulation based on a Hamilton-Jacobi (H-J) equation and the commonly used triangular fundamental diagram, we pose the problem of controlling the state of the system on a network link, in a finite horizon, as a Linear Program (LP). We then show that this framework can be extended to an arbitrary transportation network, resulting in an LP or a Quadratic Program. Unlike many previously investigated transportation network control schemes, this method yields a globally optimal solution and is capable of handling shocks (i.e., discontinuities in the state of the system). As it leverages the intrinsic properties of the H-J equation used to model the state of the system, it does not require any approximation, unlike classical methods that are based on discretizations of the model. The computational efficiency of the method is illustrated on a transportation network. © 2014 IEEE.
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.
A two-stage sequential linear programming approach to IMRT dose optimization
Zhang, Hao H; Meyer, Robert R; Wu, Jianzhou; Naqvi, Shahid A; Shi, Leyuan; D’Souza, Warren D
2010-01-01
The conventional IMRT planning process involves two stages in which the first stage consists of fast but approximate idealized pencil beam dose calculations and dose optimization and the second stage consists of discretization of the intensity maps followed by intensity map segmentation and a more accurate final dose calculation corresponding to physical beam apertures. Consequently, there can be differences between the presumed dose distribution corresponding to pencil beam calculations and optimization and a more accurately computed dose distribution corresponding to beam segments that takes into account collimator-specific effects. IMRT optimization is computationally expensive and has therefore led to the use of heuristic (e.g., simulated annealing and genetic algorithms) approaches that do not encompass a global view of the solution space. We modify the traditional two-stage IMRT optimization process by augmenting the second stage via an accurate Monte-Carlo based kernel-superposition dose calculations corresponding to beam apertures combined with an exact mathematical programming based sequential optimization approach that uses linear programming (SLP). Our approach was tested on three challenging clinical test cases with multileaf collimator constraints corresponding to two vendors. We compared our approach to the conventional IMRT planning approach, a direct-aperture approach and a segment weight optimization approach. Our results in all three cases indicate that the SLP approach outperformed the other approaches, achieving superior critical structure sparing. Convergence of our approach is also demonstrated. Finally, our approach has also been integrated with a commercial treatment planning system and may be utilized clinically. PMID:20071764
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.
Aspect-object alignment with Integer Linear Programming in opinion mining.
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.
A linear programming model for protein inference problem in shotgun proteomics.
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.
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.
A linear programming model to optimize diets in environmental policy scenarios.
Moraes, L E; Wilen, J E; Robinson, P H; Fadel, J G
2012-03-01
The objective was to develop a linear programming model to formulate diets for dairy cattle when environmental policies are present and to examine effects of these policies on diet formulation and dairy cattle nitrogen and mineral excretions as well as methane emissions. The model was developed as a minimum cost diet model. Two types of environmental policies were examined: a tax and a constraint on methane emissions. A tax was incorporated to simulate a greenhouse gas emissions tax policy, and prices of carbon credits in the current carbon markets were attributed to the methane production variable. Three independent runs were made, using carbon dioxide equivalent prices of $5, $17, and $250/t. A constraint was incorporated into the model to simulate the second type of environmental policy, reducing methane emissions by predetermined amounts. The linear programming formulation of this second alternative enabled the calculation of marginal costs of reducing methane emissions. Methane emission and manure production by dairy cows were calculated according to published equations, and nitrogen and mineral excretions were calculated by mass conservation laws. Results were compared with respect to the values generated by a base least-cost model. Current prices of the carbon credit market did not appear onerous enough to have a substantive incentive effect in reducing methane emissions and altering diet costs of our hypothetical dairy herd. However, when emissions of methane were assumed to be reduced by 5, 10, and 13.5% from the base model, total diet costs increased by 5, 19.1, and 48.5%, respectively. Either these increased costs would be passed onto the consumer or dairy producers would go out of business. Nitrogen and potassium excretions were increased by 16.5 and 16.7% with a 13.5% reduction in methane emissions from the base model. Imposing methane restrictions would further increase the demand for grains and other human-edible crops, which is not a progressive
A LINEAR PROGRAMMING METHOD TO ENHANCE RESOURCE UTILIZATION CASE OF ETHIOPIAN APPAREL SECTOR
Directory of Open Access Journals (Sweden)
Gezahegn Tesfaye
2016-06-01
Full Text Available The Ethiopian industrial development strategy is characterized by export-led and labor intensive industrialization. The country is emerging as the most important investment destination in its apparel sector. Thought this sector is expected to generate more income from the export market, its export earnings remain trivial mainly due to the inefficient organizational resource utilization. One of the competent techniques that help companies to efficiently improve the use of their resources to increase their profit is linear programming. In apparel manufacturing firms, efficient use of materials such as fabrics and sewing threads and processing time at different stages of production as well as minimization of labor and materials cost are necessary to enhance their profitability. Cutting, sewing, and finishing operations deserve more attention for apparel process optimization. However, the issue of proper resource allocation remains an unsolved problem within the Ethiopian apparel industry. The aim of this research is to devise efficient resource utilization mechanism for Ethiopian apparel sector to improve their resource utilization and profitability, taking one of the garment factories engaged in the export market as a case study. Five types of products the company is currently producing, the amount of resources employed to produce each unit of the products, and the value of profit per unit from the sale of each products have been collected from the case company. The monthly availability of resources utilized and the monthly production volume of the five products have also been collected from the company. The data gathered was mathematically modeled using a linear programming technique, and solved using MS-Excel solver. The findings of the study depicts that all of the organizational resources are severely underutilized. This research proved that the resource utilization of the case company can be improved from 46.41% of the current resource
Kler, A. M.; Maximov, A. S.; Epishkin, N. O.
2017-09-01
The paper describes the developed method for analyzing technological schemes of thermal power plants based on solving problems of auxiliary linear programming. This method involves solving the linear programming problems to evaluate the effect of supply and removal of heat or material flows of various sizes at different points of the technological scheme of a thermal power plant (TPP). The method effectiveness is demonstrated by the example of the coaldust steam turbine unit with nominal electrical output of 660 MW. As a result of its application, the change of the technological scheme of the unit was found to provide reduction in electricity cost by 0.3%.
Earthquake mechanisms from linear-programming inversion of seismic-wave amplitude ratios
Julian, B.R.; Foulger, G.R.
1996-01-01
The amplitudes of radiated seismic waves contain far more information about earthquake source mechanisms than do first-motion polarities, but amplitudes are severely distorted by the effects of heterogeneity in the Earth. This distortion can be reduced greatly by using the ratios of amplitudes of appropriately chosen seismic phases, rather than simple amplitudes, but existing methods for inverting amplitude ratios are severely nonlinear and require computationally intensive searching methods to ensure that solutions are globally optimal. Searching methods are particularly costly if general (moment tensor) mechanisms are allowed. Efficient linear-programming methods, which do not suffer from these problems, have previously been applied to inverting polarities and wave amplitudes. We extend these methods to amplitude ratios, in which formulation on inequality constraint for an amplitude ratio takes the same mathematical form as a polarity observation. Three-component digital data for an earthquake at the Hengill-Grensdalur geothermal area in southwestern Iceland illustrate the power of the method. Polarities of P, SH, and SV waves, unusually well distributed on the focal sphere, cannot distinguish between diverse mechanisms, including a double couple. Amplitude ratios, on the other hand, clearly rule out the double-couple solution and require a large explosive isotropic component.
Optimizing the herd calving pattern with linear programming and dynamic probabilistic simulation.
Jalvingh, A W; Dijkhuizen, A A; Van Arendonk, J A
1994-06-01
Until recently, little attention has been paid to the influence of seasonal variation in performance and prices on the optimal calving pattern of a herd. A method was developed to determine the herd calving pattern that is farm-specific and optimal with use of linear programming. The required technical and economic parameters are calculated with a dynamic probabilistic simulation model of the dairy herd. The approach was illustrated with a situation in which the objective was to maximize the gross margin of the herd and the annual milk production of the herd was restricted, resulting in an optimal calving pattern: all heifers calved during August. When, in addition, only home-reared replacement heifers were allowed to enter the herd, heifer calvings took place from July to October. The gross margin was reduced by only Dfl. .13/100 kg of milk ($1 US = 1.80 Dfl.) as a result of the additional constraint. The sensitivity of the optimal calving pattern of herd was determined for lower reproductive performance and when seasonal price variation was ignored. The method described herein is a flexible tool for determining the optimal calving pattern of herd, taking into account farm-specific inputs and constraints.
Integer Linear Programming for Constrained Multi-Aspect Committee Review Assignment
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
Boundary Control of Linear Uncertain 1-D Parabolic PDE Using Approximate Dynamic Programming.
Talaei, Behzad; Jagannathan, Sarangapani; Singler, John
2017-03-02
This paper develops a near optimal boundary control method for distributed parameter systems governed by uncertain linear 1-D parabolic partial differential equations (PDE) by using approximate dynamic programming. A quadratic surface integral is proposed to express the optimal cost functional for the infinite-dimensional state space. Accordingly, the Hamilton-Jacobi-Bellman (HJB) equation is formulated in the infinite-dimensional domain without using any model reduction. Subsequently, a neural network identifier is developed to estimate the unknown spatially varying coefficient in PDE dynamics. Novel tuning law is proposed to guarantee the boundedness of identifier approximation error in the PDE domain. A radial basis network (RBN) is subsequently proposed to generate an approximate solution for the optimal surface kernel function online. The tuning law for near optimal RBN weights is created, such that the HJB equation error is minimized while the dynamics are identified and closed-loop system remains stable. Ultimate boundedness (UB) of the closed-loop system is verified by using the Lyapunov theory. The performance of the proposed controller is successfully confirmed by simulation on an unstable diffusion-reaction process.
lpNet: a linear programming approach to reconstruct signal transduction networks.
Matos, Marta R A; Knapp, Bettina; Kaderali, Lars
2015-10-01
With the widespread availability of high-throughput experimental technologies it has become possible to study hundreds to thousands of cellular factors simultaneously, such as coding- or non-coding mRNA or protein concentrations. Still, extracting information about the underlying regulatory or signaling interactions from these data remains a difficult challenge. We present a flexible approach towards network inference based on linear programming. Our method reconstructs the interactions of factors from a combination of perturbation/non-perturbation and steady-state/time-series data. We show both on simulated and real data that our methods are able to reconstruct the underlying networks fast and efficiently, thus shedding new light on biological processes and, in particular, into disease's mechanisms of action. We have implemented the approach as an R package available through bioconductor. This R package is freely available under the Gnu Public License (GPL-3) from bioconductor.org (http://bioconductor.org/packages/release/bioc/html/lpNet.html) and is compatible with most operating systems (Windows, Linux, Mac OS) and hardware architectures. bettina.knapp@helmholtz-muenchen.de Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
An improved exploratory search technique for pure integer linear programming problems
Fogle, F. R.
1990-01-01
The development is documented of a heuristic method for the solution of pure integer linear programming problems. The procedure draws its methodology from the ideas of Hooke and Jeeves type 1 and 2 exploratory searches, greedy procedures, and neighborhood searches. It uses an efficient rounding method to obtain its first feasible integer point from the optimal continuous solution obtained via the simplex method. Since this method is based entirely on simple addition or subtraction of one to each variable of a point in n-space and the subsequent comparison of candidate solutions to a given set of constraints, it facilitates significant complexity improvements over existing techniques. It also obtains the same optimal solution found by the branch-and-bound technique in 44 of 45 small to moderate size test problems. Two example problems are worked in detail to show the inner workings of the method. Furthermore, using an established weighted scheme for comparing computational effort involved in an algorithm, a comparison of this algorithm is made to the more established and rigorous branch-and-bound method. A computer implementation of the procedure, in PC compatible Pascal, is also presented and discussed.
Optimizing financial effects of HIE: a multi-party linear programming approach.
Sridhar, Srikrishna; Brennan, Patricia Flatley; Wright, Stephen J; Robinson, Stephen M
2012-01-01
To describe an analytical framework for quantifying the societal savings and financial consequences of a health information exchange (HIE), and to demonstrate its use in designing pricing policies for sustainable HIEs. We developed a linear programming model to (1) quantify the financial worth of HIE information to each of its participating institutions and (2) evaluate three HIE pricing policies: fixed-rate annual, charge per visit, and charge per look-up. We considered three desired outcomes of HIE-related emergency care (modeled as parameters): preventing unrequired hospitalizations, reducing duplicate tests, and avoiding emergency department (ED) visits. We applied this framework to 4639 ED encounters over a 12-month period in three large EDs in Milwaukee, Wisconsin, using Medicare/Medicaid claims data, public reports of hospital admissions, published payer mix data, and use data from a not-for-profit regional HIE. For this HIE, data accesses produced net financial gains for all providers and payers. Gains, due to HIE, were more significant for providers with more health maintenance organizations patients. Reducing unrequired hospitalizations and avoiding repeat ED visits were responsible for more than 70% of the savings. The results showed that fixed annual subscriptions can sustain this HIE, while ensuring financial gains to all participants. Sensitivity analysis revealed that the results were robust to uncertainties in modeling parameters. Our specific HIE pricing recommendations depend on the unique characteristics of this study population. However, our main contribution is the modeling approach, which is broadly applicable to other populations.
Quality evaluation of millet-soy blended extrudates formulated through linear programming.
Balasubramanian, S; Singh, K K; Patil, R T; Onkar, Kolhe K
2012-08-01
Whole pearl millet, finger millet and decorticated soy bean blended (millet soy) extrudates formulations were designed using a linear programming (LP) model to minimize the total cost of the finished product. LP formulated composite flour was extruded through twin screw food extruder at different feed rate (6.5-13.5 kg/h), screw speed (200-350 rpm, constant feed moisture (14% wb), barrel temperature (120 °C) and cutter speed (15 rpm). The physical, functional, textural and pasting characteristics of extrudates were examined and their responses were studied. Expansion index (2.31) and sectional expansion index (5.39) was found to be was found maximum for feed rate and screw speed combination 9.5 kg/h and 250 rpm. However, density (0.25 × 10(-3) g/mm(3)) was maximum for 9.5 kg/h and 300 rpm combination. Maximum color change (10.32) was found for 9.5 kg/h feed rate and 200 rpm screw speed. The lower hardness was obtained for the samples extruded at lowest feed rate (6.5 kg/h) for all screw speed and feed rate at 9.5 kg/h for 300-350 rpm screw speed. Peak viscosity decreases with all screw speed of 9.5 kg/h feed rate.
A depth-first search algorithm to compute elementary flux modes by linear programming.
Quek, Lake-Ee; Nielsen, Lars K
2014-07-30
The decomposition of complex metabolic networks into elementary flux modes (EFMs) provides a useful framework for exploring reaction interactions systematically. Generating a complete set of EFMs for large-scale models, however, is near impossible. Even for moderately-sized models (linear programming (LP) to enumerate EFMs in an exhaustive fashion. Constraints can be introduced to directly generate a subset of EFMs satisfying the set of constraints. The depth-first search algorithm has a constant memory overhead. Using flux constraints, a large LP problem can be massively divided and parallelized into independent sub-jobs for deployment into computing clusters. Since the sub-jobs do not overlap, the approach scales to utilize all available computing nodes with minimal coordination overhead or memory limitations. The speed of the algorithm was comparable to efmtool, a mainstream Double Description method, when enumerating all EFMs; the attrition power gained from performing flux feasibility tests offsets the increased computational demand of running an LP solver. Unlike the Double Description method, the algorithm enables accelerated enumeration of all EFMs satisfying a set of constraints.
Optimising the selection of food items for FFQs using Mixed Integer Linear Programming.
Gerdessen, Johanna C; Souverein, Olga W; van 't Veer, Pieter; de Vries, Jeanne Hm
2015-01-01
To support the selection of food items for FFQs in such a way that the amount of information on all relevant nutrients is maximised while the food list is as short as possible. Selection of the most informative food items to be included in FFQs was modelled as a Mixed Integer Linear Programming (MILP) model. The methodology was demonstrated for an FFQ with interest in energy, total protein, total fat, saturated fat, monounsaturated fat, polyunsaturated fat, total carbohydrates, mono- and disaccharides, dietary fibre and potassium. The food lists generated by the MILP model have good performance in terms of length, coverage and R 2 (explained variance) of all nutrients. MILP-generated food lists were 32-40 % shorter than a benchmark food list, whereas their quality in terms of R 2 was similar to that of the benchmark. The results suggest that the MILP model makes the selection process faster, more standardised and transparent, and is especially helpful in coping with multiple nutrients. The complexity of the method does not increase with increasing number of nutrients. The generated food lists appear either shorter or provide more information than a food list generated without the MILP model.
Lu, Zhao; Sun, Jing; Butts, Kenneth
2014-05-01
Support vector regression for approximating nonlinear dynamic systems is more delicate than the approximation of indicator functions in support vector classification, particularly for systems that involve multitudes of time scales in their sampled data. The kernel used for support vector learning determines the class of functions from which a support vector machine can draw its solution, and the choice of kernel significantly influences the performance of a support vector machine. In this paper, to bridge the gap between wavelet multiresolution analysis and kernel learning, the closed-form orthogonal wavelet is exploited to construct new multiscale asymmetric orthogonal wavelet kernels for linear programming support vector learning. The closed-form multiscale orthogonal wavelet kernel provides a systematic framework to implement multiscale kernel learning via dyadic dilations and also enables us to represent complex nonlinear dynamics effectively. To demonstrate the superiority of the proposed multiscale wavelet kernel in identifying complex nonlinear dynamic systems, two case studies are presented that aim at building parallel models on benchmark datasets. The development of parallel models that address the long-term/mid-term prediction issue is more intricate and challenging than the identification of series-parallel models where only one-step ahead prediction is required. Simulation results illustrate the effectiveness of the proposed multiscale kernel learning.
A mixed-integer linear programming approach to the reduction of genome-scale metabolic networks.
Röhl, Annika; Bockmayr, Alexander
2017-01-03
Constraint-based analysis has become a widely used method to study metabolic networks. While some of the associated algorithms can be applied to genome-scale network reconstructions with several thousands of reactions, others are limited to small or medium-sized models. In 2015, Erdrich et al. introduced a method called NetworkReducer, which reduces large metabolic networks to smaller subnetworks, while preserving a set of biological requirements that can be specified by the user. Already in 2001, Burgard et al. developed a mixed-integer linear programming (MILP) approach for computing minimal reaction sets under a given growth requirement. Here we present an MILP approach for computing minimum subnetworks with the given properties. The minimality (with respect to the number of active reactions) is not guaranteed by NetworkReducer, while the method by Burgard et al. does not allow specifying the different biological requirements. Our procedure is about 5-10 times faster than NetworkReducer and can enumerate all minimum subnetworks in case there exist several ones. This allows identifying common reactions that are present in all subnetworks, and reactions appearing in alternative pathways. Applying complex analysis methods to genome-scale metabolic networks is often not possible in practice. Thus it may become necessary to reduce the size of the network while keeping important functionalities. We propose a MILP solution to this problem. Compared to previous work, our approach is more efficient and allows computing not only one, but even all minimum subnetworks satisfying the required properties.
Poos, Alexandra M; Maicher, André; Dieckmann, Anna K; Oswald, Marcus; Eils, Roland; Kupiec, Martin; Luke, Brian; König, Rainer
2016-06-02
Understanding telomere length maintenance mechanisms is central in cancer biology as their dysregulation is one of the hallmarks for immortalization of cancer cells. Important for this well-balanced control is the transcriptional regulation of the telomerase genes. We integrated Mixed Integer Linear Programming models into a comparative machine learning based approach to identify regulatory interactions that best explain the discrepancy of telomerase transcript levels in yeast mutants with deleted regulators showing aberrant telomere length, when compared to mutants with normal telomere length. We uncover novel regulators of telomerase expression, several of which affect histone levels or modifications. In particular, our results point to the transcription factors Sum1, Hst1 and Srb2 as being important for the regulation of EST1 transcription, and we validated the effect of Sum1 experimentally. We compiled our machine learning method leading to a user friendly package for R which can straightforwardly be applied to similar problems integrating gene regulator binding information and expression profiles of samples of e.g. different phenotypes, diseases or treatments. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.
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.
Computing Assortative Mixing by Degree with the s-Metric in Networks Using Linear Programming
Directory of Open Access Journals (Sweden)
Lourens J. Waldorp
2015-01-01
Full Text Available Calculation of assortative mixing by degree in networks indicates whether nodes with similar degree are connected to each other. In networks with scale-free distribution high values of assortative mixing by degree can be an indication of a hub-like core in networks. Degree correlation has generally been used to measure assortative mixing of a network. But it has been shown that degree correlation cannot always distinguish properly between different networks with nodes that have the same degrees. The so-called s-metric has been shown to be a better choice to calculate assortative mixing. The s-metric is normalized with respect to the class of networks without self-loops, multiple edges, and multiple components, while degree correlation is always normalized with respect to unrestricted networks, where self-loops, multiple edges, and multiple components are allowed. The challenge in computing the normalized s-metric is in obtaining the minimum and maximum value within a specific class of networks. We show that this can be solved by using linear programming. We use Lagrangian relaxation and the subgradient algorithm to obtain a solution to the s-metric problem. Several examples are given to illustrate the principles and some simulations indicate that the solutions are generally accurate.
Improving an Integer Linear Programming Model of an Ecovat Buffer by Adding Long-Term Planning
Directory of Open Access Journals (Sweden)
Gijs J. H. de Goeijen
2017-12-01
Full Text Available The Ecovat is a seasonal thermal storage solution consisting of a large underground water tank divided into a number of virtual segments that can be individually charged and discharged. The goal of the Ecovat is to supply heat demand to a neighborhood throughout the entire year. In this work, we extend an integer linear programming model to describe the charging and discharging of such an Ecovat buffer by adding a long-term (yearly planning step to the model. We compare the results from the model using this extension to previously obtained results and show significant improvements when looking at the combination of costs and the energy content of the buffer at the end of the optimization. Furthermore, we show that the model is very robust against prediction errors. For this, we compare two different cases: one case in which we assume perfect predictions are available and one case in which we assume no predictions are available. The largest observed difference in costs between these two cases is less than 2%.
Jung, Ho-Won; El Emam, Khaled
2014-05-29
A linear programming (LP) model was proposed to create de-identified data sets that maximally include spatial detail (e.g., geocodes such as ZIP or postal codes, census blocks, and locations on maps) while complying with the HIPAA Privacy Rule's Expert Determination method, i.e., ensuring that the risk of re-identification is very small. The LP model determines the transition probability from an original location of a patient to a new randomized location. However, it has a limitation for the cases of areas with a small population (e.g., median of 10 people in a ZIP code). We extend the previous LP model to accommodate the cases of a smaller population in some locations, while creating de-identified patient spatial data sets which ensure the risk of re-identification is very small. Our LP model was applied to a data set of 11,740 postal codes in the City of Ottawa, Canada. On this data set we demonstrated the limitations of the previous LP model, in that it produces improbable results, and showed how our extensions to deal with small areas allows the de-identification of the whole data set. The LP model described in this study can be used to de-identify geospatial information for areas with small populations with minimal distortion to postal codes. Our LP model can be extended to include other information, such as age and gender.
High Productivity Programming of Dense Linear Algebra on Heterogeneous NUMA Architectures
Alomairy, Rabab M.
2013-07-01
High-end multicore systems with GPU-based accelerators are now ubiquitous in the hardware landscape. Besides dealing with the nontrivial heterogeneous environ- ment, end users should often take into consideration the underlying memory architec- ture to decrease the overhead of data motion, especially when running on non-uniform memory access (NUMA) platforms. We propose the OmpSs parallel programming model approach using its Nanos++ dynamic runtime system to solve the two challeng- ing problems aforementioned, through 1) an innovative NUMA node-aware scheduling policy to reduce data movement between NUMA nodes and 2) a nested parallelism feature to concurrently exploit the resources available from the GPU devices as well as the CPU host, without compromising the overall performance. Our approach fea- tures separation of concerns by abstracting the complexity of the hardware from the end users so that high productivity can be achieved. The Cholesky factorization is used as a benchmark representative of dense numerical linear algebra algorithms. Superior performance is also demonstrated on the symmetric matrix inversion based on Cholesky factorization, commonly used in co-variance computations in statistics. Performance on a NUMA system with Kepler-based GPUs exceeds that of existing implementations, while the OmpSs-enabled code remains very similar to its original sequential version.
How to use composite indicator and linear programming model for determine sustainable tourism.
Ziaabadi, Maryam; Malakootian, Mohammad; Zare Mehrjerdi, Mohammad Reza; Jalaee, Seied Abdolmajid; Mehrabi Boshrabadi, Hosein
2017-01-01
The tourism industry which is one of the most dynamic economic activities in today's world plays a significant role in the sustainable development. Therefore, in addition to paying attention to tourism, sustainable tourism must be taken into huge account; otherwise, the environment and its health will be damaged irreparably. To determine the level of sustainability in this study, indicators of sustainable tourism were first presented in three environmental health, economic and social aspects. Then, the levels of sustainable tourism and environmental sustainability were practically measured in different cities of Kerman Province using a composite indicator, a linear programming model, Delphi method and the questionnaire technique. Finally, the study cities (tourist attractions) were ranked. Result of this study showed that unfortunately the tourism opportunities were not used appropriately in these cities and tourist destinations, and that environmental aspect (health and environmental sustainability) had very bad situations compared to social and economic aspects. In other words, environmental health had the lowest levels of sustainability. The environment is a place for all human activities like tourism, social and economic issues; therefore, its stability and health is of great importance. Thus, it is necessary to pay more attention to sustainability of activities, management and environmental health in planning sustainable development in regional and national policy.
Mitsos, Alexander; Melas, Ioannis N; Morris, Melody K; Saez-Rodriguez, Julio; Lauffenburger, Douglas A; Alexopoulos, Leonidas G
2012-01-01
Modeling of signal transduction pathways plays a major role in understanding cells' function and predicting cellular response. Mathematical formalisms based on a logic formalism are relatively simple but can describe how signals propagate from one protein to the next and have led to the construction of models that simulate the cells response to environmental or other perturbations. Constrained fuzzy logic was recently introduced to train models to cell specific data to result in quantitative pathway models of the specific cellular behavior. There are two major issues in this pathway optimization: i) excessive CPU time requirements and ii) loosely constrained optimization problem due to lack of data with respect to large signaling pathways. Herein, we address both issues: the former by reformulating the pathway optimization as a regular nonlinear optimization problem; and the latter by enhanced algorithms to pre/post-process the signaling network to remove parts that cannot be identified given the experimental conditions. As a case study, we tackle the construction of cell type specific pathways in normal and transformed hepatocytes using medium and large-scale functional phosphoproteomic datasets. The proposed Non Linear Programming (NLP) formulation allows for fast optimization of signaling topologies by combining the versatile nature of logic modeling with state of the art optimization algorithms.
Directory of Open Access Journals (Sweden)
Alexander Mitsos
Full Text Available Modeling of signal transduction pathways plays a major role in understanding cells' function and predicting cellular response. Mathematical formalisms based on a logic formalism are relatively simple but can describe how signals propagate from one protein to the next and have led to the construction of models that simulate the cells response to environmental or other perturbations. Constrained fuzzy logic was recently introduced to train models to cell specific data to result in quantitative pathway models of the specific cellular behavior. There are two major issues in this pathway optimization: i excessive CPU time requirements and ii loosely constrained optimization problem due to lack of data with respect to large signaling pathways. Herein, we address both issues: the former by reformulating the pathway optimization as a regular nonlinear optimization problem; and the latter by enhanced algorithms to pre/post-process the signaling network to remove parts that cannot be identified given the experimental conditions. As a case study, we tackle the construction of cell type specific pathways in normal and transformed hepatocytes using medium and large-scale functional phosphoproteomic datasets. The proposed Non Linear Programming (NLP formulation allows for fast optimization of signaling topologies by combining the versatile nature of logic modeling with state of the art optimization algorithms.
Optimal planning of gas turbine cogeneration system based on linear programming
Energy Technology Data Exchange (ETDEWEB)
Oh, S.D. [Hyosung Corp., Seoul (Korea, Republic of); Kwak, H.Y. [Chung-Ang Univ., Seoul (Korea, Republic of). Dept. of Mechanical Engineering
2005-07-01
Cogeneration systems can result in significant energy efficiency improvements because they produce electrical and heat energy simultaneously from a single source of fuel. This paper discussed planning and design optimization practices for the successful application of a gas turbine cogeneration plant in a hotel and a public building. It was suggested that planners should determine the optimal plant configuration by first selecting the size and number of auxiliary equipment, as well as considering annual electricity costs and heat and cooling requirements. An optimal planning method was presented, employing system configurations among possible combinations of equipment, operational plans and energy demand patterns. A mixed-integer linear program and branch and bound algorithms were adapted to obtain the optimal configuration, based on an annual cost method. A public building and a hotel in Seoul, Korea were selected as case studies. Energy demand patterns for both buildings were presented, with details of maximum outputs and initial equipment costs for co-generation plants. Payback periods and internal rates of return were examined. It was concluded that the optimal configuration of the cogeneration plant is determined by considering the annual energy demand patterns of both buildings, as these patterns are a crucial parameter in determining the feasibility of a cogeneration plant. It was suggested that the methods presented in this study may provide the best configuration of a cogeneration plant fitted to a hotel, or public buildings. 6 refs., 9 tabs., 6 figs.
Dyehouse, Melissa; Bennett, Deborah; Harbor, Jon; Childress, Amy; Dark, Melissa
2009-08-01
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 programs. Causal loop diagrams based on a systems thinking approach can better capture a multidimensional, layered program model while providing a more complete understanding of the relationship between program elements, which enables evaluators to examine influences and dependencies between and within program components. Few studies describe how to conceptualize and apply systems models for educational program evaluation. The goal of this paper is to use our NSF-funded, Interdisciplinary GK-12 project: Bringing Authentic Problem Solving in STEM to Rural Middle Schools to illustrate a systems thinking approach to model a complex educational program to aid in evaluation. GK-12 pairs eight teachers with eight STEM doctoral fellows per program year to implement curricula in middle schools. We demonstrate how systems thinking provides added value by modeling the participant groups, instruments, outcomes, and other factors in ways that enhance the interpretation of quantitative and qualitative data. Limitations of the model include added complexity. Implications include better understanding of interactions and outcomes and analyses reflecting interacting or conflicting variables.
Liang, Bin; Li, Yongbao; Ran, Wei; Guo, Bin; Xu, Xuang; Liu, Bo; Li, Jiafeng; Wu, Qiuwen; Zhou, Fugen
2017-11-17
With robot-controlled linac positioning, the robotic radiotherapy system such as CyberKnife significantly increases the freedom in radiation beam placement, but also imposes more challenges on treatment plan optimization. The resampling mechanism in vendor supplied treatment planning system (MultiPlan) could not fully explore the increased beam direction search space. Besides, a sparse treatment plan (using fewer beams) is desired to improve the treatment efficiency. This study proposes a singular value decomposition linear programming (SVDLP) optimization technique for circular collimator based robotic radiotherapy. The SVDLP approach initializes the input beams by simulating the process of covering the entire target volume with equivalent beam taper. The requirements on dosimetry distribution are modeled as hard and soft constraints, and the sparsity of treatment plan is achieved by compressive sensing. The proposed liner programming (LP) model optimizes beam weight by minimizing the deviation of soft constraints while subjecting to hard constraints, with the constraint on the l^{1} norm of beam weight. A singular value decomposition (SVD) based acceleration technique was developed for the LP model. Based on the degeneracy of influence matrix, the model is first compressed into lower dimension for optimization, and then back-projected to reconstruct the beam weight. After beam weight optimization, the number of beams is reduced by removing the beams with low weight, and optimizing the weight of remaining beams using the same model. This beam reduction technique is further validated by a mixed integer programming (MIP) model. The SVDLP approach was tested on a lung case. The results demonstrate that the SVD acceleration technique speeds up the optimization by a factor of 4.8. And the beam reduction achieves similar plan quality as the globally optimal plan obtained by MIP model, but is 1-2 orders of magnitude faster. Furthermore, the SVDLP approach
Xia, Youshen; Feng, Gang; Wang, Jun
2004-09-01
This paper presents a recurrent neural network for solving strict convex quadratic programming problems and related linear piecewise equations. Compared with the existing neural networks for quadratic program, the proposed neural network has a one-layer structure with a low model complexity. Moreover, the proposed neural network is shown to have a finite-time convergence and exponential convergence. Illustrative examples further show the good performance of the proposed neural network in real-time applications.
Proximal renal tubular acidosis
Renal tubular acidosis - proximal; Type II RTA; RTA - proximal; Renal tubular acidosis type II ... by alkaline substances, mainly bicarbonate. Proximal renal tubular acidosis (Type II RTA) occurs when bicarbonate is not ...
Chang, L.; Chen, Y.; Pan, C.
2009-12-01
Surface water resources are strongly influenced by hydrological conditions, and using only surface water resources as water supplies may have higher shortage risk than before because of the climate change caused by the global warming. Conjunctive use of surface and subsurface water is one of the most effective water resource practices to increase water supply reliability with minimal cost and environmental impact. Therefore, this paper presents a novel stepwise optimization model for optimizing the conjunctive use of surface and subsurface water resources management. At each time step, a two level decomposition approach was proposed to divide the nonlinear optimal conjunctive use problem into a linear surface water subproblem and a nonlinear groundwater subproblem. Because of the two level decomposition approach, a hybrid framework is used for the implementation of the conjunctive use model. In the hybrid framework, evolution algorithms, Genetic Algorithm (GA) and Artificial Neural Network (ANN), and Linear Programming (LP) are used for model solving. GA and LP are respectively used for determining the optimal pumping quantities and reservoir allocation, and ANN is used for the groundwater simulation. In the groundwater simulation, this study uses an ANN to simulate groundwater response and greatly reduce computational loading for unconfined aquifers, unlike conventional “response matrix method” or “embedding method”. Because of the very high performance of LP, the usage of LP for the linear surface water subproblem can significantly decrease the computational burden of entire model. In this study, four cases have been demonstrated. Case #1 is a pure surface water case and others are conjunctive use cases. In Case #2, “surface water supply firstly” is the supply principle between surface water. In Case #3 and #4, the “Index Balance” theory is the supply principle and different operation curves used in different cases respectively. The case result
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
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)
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.
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...
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...
Tharrey, Marion; Olaya, Gilma A; Fewtrell, Mary; Ferguson, Elaine
2017-12-01
The aim of the study was to use linear programming (LP) analyses to adapt New Complementary Feeding Guidelines (NCFg) designed for infants aged 6 to 12 months living in poor socioeconomic circumstances in Bogota to ensure dietary adequacy for young children aged 12 to 23 months. A secondary data analysis was performed using dietary and anthropometric data collected from 12-month-old infants (n = 72) participating in a randomized controlled trial. LP analyses were performed to identify nutrients whose requirements were difficult to achieve using local foods as consumed; and to test and compare the NCFg and alternative food-based recommendations (FBRs) on the basis of dietary adequacy, for 11 micronutrients, at the population level. Thiamine recommended nutrient intakes for these young children could not be achieved given local foods as consumed. NCFg focusing only on meat, fruits, vegetables, and breast milk ensured dietary adequacy at the population level for only 4 micronutrients, increasing to 8 of 11 modelled micronutrients when the FBRs promoted legumes, dairy, vitamin A-rich vegetables, and chicken giblets. None of the FBRs tested ensured population-level dietary adequacy for thiamine, niacin, and iron unless a fortified infant food was recommended. The present study demonstrated the value of using LP to adapt NCFg for a different age group than the one for which they were designed. Our analyses suggest that to ensure dietary adequacy for 12- to 23-month olds these adaptations should include legumes, dairy products, vitamin A-rich vegetables, organ meat, and a fortified food.
Integrating genomics and proteomics data to predict drug effects using binary linear programming.
Ji, Zhiwei; Su, Jing; Liu, Chenglin; Wang, Hongyan; Huang, Deshuang; Zhou, Xiaobo
2014-01-01
The Library of Integrated Network-Based Cellular Signatures (LINCS) project aims to create a network-based understanding of biology by cataloging changes in gene expression and signal transduction that occur when cells are exposed to a variety of perturbations. It is helpful for understanding cell pathways and facilitating drug discovery. Here, we developed a novel approach to infer cell-specific pathways and identify a compound's effects using gene expression and phosphoproteomics data under treatments with different compounds. Gene expression data were employed to infer potential targets of compounds and create a generic pathway map. Binary linear programming (BLP) was then developed to optimize the generic pathway topology based on the mid-stage signaling response of phosphorylation. To demonstrate effectiveness of this approach, we built a generic pathway map for the MCF7 breast cancer cell line and inferred the cell-specific pathways by BLP. The first group of 11 compounds was utilized to optimize the generic pathways, and then 4 compounds were used to identify effects based on the inferred cell-specific pathways. Cross-validation indicated that the cell-specific pathways reliably predicted a compound's effects. Finally, we applied BLP to re-optimize the cell-specific pathways to predict the effects of 4 compounds (trichostatin A, MS-275, staurosporine, and digoxigenin) according to compound-induced topological alterations. Trichostatin A and MS-275 (both HDAC inhibitors) inhibited the downstream pathway of HDAC1 and caused cell growth arrest via activation of p53 and p21; the effects of digoxigenin were totally opposite. Staurosporine blocked the cell cycle via p53 and p21, but also promoted cell growth via activated HDAC1 and its downstream pathway. Our approach was also applied to the PC3 prostate cancer cell line, and the cross-validation analysis showed very good accuracy in predicting effects of 4 compounds. In summary, our computational model can be
Automatic identification of epileptic seizures from EEG signals using linear programming boosting.
Hassan, Ahnaf Rashik; Subasi, Abdulhamit
2016-11-01
Computerized epileptic seizure detection is essential for expediting epilepsy diagnosis and research and for assisting medical professionals. Moreover, the implementation of an epilepsy monitoring device that has low power and is portable requires a reliable and successful seizure detection scheme. In this work, the problem of automated epilepsy seizure detection using singe-channel EEG signals has been addressed. At first, segments of EEG signals are decomposed using a newly proposed signal processing scheme, namely complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN). Six spectral moments are extracted from the CEEMDAN mode functions and train and test matrices are formed afterward. These matrices are fed into the classifier to identify epileptic seizures from EEG signal segments. In this work, we implement an ensemble learning based machine learning algorithm, namely linear programming boosting (LPBoost) to perform classification. The efficacy of spectral features in the CEEMDAN domain is validated by graphical and statistical analyses. The performance of CEEMDAN is compared to those of its predecessors to further inspect its suitability. The effectiveness and the appropriateness of LPBoost are demonstrated as opposed to the commonly used classification models. Resubstitution and 10 fold cross-validation error analyses confirm the superior algorithm performance of the proposed scheme. The algorithmic performance of our epilepsy seizure identification scheme is also evaluated against state-of-the-art works in the literature. Experimental outcomes manifest that the proposed seizure detection scheme performs better than the existing works in terms of accuracy, sensitivity, specificity, and Cohen's Kappa coefficient. It can be anticipated that owing to its use of only one channel of EEG signal, the proposed method will be suitable for device implementation, eliminate the onus of clinicians for analyzing a large bulk of data manually, and
Optimizing financial effects of HIE: a multi-party linear programming approach
Brennan, Patricia Flatley; Wright, Stephen J; Robinson, Stephen M
2012-01-01
Objective To describe an analytical framework for quantifying the societal savings and financial consequences of a health information exchange (HIE), and to demonstrate its use in designing pricing policies for sustainable HIEs. Materials and methods We developed a linear programming model to (1) quantify the financial worth of HIE information to each of its participating institutions and (2) evaluate three HIE pricing policies: fixed-rate annual, charge per visit, and charge per look-up. We considered three desired outcomes of HIE-related emergency care (modeled as parameters): preventing unrequired hospitalizations, reducing duplicate tests, and avoiding emergency department (ED) visits. We applied this framework to 4639 ED encounters over a 12-month period in three large EDs in Milwaukee, Wisconsin, using Medicare/Medicaid claims data, public reports of hospital admissions, published payer mix data, and use data from a not-for-profit regional HIE. Results For this HIE, data accesses produced net financial gains for all providers and payers. Gains, due to HIE, were more significant for providers with more health maintenance organizations patients. Reducing unrequired hospitalizations and avoiding repeat ED visits were responsible for more than 70% of the savings. The results showed that fixed annual subscriptions can sustain this HIE, while ensuring financial gains to all participants. Sensitivity analysis revealed that the results were robust to uncertainties in modeling parameters. Discussion Our specific HIE pricing recommendations depend on the unique characteristics of this study population. However, our main contribution is the modeling approach, which is broadly applicable to other populations. PMID:22733978
Directory of Open Access Journals (Sweden)
Selcuk Gumus
2016-12-01
Full Text Available Farm tractor skidding is one of the common methods of timber extraction in Turkey. However, the absence of an optimal skidding plan covering the entire production area can result in time loss and negative environmental impacts. In this study, the timber extraction by farm tractors was analyzed, and a new skid trail pattern design was developed using Linear Programming (LP and Geographical Information Systems (GIS. First, a sample skidding operation was evaluated with a time study, and an optimum skidding model was generated with LP. Then, the new skidding pattern was developed by an optimum skidding model and GIS analysis. At the end of the study, the developed new skid trail pattern was implemented in the study area and tested by running a time study. Using the newly developed “Direct Skid Trail Pattern (DSTP” model, a 16.84% increase in working time performance was observed when the products were extracted by farm tractors compared to the existing practices. On the other hand, the average soil compaction value measured in the study area at depths of 0–5 cm and 5–10 cm was found to be greater in the sample area skid trails than in the control points. The average density of the skid trails was 281 m/ha, while it decreased to 187 m/ha by using the developed pattern. It was also found that 44,829 ton/ha of soil losses were prevented by using the DSTP model; therefore, environmental damages were decreased.
Energy Technology Data Exchange (ETDEWEB)
Fernandes, Marco A.R., E-mail: mfernandes@fmb.unesp.b [Universidade Estadual Paulista Julio de Mesquita Filho (UNESP), Botucatu, SP (Brazil). Fac. de Medicina. Dept. de Dermatologia e Radioterapia; Fernandes, David M.; Florentino, Helenice O. [Universidade Estadual Paulista Julio de Mesquita Filho (UNESP), Botucatu, SP (Brazil). Inst. de Biociencias
2010-07-01
The work detaches the importance of the use of mathematical tools and computer systems for optimization of the planning in radiotherapy, seeking to the distribution of dose of appropriate radiation in the white volume that provides an ideal therapeutic rate between the tumor cells and the adjacent healthy tissues, extolled in the radiotherapy protocols. Examples of target volumes mathematically modeled are analyzed with the technique of linear programming, comparing the obtained results using the Simplex algorithm with those using the algorithm of Interior Points. The System Genesis II was used for obtaining of the isodose curves for the outline and geometry of fields idealized in the computer simulations, considering the parameters of a 10 MV photons beams. Both programming methods (Simplex and Interior Points) they resulted in a distribution of integral dose in the tumor volume and allow the adaptation of the dose in the critical organs inside of the restriction limits extolled. The choice of an or other method should take into account the facility and the need of limiting the programming time. The isodose curves, obtained with the Genesis II System, illustrate that the adjacent healthy tissues to the tumor receives larger doses than those reached in the computer simulations. More coincident values can be obtained altering the weights and some factors of minimization of the objective function. The prohibitive costs of the computer planning systems, at present available for radiotherapy, it motivates the researches to look for the implementation of simpler and so effective methods for optimization of the treatment plan. (author)
Approximating the Pareto Set of Multiobjective Linear Programs via Robust Optimization
Gorissen, B.L.; den Hertog, D.
2012-01-01
Abstract: The Pareto set of a multiobjective optimization problem consists of the solutions for which one or more objectives can not be improved without deteriorating one or more other objectives. We consider problems with linear objectives and linear constraints and use Adjustable Robust
Sixth SIAM conference on applied linear algebra: Final program and abstracts. Final technical report
Energy Technology Data Exchange (ETDEWEB)
NONE
1997-12-31
Linear algebra plays a central role in mathematics and applications. The analysis and solution of problems from an amazingly wide variety of disciplines depend on the theory and computational techniques of linear algebra. In turn, the diversity of disciplines depending on linear algebra also serves to focus and shape its development. Some problems have special properties (numerical, structural) that can be exploited. Some are simply so large that conventional approaches are impractical. New computer architectures motivate new algorithms, and fresh ways to look at old ones. The pervasive nature of linear algebra in analyzing and solving problems means that people from a wide spectrum--universities, industrial and government laboratories, financial institutions, and many others--share an interest in current developments in linear algebra. This conference aims to bring them together for their mutual benefit. Abstracts of papers presented are included.
Wang, Yong; Wu, Qiao-Feng; Chen, Chen; Wu, Ling-Yun; Yan, Xian-Zhong; Yu, Shu-Guang; Zhang, Xiang-Sun; Liang, Fan-Rong
2012-01-01
Acupuncture has been practiced in China for thousands of years as part of the Traditional Chinese Medicine (TCM) and has gradually accepted in western countries as an alternative or complementary treatment. However, the underlying mechanism of acupuncture, especially whether there exists any difference between varies acupoints, remains largely unknown, which hinders its widespread use. In this study, we develop a novel Linear Programming based Feature Selection method (LPFS) to understand the mechanism of acupuncture effect, at molecular level, by revealing the metabolite biomarkers for acupuncture treatment. Specifically, we generate and investigate the high-throughput metabolic profiles of acupuncture treatment at several acupoints in human. To select the subsets of metabolites that best characterize the acupuncture effect for each meridian point, an optimization model is proposed to identify biomarkers from high-dimensional metabolic data from case and control samples. Importantly, we use nearest centroid as the prototype to simultaneously minimize the number of selected features and the leave-one-out cross validation error of classifier. We compared the performance of LPFS to several state-of-the-art methods, such as SVM recursive feature elimination (SVM-RFE) and sparse multinomial logistic regression approach (SMLR). We find that our LPFS method tends to reveal a small set of metabolites with small standard deviation and large shifts, which exactly serves our requirement for good biomarker. Biologically, several metabolite biomarkers for acupuncture treatment are revealed and serve as the candidates for further mechanism investigation. Also biomakers derived from five meridian points, Zusanli (ST36), Liangmen (ST21), Juliao (ST3), Yanglingquan (GB34), and Weizhong (BL40), are compared for their similarity and difference, which provide evidence for the specificity of acupoints. Our result demonstrates that metabolic profiling might be a promising method to
Integrating genomics and proteomics data to predict drug effects using binary linear programming.
Directory of Open Access Journals (Sweden)
Zhiwei Ji
Full Text Available The Library of Integrated Network-Based Cellular Signatures (LINCS project aims to create a network-based understanding of biology by cataloging changes in gene expression and signal transduction that occur when cells are exposed to a variety of perturbations. It is helpful for understanding cell pathways and facilitating drug discovery. Here, we developed a novel approach to infer cell-specific pathways and identify a compound's effects using gene expression and phosphoproteomics data under treatments with different compounds. Gene expression data were employed to infer potential targets of compounds and create a generic pathway map. Binary linear programming (BLP was then developed to optimize the generic pathway topology based on the mid-stage signaling response of phosphorylation. To demonstrate effectiveness of this approach, we built a generic pathway map for the MCF7 breast cancer cell line and inferred the cell-specific pathways by BLP. The first group of 11 compounds was utilized to optimize the generic pathways, and then 4 compounds were used to identify effects based on the inferred cell-specific pathways. Cross-validation indicated that the cell-specific pathways reliably predicted a compound's effects. Finally, we applied BLP to re-optimize the cell-specific pathways to predict the effects of 4 compounds (trichostatin A, MS-275, staurosporine, and digoxigenin according to compound-induced topological alterations. Trichostatin A and MS-275 (both HDAC inhibitors inhibited the downstream pathway of HDAC1 and caused cell growth arrest via activation of p53 and p21; the effects of digoxigenin were totally opposite. Staurosporine blocked the cell cycle via p53 and p21, but also promoted cell growth via activated HDAC1 and its downstream pathway. Our approach was also applied to the PC3 prostate cancer cell line, and the cross-validation analysis showed very good accuracy in predicting effects of 4 compounds. In summary, our computational
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Tsantili Ivi C
2007-03-01
Full Text Available Abstract Background The need for discovery of alternative, renewable, environmentally friendly energy sources and the development of cost-efficient, "clean" methods for their conversion into higher fuels becomes imperative. Ethanol, whose significance as fuel has dramatically increased in the last decade, can be produced from hexoses and pentoses through microbial fermentation. Importantly, plant biomass, if appropriately and effectively decomposed, is a potential inexpensive and highly renewable source of the hexose and pentose mixture. Recently, the engineered (to also catabolize pentoses anaerobic bacterium Zymomonas mobilis has been widely discussed among the most promising microorganisms for the microbial production of ethanol fuel. However, Z. mobilis genome having been fully sequenced in 2005, there is still a small number of published studies of its in vivo physiology and limited use of the metabolic engineering experimental and computational toolboxes to understand its metabolic pathway interconnectivity and regulation towards the optimization of its hexose and pentose fermentation into ethanol. Results In this paper, we reconstructed the metabolic network of the engineered Z. mobilis to a level that it could be modelled using the metabolic engineering methodologies. We then used linear programming (LP analysis and identified the Z. mobilis metabolic boundaries with respect to various biological objectives, these boundaries being determined only by Z. mobilis network's stoichiometric connectivity. This study revealed the essential for bacterial growth reactions and elucidated the association between the metabolic pathways, especially regarding main product and byproduct formation. More specifically, the study indicated that ethanol and biomass production depend directly on anaerobic respiration stoichiometry and activity. Thus, enhanced understanding and improved means for analyzing anaerobic respiration and redox potential in vivo are
Optimal control of an invasive species using a reaction-diffusion model and linear programming
Bonneau, Mathieu; Johnson, Fred A.; Smith, Brian J.; Romagosa, Christina M.; Martin, Julien; Mazzotti, Frank J.
2017-01-01
Managing an invasive species is particularly challenging as little is generally known about the species’ biological characteristics in its new habitat. In practice, removal of individuals often starts before the species is studied to provide the information that will later improve control. Therefore, the locations and the amount of control have to be determined in the face of great uncertainty about the species characteristics and with a limited amount of resources. We propose framing spatial control as a linear programming optimization problem. This formulation, paired with a discrete reaction-diffusion model, permits calculation of an optimal control strategy that minimizes the remaining number of invaders for a fixed cost or that minimizes the control cost for containment or protecting specific areas from invasion. We propose computing the optimal strategy for a range of possible model parameters, representing current uncertainty on the possible invasion scenarios. Then, a best strategy can be identified depending on the risk attitude of the decision-maker. We use this framework to study the spatial control of the Argentine black and white tegus (Salvator merianae) in South Florida. There is uncertainty about tegu demography and we considered several combinations of model parameters, exhibiting various dynamics of invasion. For a fixed one-year budget, we show that the risk-averse strategy, which optimizes the worst-case scenario of tegus’ dynamics, and the risk-neutral strategy, which optimizes the expected scenario, both concentrated control close to the point of introduction. A risk-seeking strategy, which optimizes the best-case scenario, focuses more on models where eradication of the species in a cell is possible and consists of spreading control as much as possible. For the establishment of a containment area, assuming an exponential growth we show that with current control methods it might not be possible to implement such a strategy for some of the
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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.
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.
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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.
1985-07-01
representation for the Newton search direction associated with the subproblem. In Section 3, we show a formal equivalence between the Newton search... Metod Rewriting (2.9) in terms of a vector ri defined by Dr. = -pp, we see that r. and r stisfy (I DAT)-(m) (D - . ( It follows that r. is the solution...Mountain View, California. Tomlin, J. A. and Welch, J. S. (1983). Formal optimization of some reduced linear programming problems, Math. Prog. 27, pp. 232
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...
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.
Lemmen-Gerdessen, van J.C.; Souverein, O.W.; Veer, van 't P.; Vries, de J.H.M.
2015-01-01
Objective To support the selection of food items for FFQs in such a way that the amount of information on all relevant nutrients is maximised while the food list is as short as possible. Design Selection of the most informative food items to be included in FFQs was modelled as a Mixed Integer Linear
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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.
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....
Newton, Xiaoxia A.; Llosa, Lorena
2010-01-01
Most K-12 evaluations are designed to make inferences about how a program implemented at the classroom or school level affects student learning outcomes and such inferences inherently involve hierarchical data structure. One methodological challenge for evaluators is linking program implementation factors typically measured at the classroom or…
Energy Technology Data Exchange (ETDEWEB)
Stebel, Sergio L.; Magatao, Leandro [Agencia Nacional do Petroleo, Brasilia, DF (Brazil); Neves Junior, Flavio; Arruda, L.V.R. de [Centro Federal de Educacao Tecnologica do Parana, Curitiba, PR (Brazil)
2000-07-01
In a refinery, small improvements in final product quality can lead to a significant reduction in production costs. The marine fuel (bunker) blending is an example. Bunker is achieved by blending fixed percentages of 'RASF' (asphalt residue) and 'LCO' (crack diesel fuel), from refining process with 'QUEROSENE' (kerosene) stored in tanks. Nowadays, these fixed percentages are computed from an ideal mixture realized in a laboratory. Considering that the physical/chemical component features vary in accordance with the change in crude oil inventory, this formula is not always valid, and produced bunker is often over specified or need some blending correction. In this work, a simple methodology based on linear programming techniques is develop to optimize these percentages. The resulting formula takes account the features of involved products available on a refinery database. As a result, a mixture is obtained respecting the product limit specifications and minimizing the costs. The application of the developed methodology will also allow an increase in the refinery operational flexibility as well as a reduction in the product stocks involved. (author)
Advances in Normal Conducting Accelerator Technology from the X-Band Linear Collider Program
Adolphsen, Chris
2005-01-01
In the early 1990's, groups at SLAC and KEK began dedicated development of X-band (11.4 GHz) rf technology for a next generation, TeV-scale linear collider. The choice of a relatively high frequency, four times that of the SLAC 50 GeV Linac, was motivated by the cost benefits of having lower rf energy per pulse (hence fewer rf components) and reasonable efficiencies at high gradients (hence shorter linacs). However, to realize such savings requires operation at gradients and peak powers much higher than that hitherto achieved. During the past 15 years, these challenges were met through innovations on several fronts, and resulted in a viable rf system design for a linear collider. This paper reviews these achievements, which include developments in the generation and transport of high power rf, and new insights into high gradient limitations.
Maia, Julio Daniel Carvalho; Urquiza Carvalho, Gabriel Aires; Mangueira, Carlos Peixoto; Santana, Sidney Ramos; Cabral, Lucidio Anjos Formiga; Rocha, Gerd B
2012-09-11
In this study, we present some modifications in the semiempirical quantum chemistry MOPAC2009 code that accelerate single-point energy calculations (1SCF) of medium-size (up to 2500 atoms) molecular systems using GPU coprocessors and multithreaded shared-memory CPUs. Our modifications consisted of using a combination of highly optimized linear algebra libraries for both CPU (LAPACK and BLAS from Intel MKL) and GPU (MAGMA and CUBLAS) to hasten time-consuming parts of MOPAC such as the pseudodiagonalization, full diagonalization, and density matrix assembling. We have shown that it is possible to obtain large speedups just by using CPU serial linear algebra libraries in the MOPAC code. As a special case, we show a speedup of up to 14 times for a methanol simulation box containing 2400 atoms and 4800 basis functions, with even greater gains in performance when using multithreaded CPUs (2.1 times in relation to the single-threaded CPU code using linear algebra libraries) and GPUs (3.8 times). This degree of acceleration opens new perspectives for modeling larger structures which appear in inorganic chemistry (such as zeolites and MOFs), biochemistry (such as polysaccharides, small proteins, and DNA fragments), and materials science (such as nanotubes and fullerenes). In addition, we believe that this parallel (GPU-GPU) MOPAC code will make it feasible to use semiempirical methods in lengthy molecular simulations using both hybrid QM/MM and QM/QM potentials.
A program to compute geographical positions of underwater artifact based on linear measurements
Digital Repository Service at National Institute of Oceanography (India)
Ganesan, P.
While carrying out underwater positioning in shallow waters, the Diver Archaeologists measure lengths and bearings from a base line of the well-established control network to each and every corner of the artifact. A program in Basic language...
Leroy, Jef L; García-Guerra, Armando; García, Raquel; Dominguez, Clara; Rivera, Juan; Neufeld, Lynnette M
2008-04-01
The goal of this study was to evaluate the impact of Mexico's conditional cash transfer program, Oportunidades, on the growth of children urban areas. Beneficiary families received cash transfers, a fortified food (targeted to pregnant and lactating women, children 6-23 mo, and children with low weight 2-4 y), and curative health services, among other benefits. Program benefits were conditional on preventative health care utilization and attendance of health and nutrition education sessions. We estimated the impact of the program after 2 y of operation in a panel of 432 children growth reference standards. There was no overall association between program participation and growth in children 6 to 24 mo of age. Children in intervention families younger than 6 mo of age at baseline grew 1.5 cm (P growth of infants in poor urban households.
Directory of Open Access Journals (Sweden)
Made Antara
2014-05-01
Full Text Available The objective of the research are (1 to analyze the gross margin in dryland farming systems, (2 to analyze the optimal allocation of agricultural resources in the horticulture farming and cattle system in dry land, (3 to determine the effect of changes in the prices of some agricultural commodities to resource allocation in a mixed farming system of horticulture and cattle on dryland in Kerta Village, Payangan District, Gianyar Regency. Primary data were obtained through a survey of 34 dryland farmers. Constraints optimization analysis in dryland farming systems with linear programming approach using software BLPX 88. Results of the research showed that the gross margin received an average farmer in the Kerta Village before optimization of Rp 47.783.346,00. This gross margin is derived from citrus farming area of ??0.15 ha; elephant grass area of ??0.11 ha; chili first planting season (musin tanam, MT1 covering an area of ??0.09 ha; chili third planting season (MT3 area of ??0.06 ha; tomatoes first planting season (MT1 area 0.07 ha; tomatoes second planting season (MT2 area of ??0.05 ha; tomatoes third planting season (MT3 area of ??0.11 ha; chicory second planting season (MT2 area of ??0.03 ha; beans first planting season (MT1 area of ??0.02 ha; beans second planting season (MT2 area of ??0.14 ha; corn first planting season (MT1 area of ??0.09 ha ; corn second planting season (MT2 area of ??0.05 ha; corn third planting season (MT3 area of ??0.03 ha; sweet potatoes second planting season (MT2 area 0.04 ha; sweet potatoes third planting season (MT3 area 0.07 ha; peanuts first planting season (MT1 area 0.11 ha; peanut third planting season (MT3 area 0, 10 ha, and maintains five head of cattle. Optimal dryland farming systems in the Kerta Village, generating maximum gross margin of Rp 49.404.260,00 increased by 3.39% compared to gross revenue of farmers before optimal are Rp 47,783,346.00. Gross margin was obtained from a combination of
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.
Linear Program Relaxation of Sparse Nonnegative Recovery in Compressive Sensing Microarrays
Directory of Open Access Journals (Sweden)
Linxia Qin
2012-01-01
Full Text Available Compressive sensing microarrays (CSM are DNA-based sensors that operate using group testing and compressive sensing principles. Mathematically, one can cast the CSM as sparse nonnegative recovery (SNR which is to find the sparsest solutions subjected to an underdetermined system of linear equations and nonnegative restriction. In this paper, we discuss the l1 relaxation of the SNR. By defining nonnegative restricted isometry/orthogonality constants, we give a nonnegative restricted property condition which guarantees that the SNR and the l1 relaxation share the common unique solution. Besides, we show that any solution to the SNR must be one of the extreme points of the underlying feasible set.
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Samir Dey
2015-07-01
Full Text Available This paper proposes a new multi-objective intuitionistic fuzzy goal programming approach to solve a multi-objective nonlinear programming problem in context of a structural design. Here we describe some basic properties of intuitionistic fuzzy optimization. We have considered a multi-objective structural optimization problem with several mutually conflicting objectives. The design objective is to minimize weight of the structure and minimize the vertical deflection at loading point of a statistically loaded three-bar planar truss subjected to stress constraints on each of the truss members. This approach is used to solve the above structural optimization model based on arithmetic mean and compare with the solution by intuitionistic fuzzy goal programming approach. A numerical solution is given to illustrate our approach.
Two-stage stochastic linear programming by a series of Monte-Carlo estimators
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Kęstutis Žilinskas
2015-07-01
Full Text Available In this paper a stochastic adaptive method has been developed to solve stochastic linear problems by a finite sequence of Monte-Carlo sampling estimators. The method is based on the adaptive regulation of the size of Monte-Carlo samples and a statistical termination procedure taking into consideration statistical modelling accuracy. Our approach distinguishes itself by the treatment of accuracy of the solution in a statistical manner, testing the hypothesis of optimality according to statistical criteria, and estimating confidence intervals of the objective and constraint functions. To avoid “jamming” or “zigzagging” solving a constraint problem we implement the ε–feasible direction approach. The proposed adjustment of a sample size, when it is taken inversely proportional to the square of the norm of the Monte-Carlo estimate of the gradient, guarantees convergence a. s. at a linear rate. The numerical study and examples in practice corroborate theoretical conclusions and show that the developed procedures make it possible to solve stochastic problems with sufficient accuracy by the means of an acceptable size of computations.DOI: 10.15181/csat.v2i2.891
Canepa, Edward S.
2013-01-01
Traffic sensing systems rely more and more on user generated (insecure) data, which can pose a security risk whenever the data is used for traffic flow control. In this article, we propose a new formulation for detecting malicious data injection in traffic flow monitoring systems by using the underlying traffic flow model. The state of traffic is modeled by the Lighthill-Whitham- Richards traffic flow model, which is a first order scalar conservation law with concave flux function. Given a set of traffic flow data, we show that the constraints resulting from this partial differential equation are mixed integer linear inequalities for some decision variable. We use this fact to pose the problem of detecting spoofing cyber-attacks in probe-based traffic flow information systems as mixed integer linear feasibility problem. The resulting framework can be used to detect spoofing attacks in real time, or to evaluate the worst-case effects of an attack offline. A numerical implementation is performed on a cyber-attack scenario involving experimental data from the Mobile Century experiment and the Mobile Millennium system currently operational in Northern California. © 2013 IEEE.
Canepa, Edward S.
2013-09-01
Traffic sensing systems rely more and more on user generated (insecure) data, which can pose a security risk whenever the data is used for traffic flow control. In this article, we propose a new formulation for detecting malicious data injection in traffic flow monitoring systems by using the underlying traffic flow model. The state of traffic is modeled by the Lighthill- Whitham-Richards traffic flow model, which is a first order scalar conservation law with concave flux function. Given a set of traffic flow data generated by multiple sensors of different types, we show that the constraints resulting from this partial differential equation are mixed integer linear inequalities for a specific decision variable. We use this fact to pose the problem of detecting spoofing cyber attacks in probe-based traffic flow information systems as mixed integer linear feasibility problem. The resulting framework can be used to detect spoofing attacks in real time, or to evaluate the worst-case effects of an attack offliine. A numerical implementation is performed on a cyber attack scenario involving experimental data from the Mobile Century experiment and the Mobile Millennium system currently operational in Northern California. © American Institute of Mathematical Sciences.
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.
Directory of Open Access Journals (Sweden)
A. Kandil
2016-10-01
Full Text Available A multiset is a collection of objects in which repetition of elements is essential. This paper is an attempt to explore the theoretical aspects of multiset by extending the notions of compact, proximity relation and proximal neighborhood to the multiset context. Examples of new multiset topologies, open multiset cover, compact multiset and many identities involving the concept of multiset have been introduced. Further, an integral examples of multiset proximity relations are obtained. A multiset topology induced by a multiset proximity relation on a multiset M has been presented. Also the concept of multiset δ- neighborhood in the multiset proximity space which furnishes an alternative approach to the study of multiset proximity spaces has been mentioned. Finally, some results on this new approach have been obtained and one of the most important results is: every T4- multiset space is semi-compatible with multiset proximity relation δ on M (Theorem 5.10.
Safikhani, Zhaleh; Sadeghi, Mehdi; Pezeshk, Hamid; Eslahchi, Changiz
2013-01-01
Recent advances in the sequencing technologies have provided a handful of RNA-seq datasets for transcriptome analysis. However, reconstruction of full-length isoforms and estimation of the expression level of transcripts with a low cost are challenging tasks. We propose a novel de novo method named SSP that incorporates interval integer linear programming to resolve alternatively spliced isoforms and reconstruct the whole transcriptome from short reads. Experimental results show that SSP is fast and precise in determining different alternatively spliced isoforms along with the estimation of reconstructed transcript abundances. The SSP software package is available at http://www.bioinf.cs.ipm.ir/software/ssp. © 2013.
Robust Adaptive Dynamic Programming of Two-Player Zero-Sum Games for Continuous-Time Linear Systems.
Fu, Yue; Fu, Jun; Chai, Tianyou
2015-12-01
In this brief, an online robust adaptive dynamic programming algorithm is proposed for two-player zero-sum games of continuous-time unknown linear systems with matched uncertainties, which are functions of system outputs and states of a completely unknown exosystem. The online algorithm is developed using the policy iteration (PI) scheme with only one iteration loop. A new analytical method is proposed for convergence proof of the PI scheme. The sufficient conditions are given to guarantee globally asymptotic stability and suboptimal property of the closed-loop system. Simulation studies are conducted to illustrate the effectiveness of the proposed method.
Mathur, Rinku; Adlakha, Neeru
2014-06-01
Phylogenetic trees give the information about the vertical relationships of ancestors and descendants but phylogenetic networks are used to visualize the horizontal relationships among the different organisms. In order to predict reticulate events there is a need to construct phylogenetic networks. Here, a Linear Programming (LP) model has been developed for the construction of phylogenetic network. The model is validated by using data sets of chloroplast of 16S rRNA sequences of photosynthetic organisms and Influenza A/H5N1 viruses. Results obtained are in agreement with those obtained by earlier researchers.
Lorenzo-Seva, Urbano; Ferrando, Pere J
2011-03-01
We provide an SPSS program that implements currently recommended techniques and recent developments for selecting variables in multiple linear regression analysis via the relative importance of predictors. The approach consists of: (1) optimally splitting the data for cross-validation, (2) selecting the final set of predictors to be retained in the equation regression, and (3) assessing the behavior of the chosen model using standard indices and procedures. The SPSS syntax, a short manual, and data files related to this article are available as supplemental materials from brm.psychonomic-journals.org/content/supplemental.
DEFF Research Database (Denmark)
Parlesak, A.; Tetens, Inge; Dejgård Jensen, Jørgen
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...... facilitates the generation of low-cost food baskets that are nutritionally adequate, health promoting, and culturally acceptable....
Serang, Oliver
2012-01-01
Linear programming (LP) problems are commonly used in analysis and resource allocation, frequently surfacing as approximations to more difficult problems. Existing approaches to LP have been dominated by a small group of methods, and randomized algorithms have not enjoyed popularity in practice. This paper introduces a novel randomized method of solving LP problems by moving along the facets and within the interior of the polytope along rays randomly sampled from the polyhedral cones defined by the bounding constraints. This conic sampling method is then applied to randomly sampled LPs, and its runtime performance is shown to compare favorably to the simplex and primal affine-scaling algorithms, especially on polytopes with certain characteristics. The conic sampling method is then adapted and applied to solve a certain quadratic program, which compute a projection onto a polytope; the proposed method is shown to outperform the proprietary software Mathematica on large, sparse QP problems constructed from mass spectometry-based proteomics.
Ellis, J. H.; McBean, E. A.; Farquhar, G. J.
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 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 (LPUU), Chance-Constrained Programming (CCP) and Stochastic Linear Programming (SLP). 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. Complete colinearity assumes complete dependence between transfer coefficients. Complete noncolinearity assumes complete independence. 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.
Application of fuzzy goal programming approach to multi-objective linear fractional inventory model
Dutta, D.; Kumar, Pavan
2015-09-01
In this paper, we propose a model and solution approach for a multi-item inventory problem without shortages. The proposed model is formulated as a fractional multi-objective optimisation problem along with three constraints: budget constraint, space constraint and budgetary constraint on ordering cost of each item. The proposed inventory model becomes a multiple criteria decision-making (MCDM) problem in fuzzy environment. This model is solved by multi-objective fuzzy goal programming (MOFGP) approach. A numerical example is given to illustrate the proposed model.
Knapp, Bettina; Kaderali, Lars
2013-01-01
Perturbation experiments for example using RNA interference (RNAi) offer an attractive way to elucidate gene function in a high throughput fashion. The placement of hit genes in their functional context and the inference of underlying networks from such data, however, are challenging tasks. One of the problems in network inference is the exponential number of possible network topologies for a given number of genes. Here, we introduce a novel mathematical approach to address this question. We formulate network inference as a linear optimization problem, which can be solved efficiently even for large-scale systems. We use simulated data to evaluate our approach, and show improved performance in particular on larger networks over state-of-the art methods. We achieve increased sensitivity and specificity, as well as a significant reduction in computing time. Furthermore, we show superior performance on noisy data. We then apply our approach to study the intracellular signaling of human primary nave CD4(+) T-cells, as well as ErbB signaling in trastuzumab resistant breast cancer cells. In both cases, our approach recovers known interactions and points to additional relevant processes. In ErbB signaling, our results predict an important role of negative and positive feedback in controlling the cell cycle progression.
Directory of Open Access Journals (Sweden)
Bettina Knapp
Full Text Available Perturbation experiments for example using RNA interference (RNAi offer an attractive way to elucidate gene function in a high throughput fashion. The placement of hit genes in their functional context and the inference of underlying networks from such data, however, are challenging tasks. One of the problems in network inference is the exponential number of possible network topologies for a given number of genes. Here, we introduce a novel mathematical approach to address this question. We formulate network inference as a linear optimization problem, which can be solved efficiently even for large-scale systems. We use simulated data to evaluate our approach, and show improved performance in particular on larger networks over state-of-the art methods. We achieve increased sensitivity and specificity, as well as a significant reduction in computing time. Furthermore, we show superior performance on noisy data. We then apply our approach to study the intracellular signaling of human primary nave CD4(+ T-cells, as well as ErbB signaling in trastuzumab resistant breast cancer cells. In both cases, our approach recovers known interactions and points to additional relevant processes. In ErbB signaling, our results predict an important role of negative and positive feedback in controlling the cell cycle progression.
Directory of Open Access Journals (Sweden)
Xiaoling Zhang
2013-01-01
Full Text Available The conflict of water environment protection and economic development has brought severe water pollution and restricted the sustainable development in the watershed. A risk explicit interval linear programming (REILP method was used to solve integrated watershed environmental-economic optimization problem. Interval linear programming (ILP and REILP models for uncertainty-based environmental economic optimization at the watershed scale were developed for the management of Lake Fuxian watershed, China. Scenario analysis was introduced into model solution process to ensure the practicality and operability of optimization schemes. Decision makers’ preferences for risk levels can be expressed through inputting different discrete aspiration level values into the REILP model in three periods under two scenarios. Through balancing the optimal system returns and corresponding system risks, decision makers can develop an efficient industrial restructuring scheme based directly on the window of “low risk and high return efficiency” in the trade-off curve. The representative schemes at the turning points of two scenarios were interpreted and compared to identify a preferable planning alternative, which has the relatively low risks and nearly maximum benefits. This study provides new insights and proposes a tool, which was REILP, for decision makers to develop an effectively environmental economic optimization scheme in integrated watershed management.
Zhang, Xiaoling; Huang, Kai; Zou, Rui; Liu, Yong; Yu, Yajuan
2013-01-01
The conflict of water environment protection and economic development has brought severe water pollution and restricted the sustainable development in the watershed. A risk explicit interval linear programming (REILP) method was used to solve integrated watershed environmental-economic optimization problem. Interval linear programming (ILP) and REILP models for uncertainty-based environmental economic optimization at the watershed scale were developed for the management of Lake Fuxian watershed, China. Scenario analysis was introduced into model solution process to ensure the practicality and operability of optimization schemes. Decision makers' preferences for risk levels can be expressed through inputting different discrete aspiration level values into the REILP model in three periods under two scenarios. Through balancing the optimal system returns and corresponding system risks, decision makers can develop an efficient industrial restructuring scheme based directly on the window of "low risk and high return efficiency" in the trade-off curve. The representative schemes at the turning points of two scenarios were interpreted and compared to identify a preferable planning alternative, which has the relatively low risks and nearly maximum benefits. This study provides new insights and proposes a tool, which was REILP, for decision makers to develop an effectively environmental economic optimization scheme in integrated watershed management.
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.
National Research Council Canada - National Science Library
Wikil Kwak; Susan Eldridge; Yong Shi; Gang Kou
2009-01-01
Our study proposes a multiple criteria linear programming (MCLP) and other data mining methods to predict material weaknesses in a firm's internal control system after the Sarbanes-Oxley Act (SOX) using 2003-2004 U.S. data...
Federal Laboratory Consortium — The Proximal Probes Facility consists of laboratories for microscopy, spectroscopy, and probing of nanostructured materials and their functional properties. At the...
A mixed integer linear programming model applied in barge planning for Omya
Directory of Open Access Journals (Sweden)
David Bredström
2015-12-01
Full Text Available This article presents a mathematical model for barge transport planning on the river Rhine, which is part of a decision support system (DSS recently taken into use by the Swiss company Omya. The system is operated by Omya’s regional office in Cologne, Germany, responsible for distribution planning at the regional distribution center (RDC in Moerdijk, the Netherlands. The distribution planning is a vital part of supply chain management of Omya’s production of Norwegian high quality calcium carbonate slurry, supplied to European paper manufacturers. The DSS operates within a vendor managed inventory (VMI setting, where the customer inventories are monitored by Omya, who decides upon the refilling days and quantities delivered by barges. The barge planning problem falls into the category of inventory routing problems (IRP and is further characterized with multiple products, heterogeneous fleet with availability restrictions (the fleet is owned by third party, vehicle compartments, dependency of barge capacity on water-level, multiple customer visits, bounded customer inventories and rolling planning horizon. There are additional modelling details which had to be considered to make it possible to employ the model in practice at a sufficient level of detail. To the best of our knowledge, we have not been able to find similar models covering all these aspects in barge planning. This article presents the developed mixed-integer programming model and discusses practical experience with its solution. Briefly, it also puts the model into the context of the entire business case of value chain optimization in Omya.
Directory of Open Access Journals (Sweden)
Jaka ŽGAJNAR
2015-12-01
Full Text Available In this contribution, the economics of an equestrian centre, which in addition to a variety of riding school activities also includes breeding and livery, are analysed. We consider the conditions for a hypothetical holding operating in central Slovenia. Methods of mathematical programming are applied in order to attempt to optimise the holding’s activities. Their use may in the given situation facilitate the evaluation of development prospects from different perspectives and indicate the opportunities of increasing value-added. On the basis of maximizing the gross margin, we try to address the various questions and challenges that arise in managing and planning for such an equestrian centre. The obtained results indicate that breeding is unfavourable in the given price-cost ratio, both for the renewal of the working horses herd and for sale. This reflects the current adverse situation in the field of horse breeding. Livery is an important activity on such holdings and through opportunity perspective provides an optimal set of activities. Activities of the riding school for children are interesting in terms of income diversification, as well as an additional source of revenue. A riding school with one riding instructor and an indoor arena needs 4.6 horses in order to cover the costs of full-time employment.
Okubo, Hitomi; Sasaki, Satoshi; Murakami, Kentaro; Yokoyama, Tetsuji; Hirota, Naoko; Notsu, Akiko; Fukui, Mitsuru; Date, Chigusa
2015-06-06
Simultaneous dietary achievement of a full set of nutritional recommendations is difficult. Diet optimization model using linear programming is a useful mathematical means of translating nutrient-based recommendations into realistic nutritionally-optimal food combinations incorporating local and culture-specific foods. We used this approach to explore optimal food intake patterns that meet the nutrient recommendations of the Dietary Reference Intakes (DRIs) while incorporating typical Japanese food selections. As observed intake values, we used the food and nutrient intake data of 92 women aged 31-69 years and 82 men aged 32-69 years living in three regions of Japan. Dietary data were collected with semi-weighed dietary record on four non-consecutive days in each season of the year (16 days total). The linear programming models were constructed to minimize the differences between observed and optimized food intake patterns while also meeting the DRIs for a set of 28 nutrients, setting energy equal to estimated requirements, and not exceeding typical quantities of each food consumed by each age (30-49 or 50-69 years) and gender group. We successfully developed mathematically optimized food intake patterns that met the DRIs for all 28 nutrients studied in each sex and age group. Achieving nutritional goals required minor modifications of existing diets in older groups, particularly women, while major modifications were required to increase intake of fruit and vegetables in younger groups of both sexes. Across all sex and age groups, optimized food intake patterns demanded greatly increased intake of whole grains and reduced-fat dairy products in place of intake of refined grains and full-fat dairy products. Salt intake goals were the most difficult to achieve, requiring marked reduction of salt-containing seasoning (65-80%) in all sex and age groups. Using a linear programming model, we identified optimal food intake patterns providing practical food choices and
Milk and linear growth: programming of the igf-I axis and implication for health in adulthood.
Martin, Richard M; Holly, Jeff M P; Gunnell, David
2011-01-01
There is increasing awareness that childhood circumstances influence disease risk in adulthood. As well as being strongly influenced by genes/genetic factors, stature acts as a marker for early-life exposures, such as diet, and is associated with risk of several chronic diseases in adulthood. Stature is also a marker for levels of insulin-like growth factor (IGF)-I in childhood. Levels of IGF-I are nutritionally regulated and are therefore modifiable. Milk intake in childhood and in adulthood is positively associated with higher levels of circulating IGF-I and, in children, higher circulating IGF-I promotes linear growth. Studies conducted by our team and others, however, indicate that the effect of milk is complicated because consumption in childhood appears to have long-term, programming effects which are opposite to the immediate effects of consuming milk. Specifically, studies suggest that the long-term effect of higher levels of milk intake in early childhood is opposite to the expected short-term effect, because milk intake in early-life is inversely associated with IGF-I levels throughout adult life. We hypothesize that this long-term programming effect is via a resetting of pituitary control in response to raised levels of IGF-I in childhood. Such a programming effect of milk intake in early life could potentially have implications for cancer and ischemic heart disease risk many years later. Copyright © 2011 S. Karger AG, Basel.
Houts, R. C.; Burlage, D. W.
1972-01-01
A time domain technique is developed to design finite-duration impulse response digital filters using linear programming. Two related applications of this technique in data transmission systems are considered. The first is the design of pulse shaping digital filters to generate or detect signaling waveforms transmitted over bandlimited channels that are assumed to have ideal low pass or bandpass characteristics. The second is the design of digital filters to be used as preset equalizers in cascade with channels that have known impulse response characteristics. Example designs are presented which illustrate that excellent waveforms can be generated with frequency-sampling filters and the ease with which digital transversal filters can be designed for preset equalization.
Catanzaro, Daniele; Shackney, Stanley E; Schaffer, Alejandro A; Schwartz, Russell
2016-01-01
Ductal Carcinoma In Situ (DCIS) is a precursor lesion of Invasive Ductal Carcinoma (IDC) of the breast. Investigating its temporal progression could provide fundamental new insights for the development of better diagnostic tools to predict which cases of DCIS will progress to IDC. We investigate the problem of reconstructing a plausible progression from single-cell sampled data of an individual with synchronous DCIS and IDC. Specifically, by using a number of assumptions derived from the observation of cellular atypia occurring in IDC, we design a possible predictive model using integer linear programming (ILP). Computational experiments carried out on a preexisting data set of 13 patients with simultaneous DCIS and IDC show that the corresponding predicted progression models are classifiable into categories having specific evolutionary characteristics. The approach provides new insights into mechanisms of clonal progression in breast cancers and helps illustrate the power of the ILP approach for similar problems in reconstructing tumor evolution scenarios under complex sets of constraints.
Directory of Open Access Journals (Sweden)
H Kazemipoor
2012-04-01
Full Text Available A multi-skilled project scheduling problem (MSPSP has been generally presented to schedule a project with staff members as resources. Each activity in project network requires different skills and also staff members have different skills, too. This causes the MSPSP becomes a special type of a multi-mode resource-constrained project scheduling problem (MM-RCPSP with a huge number of modes. Given the importance of this issue, in this paper, a mixed integer linear programming for the MSPSP is presented. Due to the complexity of the problem, a meta-heuristic algorithm is proposed in order to find near optimal solutions. To validate performance of the algorithm, results are compared against exact solutions solved by the LINGO solver. The results are promising and show that optimal or near-optimal solutions are derived for small instances and good solutions for larger instances in reasonable time.
DEFF Research Database (Denmark)
Stolpe, Mathias
2004-01-01
linear or as convex quadratic mixed 0-1 programs. The reformulations provide new insight into the structure of the problems and may provide a foundation for the development of new methods and heuristics for solving topology optimization problems. The applications considered are maximum stiffness design......We consider equivalent reformulations of nonlinear mixed 0-1 optimization problems arising from a broad range of recent applications of topology optimization for the design of continuum structures and composite materials. It is shown that the considered problems may equivalently be cast as either...... of structures subjected to either static or periodic loads, design of composite materials with prescribed homogenized properties using the inverse homogenization approach, optimization of fluids in Stokes flow, design of band gap structures, and multi-physics problems involving coupled steady-state heat...
DEFF Research Database (Denmark)
Stolpe, Mathias
2007-01-01
linear or convex quadratic mixed 0–1 programs. The reformulations provide new insight into the structure of the problems and may provide a foundation for the development of new methods and heuristics for solving topology optimization problems. The applications considered are maximum stiffness design......We consider equivalent reformulations of nonlinear mixed 0–1 optimization problems arising from a broad range of recent applications of topology optimization for the design of continuum structures and composite materials. We show that the considered problems can equivalently be cast as either...... of structures subjected to static or periodic loads, design of composite materials with prescribed homogenized properties using the inverse homogenization approach, optimization of fluids in Stokes flow, design of band gap structures, and multi-physics problems involving coupled steady-state heat conduction...
Directory of Open Access Journals (Sweden)
Mbarek Elbounjimi
2015-11-01
Full Text Available Closed-loop supply chain network design is a critical issue due to its impact on both economic and environmental performances of the supply chain. In this paper, we address the problem of designing a multi-echelon, multi-product and capacitated closed-loop supply chain network. First, a mixed-integer linear programming formulation is developed to maximize the total profit. The main contribution of the proposed model is addressing two economic viability issues of closed-loop supply chain. The first issue is the collection of sufficient quantity of end-of-life products are assured by retailers against an acquisition price. The second issue is exploiting the benefits of colocation of forward facilities and reverse facilities. The presented model is solved by LINGO for some test problems. Computational results and sensitivity analysis are conducted to show the performance of the proposed model.
Energy Technology Data Exchange (ETDEWEB)
Morais, Hugo; Faria, Pedro; Vale, Zita A.; Khodr, H.M. [GECAD - Knowledge Engineering and Decision-Support, Research Center of the Electrical Engineering, Polytechnic Institute of Porto (ISEP/IPP) (Portugal); Kadar, Peter [Budapest University of Technology and Economics, Muegyetem rkp. 3-9, H-1111 Budapest (Hungary)
2010-01-15
In the energy management of the isolated operation of small power system, the economic scheduling of the generation units is a crucial problem. Applying right timing can maximize the performance of the supply. The optimal operation of a wind turbine, a solar unit, a fuel cell and a storage battery is searched by a mixed-integer linear programming implemented in General Algebraic Modeling Systems (GAMS). A Virtual Power Producer (VPP) can optimal operate the generation units, assured the good functioning of equipment, including the maintenance, operation cost and the generation measurement and control. A central control at system allows a VPP to manage the optimal generation and their load control. The application of methodology to a real case study in Budapest Tech, demonstrates the effectiveness of this method to solve the optimal isolated dispatch of the DC micro-grid renewable energy park. The problem has been converged in 0.09 s and 30 iterations. (author)
Energy Technology Data Exchange (ETDEWEB)
Oh, S.-D. [Hyosung Corp., Seoul (Korea, Republic of)]. E-mail: ohsidk@hyosung.com; Kwak, H.-Y. [Chung-Ang Univ., Mechanical Engineering Dept., Seoul (Korea, Republic of)]. E-mail: kwakhy@cau.ac.kr
2005-07-01
An optimal planning for gas turbine cogeneration system has been studied. The planning problem considered in this study is to determine the optimal configuration of the system equipments and optimal operational policy of the system when the annual energy demands of electric power, heat and cooling are given a priori. The main benefit of the optimal planning is to minimize operational costs and to save energy by efficient energy utilization. A mixed-integer linear programming and the branch and bound algorithm have been adopted to obtain the optimal solution. Both the optimal configuration of the system equipments and the optimal operation policy has been obtained based on annual cost method. The planning method employed here may be applied to the planning problem of the cogeneration plant to any specific building or hotel. (author)
Wood, Scott T; Dean, Brian C; Dean, Delphine
2013-04-01
This paper presents a novel computer vision algorithm to analyze 3D stacks of confocal images of fluorescently stained single cells. The goal of the algorithm is to create representative in silico model structures that can be imported into finite element analysis software for mechanical characterization. Segmentation of cell and nucleus boundaries is accomplished via standard thresholding methods. Using novel linear programming methods, a representative actin stress fiber network is generated by computing a linear superposition of fibers having minimum discrepancy compared with an experimental 3D confocal image. Qualitative validation is performed through analysis of seven 3D confocal image stacks of adherent vascular smooth muscle cells (VSMCs) grown in 2D culture. The presented method is able to automatically generate 3D geometries of the cell's boundary, nucleus, and representative F-actin network based on standard cell microscopy data. These geometries can be used for direct importation and implementation in structural finite element models for analysis of the mechanics of a single cell to potentially speed discoveries in the fields of regenerative medicine, mechanobiology, and drug discovery. Copyright © 2012 Elsevier B.V. All rights reserved.
Directory of Open Access Journals (Sweden)
M. Pattnaik
2013-08-01
Full Text Available In this paper the concept of fuzzy Non-Linear Programming Technique is applied to solve an economic order quantity (EOQ model under restricted space. Since various types of uncertainties and imprecision are inherent in real inventory problems they are classically modeled using the approaches from the probability theory. However, there are uncertainties that cannot be appropriately treated by usual probabilistic models. The questions how to define inventory optimization tasks in such environment how to interpret optimal solutions arise. This paper allows the modification of the Single item EOQ model in presence of fuzzy decision making process where demand is related to the unit price and the setup cost varies with the quantity produced/Purchased. This paper considers the modification of objective function and storage area in the presence of imprecisely estimated parameters. The model is developed for the problem by employing different modeling approaches over an infinite planning horizon. It incorporates all concepts of a fuzzy arithmetic approach, the quantity ordered and the demand per unit compares both fuzzy non linear and other models. Investigation of the properties of an optimal solution allows developing an algorithm whose validity is illustrated through an example problem and ugh MATLAB (R2009a version software, the two and three dimensional diagrams are represented to the application. Sensitivity analysis of the optimal solution is also studied with respect to changes in different parameter values and to draw managerial insights of the decision problem.
Jamali, A.; Khaleghi, E.; Gholaminezhad, I.; Nariman-zadeh, N.
2016-05-01
In this paper, a new multi-objective genetic programming (GP) with a diversity preserving mechanism and a real number alteration operator is presented and successfully used for Pareto optimal modelling of some complex non-linear systems using some input-output data. In this study, two different input-output data-sets of a non-linear mathematical model and of an explosive cutting process are considered separately in three-objective optimisation processes. The pertinent conflicting objective functions that have been considered for such Pareto optimisations are namely, training error (TE), prediction error (PE), and the length of tree (complexity of the network) (TL) of the GP models. Such three-objective optimisation implementations leads to some non-dominated choices of GP-type models for both cases representing the trade-offs among those objective functions. Therefore, optimal Pareto fronts of such GP models exhibit the trade-off among the corresponding conflicting objectives and, thus, provide different non-dominated optimal choices of GP-type models. Moreover, the results show that no significant optimality in TE and PE may occur when the TL of the corresponding GP model exceeds some values.
Dos Santos, Quenia; Sichieri, Rosely; Darmon, Nicole; Maillot, Matthieu; Verly-Junior, Eliseu
2018-01-18
To identify optimal food choices that meet nutritional recommendations to reduce prevalence of inadequate nutrient intakes. Linear programming was used to obtain an optimized diet with sixty-eight foods with the least difference from the observed population mean dietary intake while meeting a set of nutritional goals that included reduction in the prevalence of inadequate nutrient intakes to ≤20 %. Brazil. Participants (men and women, n 25 324) aged 20 years or more from the first National Dietary Survey (NDS) 2008-2009. Feasible solution to the model was not found when all constraints were imposed; infeasible nutrients were Ca, vitamins D and E, Mg, Zn, fibre, linolenic acid, monounsaturated fat and Na. Feasible solution was obtained after relaxing the nutritional constraints for these limiting nutrients by including a deviation variable in the model. Estimated prevalence of nutrient inadequacy was reduced by 60-70 % for most nutrients, and mean saturated and trans-fat decreased in the optimized diet meeting the model constraints. Optimized diet was characterized by increases especially in fruits (+92 g), beans (+64 g), vegetables (+43 g), milk (+12 g), fish and seafood (+15 g) and whole cereals (+14 g), and reductions of sugar-sweetened beverages (-90 g), rice (-63 g), snacks (-14 g), red meat (-13 g) and processed meat (-9·7 g). Linear programming is a unique tool to identify which changes in the current diet can increase nutrient intake and place the population at lower risk of nutrient inadequacy. Reaching nutritional adequacy for all nutrients would require major dietary changes in the Brazilian diet.
Directory of Open Access Journals (Sweden)
Leif E. Peterson
1997-11-01
Full Text Available A computer program for multifactor relative risks, confidence limits, and tests of hypotheses using regression coefficients and a variance-covariance matrix obtained from a previous additive or multiplicative regression analysis is described in detail. Data used by the program can be stored and input from an external disk-file or entered via the keyboard. The output contains a list of the input data, point estimates of single or joint effects, confidence intervals and tests of hypotheses based on a minimum modified chi-square statistic. Availability of the program is also discussed.
Directory of Open Access Journals (Sweden)
Mochammad Chaerul
2013-07-01
Full Text Available ABSTRAK Berbagai macam pelayanan perawatan kesehatan yang disediakan oleh rumah sakit akan berpotensi menghasilkan limbah medis. Walaupun sebagian besar limbah rumah sakit dapat dikelompokkan sebagai limbah yang tidak berbahaya yang memiliki sifat yang sama dengan sampah rumah tangga dan dapat dibuang ke tempat penimbunan sampah, sebagian kecil dari limbah medis harus dikelola dengan tepat untuk meminimasi resiko terhadap kesehatan masyarakat. Model pengelolaan limbah medis yang dikembangkan ditujukan untuk meminimasi resiko terhadap fasilitas umum dan komersial seperti fasilitas ibadah, bank, perkantoran, restoran, hotel, stasiun pengisian bahan bakar, fasilitas pendidikan, mall dan pusat perbelanjaan, taman dan pusat olahraga/kebugaran, akibat pengangkutan limbah medis dan abu hasil pengolahannya. Tingkat resiko dari setiap fasilitas di atas ditentukan menggunakan metode Analytical Hierarchy Process (AHP. Permasalahan diselesaikan dengan mengaplikasikan linear programming menggunakan software optimimasi LINGO®. Output model berupa optimasi alokasi limbah medis dari setiap rumah sakit ke fasilitas pengolahan dan alokasi abu dari fasilitas pengolahan ke tempat penimbunan akhir. Hasil model memperlihatkan bahwa rute terpendek tidak menghasilkan total resiko terkecil karena dipengaruhi oleh jumlah dan tingkat resiko dari setiap fasilitas yang dilalui oleh kemdaraan pengangkut limbah medis dan abu. Perbedaan fasilitas yang berada di sekitar pengolahan limbah medis juga akan menghasilkan total resiko yang berbeda. ABSTRACT A broad range of healthcare services provided by hospital may generate medical waste. Although a large percentage of hospital waste is classified as general waste, which has similar nature as that of municipal solid waste and, therefore, could be disposed in municipal landfill, a small portion of medical waste has to be managed in a proper manner to minimize risk to public health. A medical waste management model is proposed in
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.
Diffendorfer, James E.; Richards, Paul M.; Dalrymple, George H.; DeAngelis, Donald L.
2001-01-01
We present the application of Linear Programming for estimating biomass fluxes in ecosystem and food web models. We use the herpetological assemblage of the Everglades as an example. We developed food web structures for three common Everglades freshwater habitat types: marsh, prairie, and upland. We obtained a first estimate of the fluxes using field data, literature estimates, and professional judgment. Linear programming was used to obtain a consistent and better estimate of the set of fluxes, while maintaining mass balance and minimizing deviations from point estimates. The results support the view that the Everglades is a spatially heterogeneous system, with changing patterns of energy flux, species composition, and biomasses across the habitat types. We show that a food web/ecosystem perspective, combined with Linear Programming, is a robust method for describing food webs and ecosystems that requires minimal data, produces useful post-solution analyses, and generates hypotheses regarding the structure of energy flow in the system.
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Dongyul Lee
2014-01-01
Full Text Available The advancement in wideband wireless network supports real time services such as IPTV and live video streaming. However, because of the sharing nature of the wireless medium, efficient resource allocation has been studied to achieve a high level of acceptability and proliferation of wireless multimedia. Scalable video coding (SVC with adaptive modulation and coding (AMC provides an excellent solution for wireless video streaming. By assigning different modulation and coding schemes (MCSs to video layers, SVC can provide good video quality to users in good channel conditions and also basic video quality to users in bad channel conditions. For optimal resource allocation, a key issue in applying SVC in the wireless multicast service is how to assign MCSs and the time resources to each SVC layer in the heterogeneous channel condition. We formulate this problem with integer linear programming (ILP and provide numerical results to show the performance under 802.16 m environment. The result shows that our methodology enhances the overall system throughput compared to an existing algorithm.
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Edwin Corrigan
2016-06-01
Full Text Available Ecosystem service provisions are becoming more frequently used to assess land-use related conflicts in recent decades. This study investigates the current spatial and research information available to quantify ecosystem services relative to forest land-use planning in Ireland. A model is developed using the linear-programming method in Remsoft’s Woodstock platform. This model is applied to two case study areas in Ireland: Western Peatlands and Newmarket. Each case study area was chosen to assess a unique issue in the Irish and European context on the provision of ecosystem services. Western Peatlands was chosen to assess the effects of forest and alternative land-use options and Newmarket was chosen to investigate the effect of afforestation. The synergies and trade-offs of biophysically optimising the provisions of each ecosystem service are presented and discussed. The study quantitatively determines that trade-offs among provisions of some ecosystem services are required when optimising an ecosystem service while other ecosystem services are synergistic when the provision of a single ecosystem service is optimised.
Levesque, Sarah; Delisle, Hélène; Agueh, Victoire
2015-03-01
Food guides are important tools for nutrition education. While developing a food guide in Benin, the objective was to determine the daily number of servings per food group and the portion sizes of common foods to be recommended. Linear programming (LP) was used to determine, for each predefined food group, the optimal number and size of servings of commonly consumed foods. Two types of constraints were introduced into the LP models: (i) WHO/FAO Recommended Nutrient Intakes and dietary guidelines for the prevention of chronic diseases; and (ii) dietary patterns based on local food consumption data recently collected in southern Benin in 541 adults. Dietary intakes of the upper tertile of participants for diet quality based on prevention and micronutrient adequacy scores were used in the LP algorithms. Southern area of the Republic of Benin. Local key-players in nutrition (n 30) from the government, academic institutions, international organizations and civil society were partners in the development of the food guide directed at the population. The number of servings per food group and the portion size for eight age-sex groups were determined. For four limiting micronutrients (Fe, Ca, folate and Zn), local diets could be optimized to meet only 70 % of the Recommended Nutrient Intakes, not 100 %. It was possible to determine the daily number of servings and the portion sizes of common foods that can be recommended in Benin with the help of LP to optimize local diets, although Recommended Nutrient Intakes were not fully met for a few critical micronutrients.
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Esten I. Grøtli
2016-04-01
Full Text Available Large amounts of data are typically generated in applications such as surveillance of power lines and railways, inspection of gas pipes, and security surveillance. In the latter application it is a necessity that the data is transmitted to the control centre ``on-the-fly'' for analysis. Also missions related to other applications would greatly benefit from near real-time analysis and operator interaction based on captured data. This is the motivation behind this paper on coarse offline motion- and communication-planning for cooperating Unmanned Aerial Vehicles (UAVs. A Mixed-Integer Linear Programming (MILP problem is defined in order to solve the surveillance mission. To efficiently transmit the data back to the base station the vehicles are allowed to store data for later transmission and transmit via other vehicles, in addition to direct transmission. The paths obtained by solving the optimization problem are analyzed using a realistic radio propagation path loss simulator. If the radio propagation path loss exceeds the maximum design criterion the optimization problem is solved again with a stricter communication constraint, and the procedure is continued in an iterative manner until the criterion is met. The proposed algorithm is supported by simulations showing the resulting paths and communication topologies for different choices of delay tolerance.
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S. Mohammad Arabzad
2012-06-01
Full Text Available In recent years, numerous methods have been proposed to deal with supplier evaluation and selection problem, but a point which has been usually neglected by researchers is the role of purchasing items. The aim of this paper is to propose an integrated approach to select suppliers and allocate orders on the basis of the nature of the purchasing items which means that this issue plays an important role in supplier selection and order allocation. Therefore, items are first categorized according to the Kraljic’s model by the use of FMEA technique. Then, suppliers are categorized and evaluated in four phases with respect to different types of purchasing items (Strategic, Bottleneck, Leverage and Routine. Finally, an integer linear programming is utilized to allocate purchasing orders to suppliers. Furthermore, an empirical example is conducted to illustrate the stage of proposed approach. Results imply that ranking of suppliers and allocation of purchasing items based on the nature of purchasing items will create more capabilities in managing purchasing items and suppliers .
Lee, Dongyul; Lee, Chaewoo
2014-01-01
The advancement in wideband wireless network supports real time services such as IPTV and live video streaming. However, because of the sharing nature of the wireless medium, efficient resource allocation has been studied to achieve a high level of acceptability and proliferation of wireless multimedia. Scalable video coding (SVC) with adaptive modulation and coding (AMC) provides an excellent solution for wireless video streaming. By assigning different modulation and coding schemes (MCSs) to video layers, SVC can provide good video quality to users in good channel conditions and also basic video quality to users in bad channel conditions. For optimal resource allocation, a key issue in applying SVC in the wireless multicast service is how to assign MCSs and the time resources to each SVC layer in the heterogeneous channel condition. We formulate this problem with integer linear programming (ILP) and provide numerical results to show the performance under 802.16 m environment. The result shows that our methodology enhances the overall system throughput compared to an existing algorithm.
Ryan, Jason C; Banerjee, Ashis Gopal; Cummings, Mary L; Roy, Nicholas
2014-06-01
Planning operations across a number of domains can be considered as resource allocation problems with timing constraints. An unexplored instance of such a problem domain is the aircraft carrier flight deck, where, in current operations, replanning is done without the aid of any computerized decision support. Rather, veteran operators employ a set of experience-based heuristics to quickly generate new operating schedules. These expert user heuristics are neither codified nor evaluated by the United States Navy; they have grown solely from the convergent experiences of supervisory staff. As unmanned aerial vehicles (UAVs) are introduced in the aircraft carrier domain, these heuristics may require alterations due to differing capabilities. The inclusion of UAVs also allows for new opportunities for on-line planning and control, providing an alternative to the current heuristic-based replanning methodology. To investigate these issues formally, we have developed a decision support system for flight deck operations that utilizes a conventional integer linear program-based planning algorithm. In this system, a human operator sets both the goals and constraints for the algorithm, which then returns a proposed schedule for operator approval. As a part of validating this system, the performance of this collaborative human-automation planner was compared with that of the expert user heuristics over a set of test scenarios. The resulting analysis shows that human heuristics often outperform the plans produced by an optimization algorithm, but are also often more conservative.
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Dwi Erna Novianti
2016-09-01
Full Text Available This research and development is meant to produce a product of learning set based on problem submission and problem solving in Linear program course in the department of mathematics Teaching of IKIP PGRI Bojonegoro. The development of this set includes Lesson Plan, worksheet and a test of study result. This research is done within the department of Mathematics Teaching of IKIP PGRI Bojonegoro in the academic year of 2015/2016 from March to June 2016. The population of this research are sixth semester students. The research method used in this research is developmental research, while the model of developmental research used is developmental Thiagarajan which had been modified from four steps into three steps model namely:defining, designing, and developing. The data collection methods used in this research are documentation, Questionnaire, and learning result. The result shows that the set of learning in 4-D model which had been modified, resulted in a good learning set of JUCAMA model because the set of learning produced is a valid set based on the expert and based on the test in the field shows the data as the response toward positive learning, and the result of the test had fulfilled a good validation criteria, reliability as well as its sensitiveness.
Simic, Vladimir; Dimitrijevic, Branka
2015-02-01
An interval linear programming approach is used to formulate and comprehensively test a model for optimal long-term planning of vehicle recycling in the Republic of Serbia. The proposed model is applied to a numerical case study: a 4-year planning horizon (2013-2016) is considered, three legislative cases and three scrap metal price trends are analysed, availability of final destinations for sorted waste flows is explored. Potential and applicability of the developed model are fully illustrated. Detailed insights on profitability and eco-efficiency of the projected contemporary equipped vehicle recycling factory are presented. The influences of the ordinance on the management of end-of-life vehicles in the Republic of Serbia on the vehicle hulks procuring, sorting generated material fractions, sorted waste allocation and sorted metals allocation decisions are thoroughly examined. The validity of the waste management strategy for the period 2010-2019 is tested. The formulated model can create optimal plans for procuring vehicle hulks, sorting generated material fractions, allocating sorted waste flows and allocating sorted metals. Obtained results are valuable for supporting the construction and/or modernisation process of a vehicle recycling system in the Republic of Serbia. © The Author(s) 2015.
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Hassan Barati
2011-10-01
Full Text Available In this paper a new bidding strategy become modeling to day-ahead markets. The proposed algorithm is related to the point of view of a generation company (Genco that its end is maximized its benefit as a participant in sale markets of active power and spinning reserve. In this method, hourly forecasted energy price (FEP and forecasted reserve price (FRP is used as a reference to model the possible and probable price strategies of Gencos. A bi-level optimization problem That first level, is used to maximize the individual Genco’s payoffs for obtaining the optimal offered quantity of Gencos. The second one, uses the results of the upper sub-problem and minimizes the consumer’s payment with regard to the technical and network constraints, which leads to the awarded generation of the Gencos. In this paper use of the game theory in exist optimization model. The paper proposes a linear programming approach. A six bus system is employed to illustrate the application of the proposed method and to show its high precision and capabilities.
Ryan, Kelsey N; Adams, Katherine P; Vosti, Stephen A; Ordiz, M Isabel; Cimo, Elizabeth D; Manary, Mark J
2014-12-01
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 international and national crop and animal food databases was used to create a global and local candidate ingredient database. The database included information about each ingredient regarding nutrient composition, ingredient category, regional availability, and food safety, processing, and price. An LP tool was then designed to compose novel RUTF formulations. For the example case of Ethiopia, the objective was to minimize the ingredient cost of RUTF; the decision variables were ingredient weights and the extent of use of locally available ingredients, and the constraints were nutritional and product-quality related. Of the new RUTF formulations found by the LP tool for Ethiopia, 32 were predicted to be feasible for creating a paste, and these were prepared in the laboratory. Palatable final formulations contained a variety of ingredients, including fish, different dairy powders, and various seeds, grains, and legumes. Nearly all of the macronutrient values calculated by the LP tool differed by lead to production of a variety of low-cost RUTF formulations that meet international standards and thereby potentially allow more children to be treated for SAM. © 2014 American Society for Nutrition.
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Jebaraj, S.; Iniyan, S. [Anna University, Chennai (India). Dept. of Mechanical Engineering
2007-07-01
Development of an energy allocation model will help in the proper allocation of the energy sources in meeting the future energy demand in India. In this paper, an attempt has been made to develop a fuzzy-based linear programming optimal energy model that minimises the cost and determines the optimum allocation of different energy sources for the centralised and decentralised power generation in India. The potential, energy demand, efficiency, emission and carbon tax are used as constraints in the model. The model allocates the energy distribution pattern for the year 2020 in India. The results indicate that the energy distribution pattern would be 15,800 GWh (4%) from the coal-based plants, 85,400 GWh (20%) from the nuclear plants, 191,100 GWh (44%) from the hydro plants, 22,400 GWh (5%) from the wind turbine generators, 45,520 GWh (11%) from the biomass gasifier plants, 14,112 GWh (3%) from the biogas plants, 8400 GWh (2%) from the solid waste, 33,600 GWh (8%) from the cogeneration plants and 11,970 GWh (3%) from the mini-hydel plants, for the year 2020. A sensitivity analysis has been done to validate the OEAM model. This study will help in the formation of strategies for the effective utilisation of energy sources in India.
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Jebaraj, S.; Iniyan, S. [Anna University, Chennai (India). Department of Mechanical Engineering
2004-08-15
Development of an energy allocation model will help in the proper allocation of the energy sources in meeting the future energy demand in India. In this paper, an attempt has been made to develop a fuzzy-based linear programming optimal energy model that minimises the cost and determines the optimum allocation of different energy sources for the centralised and decentralised power generation in India. The potential, energy demand, efficiency, emission and carbon tax are used as constraints in the model. The model allocates the energy distribution pattern for the year 2020 in India. The results indicate that the energy distribution pattern would be 15,800 GWh (4%) from the coal-based plants, 85 400 GWh (20%) from the nuclear plants, 191,100 GWh (44%) from the hydro plants, 22 400 GWh (5%) from the wind turbine generators, 45,520 GWh (11%) from the biomass gasifier plants, 14,112 GWh (3%) from the biogas plants, 8400 GWh (2%) from the solid waste, 33,600 GWh (8%) from the cogeneration plants and 11,970 GWh (3%) from the mini-hydel plants, for the year 2020. A sensitivity analysis has been done to validate the OEAM model. This study will help in the formation of strategies for the effective utilisation of energy sources in India.
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Augusto Hauber Gameiro
2016-04-01
Full Text Available ABSTRACT A linear programming mathematical model was applied to a representative dairy farm located in Brazil. The results showed that optimization models are relevant tools to assist in the planning and management of agricultural production, as well as to assist in estimating potential gains from the use of integrated systems. Diversification was a necessary condition for economic viability. A total cost reduction potential of about 30% was revealed when a scenario of lower levels of diversification was contrasted to one of higher levels. Technical complementarities proved to be important sources of economies. The possibility of reusing nitrogen, phosphorus, and potassium present in animal waste could be increased to 167%, while water reuse could be increased up to 150%. In addition to economic gains, integrated systems bring benefits to the environment, especially with reference to the reuse of resources. The cost dilution of fixed production factors can help economies of scope to be achieved. However, this does not seem to have been the main source of these benefits. Still, the percentage of land use could increase up to 30.7% when the lowest and the highest diversification scenarios were compared. The labor coefficient could have a 4.3 percent increase. Diversification also leads to drastic transaction cost reductions.
Kronberg, James W.
1994-01-01
A proximity sensor based on a closed field circuit. The circuit comprises a ring oscillator using a symmetrical array of plates that creates an oscillating displacement current. The displacement current varies as a function of the proximity of objects to the plate array. Preferably the plates are in the form of a group of three pair of symmetric plates having a common center, arranged in a hexagonal pattern with opposing plates linked as a pair. The sensor produces logic level pulses suitable for interfacing with a computer or process controller. The proximity sensor can be incorporated into a load cell, a differential pressure gauge, or a device for measuring the consistency of a characteristic of a material where a variation in the consistency causes the dielectric constant of the material to change.
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.
Atrofia muscular proximal familiar
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José Antonio Levy
1962-09-01
Full Text Available Os autores relatam dois casos de atrofia muscular proximal familiar, moléstia caracterizada por déficit motor e atrofias musculares de distribuição proximal, secundárias a lesão de neurônios periféricos. Assim, como em outros casos descritos na literatura, foi feito inicialmente o diagnóstico de distrofia muscular progressiva. O diagnóstico correto foi conseguido com auxílio da eletromiografia e da biopsia muscular.
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Ureba, A. [Dpto. Fisiología Médica y Biofísica. Facultad de Medicina, Universidad de Sevilla, E-41009 Sevilla (Spain); Salguero, F. J. [Nederlands Kanker Instituut, Antoni van Leeuwenhoek Ziekenhuis, 1066 CX Ámsterdam, The Nederlands (Netherlands); Barbeiro, A. R.; Jimenez-Ortega, E.; Baeza, J. A.; Leal, A., E-mail: alplaza@us.es [Dpto. Fisiología Médica y Biofísica, Facultad de Medicina, Universidad de Sevilla, E-41009 Sevilla (Spain); Miras, H. [Servicio de Radiofísica, Hospital Universitario Virgen Macarena, E-41009 Sevilla (Spain); Linares, R.; Perucha, M. [Servicio de Radiofísica, Hospital Infanta Luisa, E-41010 Sevilla (Spain)
2014-08-15
Purpose: The authors present a hybrid direct multileaf collimator (MLC) aperture optimization model exclusively based on sequencing of patient imaging data to be implemented on a Monte Carlo treatment planning system (MC-TPS) to allow the explicit radiation transport simulation of advanced radiotherapy treatments with optimal results in efficient times for clinical practice. Methods: The planning system (called CARMEN) is a full MC-TPS, controlled through aMATLAB interface, which is based on the sequencing of a novel map, called “biophysical” map, which is generated from enhanced image data of patients to achieve a set of segments actually deliverable. In order to reduce the required computation time, the conventional fluence map has been replaced by the biophysical map which is sequenced to provide direct apertures that will later be weighted by means of an optimization algorithm based on linear programming. A ray-casting algorithm throughout the patient CT assembles information about the found structures, the mass thickness crossed, as well as PET values. Data are recorded to generate a biophysical map for each gantry angle. These maps are the input files for a home-made sequencer developed to take into account the interactions of photons and electrons with the MLC. For each linac (Axesse of Elekta and Primus of Siemens) and energy beam studied (6, 9, 12, 15 MeV and 6 MV), phase space files were simulated with the EGSnrc/BEAMnrc code. The dose calculation in patient was carried out with the BEAMDOSE code. This code is a modified version of EGSnrc/DOSXYZnrc able to calculate the beamlet dose in order to combine them with different weights during the optimization process. Results: Three complex radiotherapy treatments were selected to check the reliability of CARMEN in situations where the MC calculation can offer an added value: A head-and-neck case (Case I) with three targets delineated on PET/CT images and a demanding dose-escalation; a partial breast
Ureba, A; Salguero, F J; Barbeiro, A R; Jimenez-Ortega, E; Baeza, J A; Miras, H; Linares, R; Perucha, M; Leal, A
2014-08-01
The authors present a hybrid direct multileaf collimator (MLC) aperture optimization model exclusively based on sequencing of patient imaging data to be implemented on a Monte Carlo treatment planning system (MC-TPS) to allow the explicit radiation transport simulation of advanced radiotherapy treatments with optimal results in efficient times for clinical practice. The planning system (called CARMEN) is a full MC-TPS, controlled through aMATLAB interface, which is based on the sequencing of a novel map, called "biophysical" map, which is generated from enhanced image data of patients to achieve a set of segments actually deliverable. In order to reduce the required computation time, the conventional fluence map has been replaced by the biophysical map which is sequenced to provide direct apertures that will later be weighted by means of an optimization algorithm based on linear programming. A ray-casting algorithm throughout the patient CT assembles information about the found structures, the mass thickness crossed, as well as PET values. Data are recorded to generate a biophysical map for each gantry angle. These maps are the input files for a home-made sequencer developed to take into account the interactions of photons and electrons with the MLC. For each linac (Axesse of Elekta and Primus of Siemens) and energy beam studied (6, 9, 12, 15 MeV and 6 MV), phase space files were simulated with the EGSnrc/BEAMnrc code. The dose calculation in patient was carried out with the BEAMDOSE code. This code is a modified version of EGSnrc/DOSXYZnrc able to calculate the beamlet dose in order to combine them with different weights during the optimization process. Three complex radiotherapy treatments were selected to check the reliability of CARMEN in situations where the MC calculation can offer an added value: A head-and-neck case (Case I) with three targets delineated on PET/CT images and a demanding dose-escalation; a partial breast irradiation case (Case II) solved
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.
Zhang, Huiling; Huang, Qingsheng; Bei, Zhendong; Wei, Yanjie; Floudas, Christodoulos A
2016-03-01
In this article, we present COMSAT, a hybrid framework for residue contact prediction of transmembrane (TM) proteins, integrating a support vector machine (SVM) method and a mixed integer linear programming (MILP) method. COMSAT consists of two modules: COMSAT_SVM which is trained mainly on position-specific scoring matrix features, and COMSAT_MILP which is an ab initio method based on optimization models. Contacts predicted by the SVM model are ranked by SVM confidence scores, and a threshold is trained to improve the reliability of the predicted contacts. For TM proteins with no contacts above the threshold, COMSAT_MILP is used. The proposed hybrid contact prediction scheme was tested on two independent TM protein sets based on the contact definition of 14 Å between Cα-Cα atoms. First, using a rigorous leave-one-protein-out cross validation on the training set of 90 TM proteins, an accuracy of 66.8%, a coverage of 12.3%, a specificity of 99.3% and a Matthews' correlation coefficient (MCC) of 0.184 were obtained for residue pairs that are at least six amino acids apart. Second, when tested on a test set of 87 TM proteins, the proposed method showed a prediction accuracy of 64.5%, a coverage of 5.3%, a specificity of 99.4% and a MCC of 0.106. COMSAT shows satisfactory results when compared with 12 other state-of-the-art predictors, and is more robust in terms of prediction accuracy as the length and complexity of TM protein increase. COMSAT is freely accessible at http://hpcc.siat.ac.cn/COMSAT/. © 2016 Wiley Periodicals, Inc.
Dexter, Franklin; Blake, John T; Penning, Donald H; Sloan, Brian; Chung, Patricia; Lubarsky, David A
2002-03-01
Administrators at hospitals with a fixed annual budget may want to focus surgical services on priority areas to ensure its community receives the best health services possible. However, many hospitals lack the detailed managerial accounting data needed to ensure that such a change does not increase operating costs. The authors used a detailed hospital cost database to investigate by how much a change in allocations of operating room (OR) time among surgeons can increase perioperative variable costs. The authors obtained financial data for all patients who underwent outpatient or same-day admit surgery during a year. Linear programming was used to determine by how much changing the mix of surgeons can increase total variable costs while maintaining the same total hours of OR time for elective cases. Changing OR allocations among surgeons without changing total OR hours allocated will likely increase perioperative variable costs by less than 34%. If, in addition, intensive care unit hours for elective surgical cases are not increased, hospital ward occupancy is capped, and implant use is tracked and capped, perioperative costs will likely increase by less than 10%. These four variables predict 97% of the variance in total variable costs. The authors showed that changing OR allocations among surgeons without changing total OR hours allocated can increase hospital perioperative variable costs by up to approximately one third. Thus, at hospitals with fixed or nearly fixed annual budgets, allocating OR time based on an OR-based statistic such as utilization can adversely affect the hospital financially. The OR manager can reduce the potential increase in costs by considering not just OR time, but also the resulting use of hospital beds and implants.
[Experimental proximal carpectomy. Biodynamics].
Kuhlmann, J N
1992-01-01
Proximal carpectomy was performed in 10 fresh cadavre wrists. Dynamic x-rays were taken and the forces necessary to obtain different movements before and after the operation were measured. Comparison of these parameters clearly defines the advantages and limitations of carpectomy and indicates the reasons.
Donahue, Craig J.; Rais, Elizabeth A.
2009-01-01
This lab experiment illustrates the use of thermogravimetric analysis (TGA) to perform proximate analysis on a series of coal samples of different rank. Peat and coke are also examined. A total of four exercises are described. These are dry exercises as students interpret previously recorded scans. The weight percent moisture, volatile matter,…
... the Big Toe Ailments of the Smaller Toes Diabetic Foot Treatments Currently selected Injections and other Procedures Treatments ... from which the bone was taken if the foot/ankle surgeries done at the same time allow for it. ... problems after a PTBG include infection, fracture of the proximal tibia and pain related ...
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Cuevas Vivas, Gabriel Francisco
1999-12-01
A methodology to optimize enrichment distributions in Light Water Reactor (LWR) fuel assemblies is developed and tested. The optimization technique employed is the linear programming revised simplex method, and the fuel assembly's performance is evaluated with a neutron transport code that is also utilized in the calculation of sensitivity coefficients. The enrichment distribution optimization procedure begins from a single-value (flat) enrichment distribution until a target, maximum local power peaking factor, is achieved. The optimum rod enrichment distribution, with 1.00 for the maximum local power peaking factor and with each rod having its own enrichment, is calculated at an intermediate stage of the analysis. Later, the best locations and values for a reduced number of rod enrichments is obtained as a function of a target maximum local power peaking factor by applying sensitivity to change techniques. Finally, a shuffling process that assigns individual rod enrichments among the enrichment groups is performed. The relative rod power distribution is then slightly modified and the rod grouping redefined until the optimum configuration is attained. To verify the accuracy of the relative rod power distribution, a full computation with the neutron transport code using the optimum enrichment distribution is carried out. The results are compared and tested for assembly designs loaded with fresh Low Enriched Uranium (LEU) and plutonium Mixed Oxide (MOX) isotopics for both reactor-grade and weapons-grade plutonium were utilized to demonstrate the wide range of applicability of the optimization technique. The feature of the assembly designs used for evaluation purposes included burnable absorbers and internal water regions, and were prepared to resemble the configurations of modern assemblies utilized in commercial Boiling Water Reactor (BWRs) and Pressurized Water Reactors (PWRs). In some cases, a net improvement in the relative rod power distribution or in the
2013-01-01
that these constraints can often lead to significant reductions in the gap between the optimal solution and its non-integral linear programming bound relative to the prior art as well as often substantially faster processing of moderately hard problem instances. Conclusion We provide an indication of the conditions under which such an optimal enumeration approach is likely to be feasible, suggesting that these strategies are usable for relatively large numbers of taxa, although with stricter limits on numbers of variable sites. The work thus provides methodology suitable for provably optimal solution of some harder instances that resist all prior approaches. PMID:23343437
Simic, Vladimir
2015-01-01
End-of-life vehicles (ELVs) are vehicles that have reached the end of their useful lives and are no longer registered or licensed for use. The ELV recycling problem has become very serious in the last decade and more and more efforts are made in order to reduce the impact of ELVs on the environment. This paper proposes the fuzzy risk explicit interval linear programming model for ELV recycling planning in the EU. It has advantages in reflecting uncertainties presented in terms of intervals in the ELV recycling systems and fuzziness in decision makers' preferences. The formulated model has been applied to a numerical study in which different decision maker types and several ELV types under two EU ELV Directive legislative cases were examined. This study is conducted in order to examine the influences of the decision maker type, the α-cut level, the EU ELV Directive and the ELV type on decisions about vehicle hulks procuring, storing unprocessed hulks, sorting generated material fractions, allocating sorted waste flows and allocating sorted metals. Decision maker type can influence quantity of vehicle hulks kept in storages. The EU ELV Directive and decision maker type have no influence on which vehicle hulk type is kept in the storage. Vehicle hulk type, the EU ELV Directive and decision maker type do not influence the creation of metal allocation plans, since each isolated metal has its regular destination. The valid EU ELV Directive eco-efficiency quotas can be reached even when advanced thermal treatment plants are excluded from the ELV recycling process. The introduction of the stringent eco-efficiency quotas will significantly reduce the quantities of land-filled waste fractions regardless of the type of decision makers who will manage vehicle recycling system. In order to reach these stringent quotas, significant quantities of sorted waste need to be processed in advanced thermal treatment plants. Proposed model can serve as the support for the European
Jonrinaldi, Hadiguna, Rika Ampuh; Salastino, Rades
2017-11-01
Environmental consciousness has paid many attention nowadays. It is not only about how to recycle, remanufacture or reuse used end products but it is also how to optimize the operations of the reverse system. A previous research has proposed a design of reverse supply chain of biodiesel network from used cooking oil. However, the research focused on the design of the supply chain strategy not the operations of the supply chain. It only decided how to design the structure of the supply chain in the next few years, and the process of each stage will be conducted in the supply chain system in general. The supply chain system has not considered operational policies to be conducted by the companies in the supply chain. Companies need a policy for each stage of the supply chain operations to be conducted so as to produce the optimal supply chain system, including how to use all the resources that have been designed in order to achieve the objectives of the supply chain system. Therefore, this paper proposes a model to optimize the operational planning of a biodiesel supply chain network from used cooking oil. A mixed integer linear programming is developed to model the operational planning of biodiesel supply chain in order to minimize the total operational cost of the supply chain. Based on the implementation of the model developed, the total operational cost of the biodiesel supply chain incurred by the system is less than the total operational cost of supply chain based on the previous research during seven days of operational planning about amount of 2,743,470.00 or 0.186%. Production costs contributed to 74.6 % of total operational cost and the cost of purchasing the used cooking oil contributed to 24.1 % of total operational cost. So, the system should pay more attention to these two aspects as changes in the value of these aspects will cause significant effects to the change in the total operational cost of the supply chain.
Directory of Open Access Journals (Sweden)
Jonathan T. Barge
2016-06-01
Full Text Available This study focused on employing Linear Genetic Programming (LGP, Ensemble Empirical Mode Decomposition (EEMD, and the Self-Organizing Map (SOM in modeling the rainfall–runoff relationship in a mid-size catchment. Models were assessed with regard to their ability to capture daily discharge at Lock and Dam 10 along the Kentucky River as well as the hybrid design of EEM-SOM-LGP to make predictions multiple time-steps ahead. Different model designs were implemented to demonstrate the improvements of hybrid designs compared to LGP as a standalone application. Additionally, LGP was utilized to gain a better understanding of the catchment in question and to assess its ability to capture different aspects of the flow hydrograph. As a standalone application, LGP was able to outperform published Artificial Neural Network (ANN results over the same dataset, posting an average absolute relative error (AARE of 17.118 and Nash-Sutcliff (E of 0.937. Utilizing EEMD derived IMF runoff subcomponents for forecasting daily discharge resulted in an AARE of 14.232 and E of 0.981. Clustering the EEMD-derived input space through an SOM before LGP application returned the strongest results, posting an AARE of 10.122 and E of 0.987. Applying LGP to the distinctive low and high flow seasons demonstrated a loss in correlation for the low flow season with an under-predictive nature signified by a normalized mean biased error (NMBE of −2.353. Separating the rising and falling trends of the hydrograph showed that the falling trends were more easily captured with an AARE of 8.511 and E of 0.968 compared to the rising trends AARE of 38.744 and E of 0.948. Utilizing the EEMD-SOM-LGP design to make predictions multiple-time-steps ahead resulted in a AARE of 43.365 and E of 0.902 for predicting streamflow three days ahead. The results demonstrate the effectiveness of utilizing EEMD and an SOM in conjunction with LGP for streamflow forecasting.
DEFF Research Database (Denmark)
Palm, Henrik; Teixidor, Jordi
2015-01-01
-displaced femoral neck fractures and prosthesis for displaced among the elderly; and sliding hip screw for stabile- and intramedullary nails for unstable- and sub-trochanteric fractures) but they are based on a variety of criteria and definitions - and often leave wide space for the individual surgeons' subjective...... guidelines for hip fracture surgery and discuss a method for future pathway/guideline implementation and evaluation. METHODS: By a PubMed search in March 2015 six studies of surgical treatment pathways covering all types of proximal femoral fractures with publication after 1995 were identified. Also we...... 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...
Mauro, Craig S.
2011-01-01
Proximal humeral fractures may present with many different configurations in patients with varying co-morbities and expectations. As a result, the treating physician must understand the fracture pattern, the quality of the bone, other patient-related factors, and the expanding range of reconstructive options to achieve the best functional outcome and to minimize complications. Current treatment options range from non-operative treatment with physical therapy to fracture fixation using percuta...
Talsma, Elise F.; Borgonjen-van den Berg, Karin J.; Melse-Boonstra, Alida; Mayer, Eva V.; Verhoef, Hans; Demir, Ayşe Y.; Ferguson, Elaine L.; Kok, Frans J.; Brouwer, Inge D.
2018-01-01
Objective: Introduction of biofortified cassava as school lunch can increase vitamin A intake, but may increase risk of other deficiencies due to poor nutrient profile of cassava. We assessed the potential effect of introducing a yellow cassava-based school lunch combined with additional food-based recommendations (FBR) on vitamin A and overall nutrient adequacy using Optifood (linear programming tool). Design: Cross-sectional study to assess dietary intakes (24 h recall) and derive model par...
DEFF Research Database (Denmark)
Xydis, George; Koroneos, C.
2012-01-01
renewable energy sources (RES) and at the same time to define the remaining available space for energy recovery units from municipal solid waste (MSW) in each region to participate in the energy system. Based on the results of the different scenarios examined for meeting the electricity needs using linear...... programming and by using the exergoeconomic analysis the penetration grade was found for the proposed energy recovery units from MSWs in each region....
Directory of Open Access Journals (Sweden)
João C. F. Borges Júnior
2008-09-01
Full Text Available Linear programming models are effective tools to support initial or periodic planning of agricultural enterprises, requiring, however, technical coefficients that can be determined using computer simulation models. This paper, presented in two parts, deals with the development, application and tests of a methodology and of a computational modeling tool to support planning of irrigated agriculture activities. Part I aimed at the development and application, including sensitivity analysis, of a multiyear linear programming model to optimize the financial return and water use, at farm level for Jaíba irrigation scheme, Minas Gerais State, Brazil, using data on crop irrigation requirement and yield, obtained from previous simulation with MCID model. The linear programming model outputted a crop pattern to which a maximum total net present value of R$ 372,723.00 for the four years period, was obtained. Constraints on monthly water availability, labor, land and production were critical in the optimal solution. In relation to the water use optimization, it was verified that an expressive reductions on the irrigation requirements may be achieved by small reductions on the maximum total net present value.Modelos de programação linear são ferramentas eficazes de suporte ao planejamento inicial ou periódico de empreendimentos agrícolas, requerendo, todavia, coeficientes técnicos que podem ser obtidos por modelos computacionais de simulação. Este trabalho, dividido em duas partes, aborda o desenvolvimento, a aplicação e os testes de metodologia e da modelagem computacional de uma ferramenta de auxílio ao planejamento da exploração agrícola irrigada. Teve-se o objetivo de desenvolver e aplicar, com análise de sensibilidade, um modelo de programação linear plurianual para otimização do retorno financeiro e uso da água, em nível de propriedade rural no perímetro de irrigação do Jaíba - MG, utilizando dados de requerimento de irriga
TEWIERIK, GHP; VANDERVEEN, J; EISSENS, AC; LERK, CF
1993-01-01
This study reports the successful application of amylodextrin as a unique excipient in the design of programmed release systems. Physical mixtures of amylodextrin with the model compounds theophylline, paracetamol, methyl-PABA, prednisolone, atrazine, procaine HCl and potassium dichromate,
Energy Technology Data Exchange (ETDEWEB)
Waddell, Lucas [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Muldoon, Frank [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Henry, Stephen Michael [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Hoffman, Matthew John [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Zwerneman, April Marie [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Backlund, Peter [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Melander, Darryl J. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Lawton, Craig R. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Rice, Roy Eugene [Teledyne Brown Engineering, Huntsville, AL (United States)
2017-09-01
In order to effectively plan the management and modernization of their large and diverse fleets of vehicles, Program Executive Office Ground Combat Systems (PEO GCS) and Program Executive Office Combat Support and Combat Service Support (PEO CS&CSS) commis- sioned the development of a large-scale portfolio planning optimization tool. This software, the Capability Portfolio Analysis Tool (CPAT), creates a detailed schedule that optimally prioritizes the modernization or replacement of vehicles within the fleet - respecting numerous business rules associated with fleet structure, budgets, industrial base, research and testing, etc., while maximizing overall fleet performance through time. This paper contains a thor- ough documentation of the terminology, parameters, variables, and constraints that comprise the fleet management mixed integer linear programming (MILP) mathematical formulation. This paper, which is an update to the original CPAT formulation document published in 2015 (SAND2015-3487), covers the formulation of important new CPAT features.
Some Properties of Fuzzy Soft Proximity Spaces
Demir, İzzettin; Özbakır, Oya Bedre
2015-01-01
We study the fuzzy soft proximity spaces in Katsaras's sense. First, we show how a fuzzy soft topology is derived from a fuzzy soft proximity. Also, we define the notion of fuzzy soft δ-neighborhood in the fuzzy soft proximity space which offers an alternative approach to the study of fuzzy soft proximity spaces. Later, we obtain the initial fuzzy soft proximity determined by a family of fuzzy soft proximities. Finally, we investigate relationship between fuzzy soft proximities and proximities. PMID:25793224
Darmon, Nicole; Ferguson, Elaine L; Briend, André
2002-12-01
Economic constraints may contribute to the unhealthy food choices observed among low socioeconomic groups in industrialized countries. The objective of the present study was to predict the food choices a rational individual would make to reduce his or her food budget, while retaining a diet as close as possible to the average population diet. Isoenergetic diets were modeled by linear programming. To ensure these diets were consistent with habitual food consumption patterns, departure from the average French diet was minimized and constraints that limited portion size and the amount of energy from food groups were introduced into the models. A cost constraint was introduced and progressively strengthened to assess the effect of cost on the selection of foods by the program. Strengthening the cost constraint reduced the proportion of energy contributed by fruits and vegetables, meat and dairy products and increased the proportion from cereals, sweets and added fats, a pattern similar to that observed among low socioeconomic groups. This decreased the nutritional quality of modeled diets, notably the lowest cost linear programming diets had lower vitamin C and beta-carotene densities than the mean French adult diet (i.e., diets and influence food selection in ways that reproduce the food intake patterns observed among low socioeconomic groups. They suggest that economic measures will be needed to effectively improve the nutritional quality of diets consumed by these populations.
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.
Linear optics based nanoscopy.
Gur, Aviram; Fixler, Dror; Micó, Vicente; Garcia, Javier; Zalevsky, Zeev
2010-10-11
Classically, optical systems are considered to have a fundamental resolution limit due to wave nature of light. This article presents a novel method for observing sub-wavelength features in a conventional optical microscope using linear optics. The operation principle is based on a random and time varying flow of nanoparticles moving in proximity to the inspected sample. Those particles excite the evanescent waves and couple them into harmonic waves. The sub-wavelength features are encoded and later on digitally decoded by proper image processing of a sequence of images. The achievable final resolution limit corresponds to the size of the nanoparticles. Experimental proof of principle validation of the technique is reported.
Turrini, Enrico; Carnevale, Claudio; Finzi, Giovanna; Volta, Marialuisa
2017-10-28
This paper introduces the MAQ (Multi-dimensional Air Quality) model aimed at defining cost-effective air quality plans at different scales (urban to national) and assessing the co-benefits for GHG emissions. The model implements and solves a non-linear multi-objective, multi-pollutant decision problem where the decision variables are the application levels of emission abatement measures allowing the reduction of energy consumption, end-of pipe technologies and fuel switch options. The objectives of the decision problem are the minimization of tropospheric secondary pollution exposure and of internal costs. The model assesses CO2 equivalent emissions in order to support decision makers in the selection of win-win policies. The methodology is tested on Lombardy region, a heavily polluted area in northern Italy. Copyright © 2017 Elsevier B.V. All rights reserved.
Xu, Guanglin; Burer, Samuel
2017-01-01
This paper studies the expected optimal value of a mixed 0-1 programming problem with uncertain objective coefficients following a joint distribution. We assume that the true distribution is not known exactly, but a set of independent samples can be observed. Using the Wasserstein metric, we construct an ambiguity set centered at the empirical distribution from the observed samples and containing the true distribution with a high statistical guarantee. The problem of interest is to investigat...
Bielawa, R. L.
1976-01-01
The differential equations of motion for the lateral and torsional deformations of a nonlinearly twisted rotor blade in steady flight conditions together with those additional aeroelastic features germane to composite bearingless rotors are derived. The differential equations are formulated in terms of uncoupled (zero pitch and twist) vibratory modes with exact coupling effects due to finite, time variable blade pitch and, to second order, twist. Also presented are derivations of the fully coupled inertia and aerodynamic load distributions, automatic pitch change coupling effects, structural redundancy characteristics of the composite bearingless rotor flexbeam - torque tube system in bending and torsion, and a description of the linearized equations appropriate for eigensolution analyses. Three appendixes are included presenting material appropriate to the digital computer program implementation of the analysis, program G400.
Maillot, Matthieu; Drewnowski, Adam
2011-02-01
The 2010 Dietary Guidelines Advisory Committee has recommended that no more than 5-15% of total dietary energy should be derived from solid fats and added sugars (SoFAS). The guideline was based on USDA food pattern modeling analyses that met the Dietary Reference Intake recommendations and Dietary Guidelines and followed typical American eating habits. This study recreated food intake patterns for 6 of the same gender-age groups by using USDA data sources and a mathematical optimization technique known as linear programming. The analytic process identified food consumption patterns based on 128 food categories that met the nutritional goals for 9 vitamins, 9 minerals, 8 macronutrients, and dietary fiber and minimized deviation from typical American eating habits. Linear programming Model 1 created gender- and age-specific food patterns that corresponded to energy needs for each group. Model 2 created food patterns that were iso-caloric with diets observed for that group in the 2001-2002 NHANES. The optimized food patterns were evaluated with respect to MyPyramid servings goals, energy density [kcal/g (1 kcal = 4.18 kJ)], and energy cost (US$/2000 kcal). The optimized food patterns had more servings of vegetables and fruit, lower energy density, and higher cost compared with the observed diets. All nutrient goals were met. In contrast to the much lower USDA estimates, the 2 models placed SoFAS allowances at between 17 and 33% of total energy, depending on energy needs.
Wang, Hsiao-Fan; Hsu, Hsin-Wei
2010-11-01
With the urgency of global warming, green supply chain management, logistics in particular, has drawn the attention of researchers. Although there are closed-loop green logistics models in the literature, most of them do not consider the uncertain environment in general terms. In this study, a generalized model is proposed where the uncertainty is expressed by fuzzy numbers. An interval programming model is proposed by the defined means and mean square imprecision index obtained from the integrated information of all the level cuts of fuzzy numbers. The resolution for interval programming is based on the decision maker (DM)'s preference. The resulting solution provides useful information on the expected solutions under a confidence level containing a degree of risk. The results suggest that the more optimistic the DM is, the better is the resulting solution. However, a higher risk of violation of the resource constraints is also present. By defining this probable risk, a solution procedure was developed with numerical illustrations. This provides a DM trade-off mechanism between logistic cost and the risk. Copyright 2010 Elsevier Ltd. All rights reserved.
Energy Technology Data Exchange (ETDEWEB)
Ureba, A.; Palma, B. A.; Leal, A.
2011-07-01
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.
Said-Houari, Belkacem
2017-01-01
This self-contained, clearly written textbook on linear algebra is easily accessible for students. It begins with the simple linear equation and generalizes several notions from this equation for the system of linear equations and introduces the main ideas using matrices. It then offers a detailed chapter on determinants and introduces the main ideas with detailed proofs. The third chapter introduces the Euclidean spaces using very simple geometric ideas and discusses various major inequalities and identities. These ideas offer a solid basis for understanding general Hilbert spaces in functional analysis. The following two chapters address general vector spaces, including some rigorous proofs to all the main results, and linear transformation: areas that are ignored or are poorly explained in many textbooks. Chapter 6 introduces the idea of matrices using linear transformation, which is easier to understand than the usual theory of matrices approach. The final two chapters are more advanced, introducing t...
Stoll, R R
1968-01-01
Linear Algebra is intended to be used as a text for a one-semester course in linear algebra at the undergraduate level. The treatment of the subject will be both useful to students of mathematics and those interested primarily in applications of the theory. The major prerequisite for mastering the material is the readiness of the student to reason abstractly. Specifically, this calls for an understanding of the fact that axioms are assumptions and that theorems are logical consequences of one or more axioms. Familiarity with calculus and linear differential equations is required for understand
Linear Algebra and Linear Models
Indian Academy of Sciences (India)
This monograph provides an introduction to the basic aspects of the theory oflinear estima- tion and that of testing linear hypotheses. The primary objective is to provide a basic knowledge of analysis of linear models to advanced undergraduate or first year Master's students. The second edition virtually covers the same ...
Laparoscopic proximal gastrectomy with oblique jejunogastrostomy.
Tanaka, Kimitaka; Ebihara, Yuma; Kurashima, Yo; Nakanishi, Yoshitsugu; Asano, Toshimichi; Noji, Takehiro; Murakami, Soichi; Nakamura, Toru; Tsuchikawa, Takahiro; Okamura, Keisuke; Shichinohe, Toshiaki; Hirano, Satoshi
2017-05-10
Proximal early gastric cancer is a good indication for totally laparoscopic proximal gastrectomy (TLPG) with double-tract reconstruction (DTR). However, when most of the dietary intake passes through the escape route of the jejunum, the functional benefits of proximal gastrectomy might be similar to those after total gastrectomy. Our DTR procedure was improved for easy passage through the remnant stomach. The purposes of this study were to present a novel technique for intracorporeal DTR using linear staplers after TLPG and to investigate surgical outcomes. DTR was performed using linear staplers only. A side-to-side jejunogastrostomy with twisting of both the remnant stomach and the anal jejunum was performed for the purpose of passing meals through the remnant stomach (an oblique jejunogastrostomy technique). The ten patients who underwent TLPG with DTR from January 2011 to August 2016 in Hokkaido University Hospital were retrospectively reviewed. Their clinicopathological characteristics and surgical and postoperative outcomes were collected and analyzed. The median duration of operation was 285 (range 146-440) min. No patients required blood transfusions. The number of dissected lymph nodes was 32 (range 22-56). There were no intraoperative complications, and no cases were converted to open surgery. All the patients were pT1N0M0 stage IA. No anastomotic leakage or complications were detected. Postoperative gastrography after reconstruction showed that contrast medium flowed mainly to the remnant stomach. The average percentage body weight loss was 14.0 ± 7.1% at 10 months. The average percentage decrease in serum hemoglobin was 5.4 ± 10.4% at 12 months. This novel technique for intracorporeal DTR provided a considerable advantage by the passage of dietary intake to the remnant stomach after LPG.
Armutlu, Pelin; Ozdemir, Muhittin E; Uney-Yuksektepe, Fadime; Kavakli, I Halil; Turkay, Metin
2008-10-03
A priori analysis of the activity of drugs on the target protein by computational approaches can be useful in narrowing down drug candidates for further experimental tests. Currently, there are a large number of computational methods that predict the activity of drugs on proteins. In this study, we approach the activity prediction problem as a classification problem and, we aim to improve the classification accuracy by introducing an algorithm that combines partial least squares regression with mixed-integer programming based hyper-boxes classification method, where drug molecules are classified as low active or high active regarding their binding activity (IC50 values) on target proteins. We also aim to determine the most significant molecular descriptors for the drug molecules. We first apply our approach by analyzing the activities of widely known inhibitor datasets including Acetylcholinesterase (ACHE), Benzodiazepine Receptor (BZR), Dihydrofolate Reductase (DHFR), Cyclooxygenase-2 (COX-2) with known IC50 values. The results at this stage proved that our approach consistently gives better classification accuracies compared to 63 other reported classification methods such as SVM, Naïve Bayes, where we were able to predict the experimentally determined IC50 values with a worst case accuracy of 96%. To further test applicability of this approach we first created dataset for Cytochrome P450 C17 inhibitors and then predicted their activities with 100% accuracy. Our results indicate that this approach can be utilized to predict the inhibitory effects of inhibitors based on their molecular descriptors. This approach will not only enhance drug discovery process, but also save time and resources committed.
Liesen, Jörg
2015-01-01
This self-contained textbook takes a matrix-oriented approach to linear algebra and presents a complete theory, including all details and proofs, culminating in the Jordan canonical form and its proof. Throughout the development, the applicability of the results is highlighted. Additionally, the book presents special topics from applied linear algebra including matrix functions, the singular value decomposition, the Kronecker product and linear matrix equations. The matrix-oriented approach to linear algebra leads to a better intuition and a deeper understanding of the abstract concepts, and therefore simplifies their use in real world applications. Some of these applications are presented in detailed examples. In several ‘MATLAB-Minutes’ students can comprehend the concepts and results using computational experiments. Necessary basics for the use of MATLAB are presented in a short introduction. Students can also actively work with the material and practice their mathematical skills in more than 300 exerc...
Searle, Shayle R
2012-01-01
This 1971 classic on linear models is once again available--as a Wiley Classics Library Edition. It features material that can be understood by any statistician who understands matrix algebra and basic statistical methods.
Berberian, Sterling K
2014-01-01
Introductory treatment covers basic theory of vector spaces and linear maps - dimension, determinants, eigenvalues, and eigenvectors - plus more advanced topics such as the study of canonical forms for matrices. 1992 edition.
Christofilos, N.C.; Polk, I.J.
1959-02-17
Improvements in linear particle accelerators are described. A drift tube system for a linear ion accelerator reduces gap capacity between adjacent drift tube ends. This is accomplished by reducing the ratio of the diameter of the drift tube to the diameter of the resonant cavity. Concentration of magnetic field intensity at the longitudinal midpoint of the external sunface of each drift tube is reduced by increasing the external drift tube diameter at the longitudinal center region.
Fractures of the proximal humerus
DEFF Research Database (Denmark)
Brorson, Stig
2013-01-01
. The bandages were further supported by splints made of wood or coarse grass. Healing was expected in forty days. Different fracture patterns have been discussed and classified since Ancient Greece. Current classification of proximal humeral fractures mainly relies on the classifications proposed by Charles......, 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......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...
Kang, Bongmun; Yoon, Ho-Sung
2015-02-01
Recently, microalgae was considered as a renewable energy for fuel production because its production is nonseasonal and may take place on nonarable land. Despite all of these advantages, microalgal oil production is significantly affected by environmental factors. Furthermore, the large variability remains an important problem in measurement of algae productivity and compositional analysis, especially, the total lipid content. Thus, there is considerable interest in accurate determination of total lipid content during the biotechnological process. For these reason, various high-throughput technologies were suggested for accurate measurement of total lipids contained in the microorganisms, especially oleaginous microalgae. In addition, more advanced technologies were employed to quantify the total lipids of the microalgae without a pretreatment. However, these methods are difficult to measure total lipid content in wet form microalgae obtained from large-scale production. In present study, the thermal analysis performed with two-step linear temeperature program was applied to measure heat evolved in temperature range from 310 to 351 °C of Nostoc sp. KNUA003 obtained from large-scale cultivation. And then, we examined the relationship between the heat evolved in 310-351 °C (HE) and total lipid content of the wet Nostoc cell cultivated in raceway. As a result, the linear relationship was determined between HE value and total lipid content of Nostoc sp. KNUA003. Particularly, there was a linear relationship of 98% between the HE value and the total lipid content of the tested microorganism. Based on this relationship, the total lipid content converted from the heat evolved of wet Nostoc sp. KNUA003 could be used for monitoring its lipid induction in large-scale cultivation. Copyright © 2014 Elsevier Inc. All rights reserved.
Wang, Jun-Sheng; Yang, Guang-Hong
2017-07-25
This paper studies the optimal output-feedback control problem for unknown linear discrete-time systems with stochastic measurement and process noise. A dithered Bellman equation with the innovation covariance matrix is constructed via the expectation operator given in the form of a finite summation. On this basis, an output-feedback-based approximate dynamic programming method is developed, where the terms depending on the innovation covariance matrix are available with the aid of the innovation covariance matrix identified beforehand. Therefore, by iterating the Bellman equation, the resulting value function can converge to the optimal one in the presence of the aforementioned noise, and the nearly optimal control laws are delivered. To show the effectiveness and the advantages of the proposed approach, a simulation example and a velocity control experiment on a dc machine are employed.
Levels and proximate determinants of fertility in Butajira District ...
African Journals Online (AJOL)
admin
and child health services in Ethiopia were one of the main aims of the health extension program. The impediment of ... Objectives: This study aimed at measuring levels and fertility inhibition effects of proximate determinants in Butajira district. Methods: A ... its link to the success of reproductive health programs and policies ...
Dibari, Filippo; Diop, El Hadji I; Collins, Steven; Seal, Andrew
2012-05-01
According to the United Nations (UN), 25 million children linear programming (LP) analysis was developed and piloted in the design of a RUTF prototype for the treatment of wasting in East African children and adults. The LP objective function and decision variables consisted of the lowest formulation price and the weights of the chosen commodities (soy, sorghum, maize, oil, and sugar), respectively. The LP constraints were based on current UN recommendations for the macronutrient content of therapeutic food and included palatability, texture, and maximum food ingredient weight criteria. Nonlinear constraints for nutrient ratios were converted to linear equations to allow their use in LP. The formulation was considered accurate if laboratory results confirmed an energy density difference <10% and a protein or lipid difference <5 g · 100 g(-1) compared to the LP formulation estimates. With this test prototype, the differences were 7%, and 2.3 and -1.0 g · 100 g(-1), respectively, and the formulation accuracy was considered good. LP can contribute to the design of ready-to-use foods (therapeutic, supplementary, or complementary), targeting different forms of malnutrition, while using commodities that are cheaper, regionally available, and meet local cultural preferences. However, as with all prototype feeding products for medical use, composition analysis, safety, acceptability, and clinical effectiveness trials must be conducted to validate the formulation.
The infrastructure of psychological proximity
DEFF Research Database (Denmark)
Nickelsen, Niels Christian Mossfeldt
2015-01-01
). The experience of psychological proximity between patient and nurse is provided through confidence, continuity and the practical set-up. This constitutes an important enactment of skillfulness, which may render telemedicine a convincing health service in the future. Methodology: The study draws on a pilot...... (Langstrup & Winthereik 2008). This study contributes by showing the infrastructure of psychological proximity, which is provided by way of device, confidence, continuity and accountability....
Li, Mo; Fu, Qiang; Singh, Vijay P.; Ma, Mingwei; Liu, Xiao
2017-12-01
Water scarcity causes conflicts among natural resources, society and economy and reinforces the need for optimal allocation of irrigation water resources in a sustainable way. Uncertainties caused by natural conditions and human activities make optimal allocation more complex. An intuitionistic fuzzy multi-objective non-linear programming (IFMONLP) model for irrigation water allocation under the combination of dry and wet conditions is developed to help decision makers mitigate water scarcity. The model is capable of quantitatively solving multiple problems including crop yield increase, blue water saving, and water supply cost reduction to obtain a balanced water allocation scheme using a multi-objective non-linear programming technique. Moreover, it can deal with uncertainty as well as hesitation based on the introduction of intuitionistic fuzzy numbers. Consideration of the combination of dry and wet conditions for water availability and precipitation makes it possible to gain insights into the various irrigation water allocations, and joint probabilities based on copula functions provide decision makers an average standard for irrigation. A case study on optimally allocating both surface water and groundwater to different growth periods of rice in different subareas in Heping irrigation area, Qing'an County, northeast China shows the potential and applicability of the developed model. Results show that the crop yield increase target especially in tillering and elongation stages is a prevailing concern when more water is available, and trading schemes can mitigate water supply cost and save water with an increased grain output. Results also reveal that the water allocation schemes are sensitive to the variation of water availability and precipitation with uncertain characteristics. The IFMONLP model is applicable for most irrigation areas with limited water supplies to determine irrigation water strategies under a fuzzy environment.
Linear Logical Voting Protocols
DEFF Research Database (Denmark)
DeYoung, Henry; Schürmann, Carsten
2012-01-01
Current approaches to electronic implementations of voting protocols involve translating legal text to source code of an imperative programming language. Because the gap between legal text and source code is very large, it is difficult to trust that the program meets its legal specification....... In response, we promote linear logic as a high-level language for both specifying and implementing voting protocols. Our linear logical specifications of the single-winner first-past-the-post (SW- FPTP) and single transferable vote (STV) protocols demonstrate that this approach leads to concise...
Olive, David J
2017-01-01
This text covers both multiple linear regression and some experimental design models. The text uses the response plot to visualize the model and to detect outliers, does not assume that the error distribution has a known parametric distribution, develops prediction intervals that work when the error distribution is unknown, suggests bootstrap hypothesis tests that may be useful for inference after variable selection, and develops prediction regions and large sample theory for the multivariate linear regression model that has m response variables. A relationship between multivariate prediction regions and confidence regions provides a simple way to bootstrap confidence regions. These confidence regions often provide a practical method for testing hypotheses. There is also a chapter on generalized linear models and generalized additive models. There are many R functions to produce response and residual plots, to simulate prediction intervals and hypothesis tests, to detect outliers, and to choose response trans...
Sahai, Vivek
2013-01-01
Beginning with the basic concepts of vector spaces such as linear independence, basis and dimension, quotient space, linear transformation and duality with an exposition of the theory of linear operators on a finite dimensional vector space, this book includes the concept of eigenvalues and eigenvectors, diagonalization, triangulation and Jordan and rational canonical forms. Inner product spaces which cover finite dimensional spectral theory and an elementary theory of bilinear forms are also discussed. This new edition of the book incorporates the rich feedback of its readers. We have added new subject matter in the text to make the book more comprehensive. Many new examples have been discussed to illustrate the text. More exercises have been included. We have taken care to arrange the exercises in increasing order of difficulty. There is now a new section of hints for almost all exercises, except those which are straightforward, to enhance their importance for individual study and for classroom use.
Edwards, Harold M
1995-01-01
In his new undergraduate textbook, Harold M Edwards proposes a radically new and thoroughly algorithmic approach to linear algebra Originally inspired by the constructive philosophy of mathematics championed in the 19th century by Leopold Kronecker, the approach is well suited to students in the computer-dominated late 20th century Each proof is an algorithm described in English that can be translated into the computer language the class is using and put to work solving problems and generating new examples, making the study of linear algebra a truly interactive experience Designed for a one-semester course, this text adopts an algorithmic approach to linear algebra giving the student many examples to work through and copious exercises to test their skills and extend their knowledge of the subject Students at all levels will find much interactive instruction in this text while teachers will find stimulating examples and methods of approach to the subject
DEFF Research Database (Denmark)
Ren, Carina Bregnholm; Gyimóthy, Szilvia; Jensen, Martin Trandberg
2014-01-01
There is a widespread acknowledgement among European policy-makers that higher education may potentially contribute to enhancing competitiveness of tourism. This has led to a sheer explosion of specific measures encouraging knowledge transfer with the private sector. Despite the importance...... of knowledge flow processes, the role of universities and students has been little researched or linked to the understanding of innovation defectiveness in tourism. Followed by a critical review of knowledge transfer and learning processes in generic development and tourism literature, the chapter presents...... an illustrative case from an innovation course on a Danish Master program in tourism. The case describes and discusses challenges in working with, creating and implementing innovation through student-practitioner collaboration. It is argued that successful innovation is not solely, as previously argued...
Allenby, Reg
1995-01-01
As the basis of equations (and therefore problem-solving), linear algebra is the most widely taught sub-division of pure mathematics. Dr Allenby has used his experience of teaching linear algebra to write a lively book on the subject that includes historical information about the founders of the subject as well as giving a basic introduction to the mathematics undergraduate. The whole text has been written in a connected way with ideas introduced as they occur naturally. As with the other books in the series, there are many worked examples.Solutions to the exercises are available onlin
Directory of Open Access Journals (Sweden)
Jozo Grgic
2017-08-01
Full Text Available Background Periodization is an important component of resistance training programs. It is meant to improve adherence to the training regimen, allow for constant progression, help in avoiding plateaus, and reduce occurrence and severity of injuries. Previous findings regarding the effects of different periodization models on measures of muscle hypertrophy are equivocal. To provide a more in-depth look at the topic, we undertook a systematic review of the literature and a meta-analysis of intervention trials comparing the effects of linear periodization (LP and daily undulating periodization (DUP resistance training programs on muscle hypertrophy. Materials and Methods A comprehensive literature search was conducted through PubMed/MEDLINE, Scopus, Web of Science, SPORTDiscus, Networked Digital Library of Theses and Dissertations (NDLTD and Open Access Theses and Dissertations (OATD. Results The pooled standardized mean difference (Cohen’s d from 13 eligible studies for the difference between the periodization models on muscle hypertrophy was −0.02 (95% confidence interval [−0.25, 0.21], p = 0.848. Conclusions The meta-analysis comparing LP and DUP indicated that the effects of the two periodization models on muscle hypertrophy are likely to be similar. However, more research is needed in this area, particularly among trained individuals and clinical populations. Future studies may benefit from using instruments that are more sensitive for detecting changes in muscle mass, such as ultrasound or magnetic resonance imaging.
Energy Technology Data Exchange (ETDEWEB)
Borbulevych, Oleg Y.; Plumley, Joshua A.; Martin, Roger I. [QuantumBio Inc., 2790 West College Avenue, State College, PA 16801 (United States); Merz, Kenneth M. Jr [University of Florida, Gainesville, Florida (United States); Westerhoff, Lance M., E-mail: lance@quantumbioinc.com [QuantumBio Inc., 2790 West College Avenue, State College, PA 16801 (United States)
2014-05-01
Semiempirical quantum-chemical X-ray macromolecular refinement using the program DivCon integrated with PHENIX is described. Macromolecular crystallographic refinement relies on sometimes dubious stereochemical restraints and rudimentary energy functionals to ensure the correct geometry of the model of the macromolecule and any covalently bound ligand(s). The ligand stereochemical restraint file (CIF) requires a priori understanding of the ligand geometry within the active site, and creation of the CIF is often an error-prone process owing to the great variety of potential ligand chemistry and structure. Stereochemical restraints have been replaced with more robust functionals through the integration of the linear-scaling, semiempirical quantum-mechanics (SE-QM) program DivCon with the PHENIX X-ray refinement engine. The PHENIX/DivCon package has been thoroughly validated on a population of 50 protein–ligand Protein Data Bank (PDB) structures with a range of resolutions and chemistry. The PDB structures used for the validation were originally refined utilizing various refinement packages and were published within the past five years. PHENIX/DivCon does not utilize CIF(s), link restraints and other parameters for refinement and hence it does not make as many a priori assumptions about the model. Across the entire population, the method results in reasonable ligand geometries and low ligand strains, even when the original refinement exhibited difficulties, indicating that PHENIX/DivCon is applicable to both single-structure and high-throughput crystallography.
Directory of Open Access Journals (Sweden)
E. Fallahi
2016-10-01
Full Text Available Introduction: Determining a suitable cropping pattern is an important task for planners and requires an exact and realistic decision-making process based on several goals and criteria corresponding to secure the interest of agricultural beneficiaries in long-term. Accordingly, this study reviews the current pattern operated by farmers in Sari, Iran, and intends to provide a cropping pattern that considers the multifold regional and agricultural sustainability criteria along with economic considerations. Materials and Methods: In order to achieve the study goals, a consolidated model of AHP and Linear Programming was applied. For this purpose, we constructed a three-level AHP, including a goal (determining the weight of each crop, seven criteria, and seven alternatives. Profitability, compatibility with regional and geographical conditions, water consumption, environmental effects of cropping, job creation opportunities, skill and proficiency required for producing a crop, and risk taken to cultivate a crop were considered as the criteria in the model. Seven alternative crops including rice, wheat, rapeseed, barley, soybean, clover, and vegetables were considered too. The next step is determining the weight of each criterion with regard to the goal and the weight of each alternative with regard to each criteria. By multiplying these weights, final weights for various crops were obtained from the model. Derived weights for each crop were then applied as objective function coefficients in the Linear Programming model and the model was solved subject to the constraints. Results and Discussion: Optimal cropping pattern determined based on the consolidated model of AHP and Linear Programming and the results compared to a scenario that only looks forward to maximizing the economic interests. Due to the low profitability of rapeseed and barley, these crops eliminated from the pattern in the profit-maximizing scenario. According to the results, the
175 Years of Linear Programming
Indian Academy of Sciences (India)
Vijay Chandru1 M R Rao2. Computer Science and Automation, Indian Institute of Science, Bangalore 560 012; Director, Indian Institute of Management, Bannerghatta Road, Bangalore 560 076. Resonance – Journal of Science Education. Current Issue : Vol. 22, Issue 12. Current Issue Volume 22 | Issue 12. December ...
175 Years of Linear Programming
Indian Academy of Sciences (India)
Hence, Ram's best strategy has to be to cut the cake into two equal pieces and thus minimise the maximum share of cake that Shyam gets. The game can be represented by the matrix below, whose entries are the payoff to Shyam (his share of the cake). If Shyam had to declare his str~tegy first, the outcome would not be any ...
Cubesat Proximity Operations Demonstration (CPOD)
Villa, Marco; Martinez, Andres; Petro, Andrew
2015-01-01
The CubeSat Proximity Operations Demonstration (CPOD) project will demonstrate rendezvous, proximity operations and docking (RPOD) using two 3-unit (3U) CubeSats. Each CubeSat is a satellite with the dimensions 4 inches x 4 inches x 13 inches (10 centimeters x 10 centimeters x 33 centimeters) and weighing approximately 11 pounds (5 kilograms). This flight demonstration will validate and characterize many new miniature low-power proximity operations technologies applicable to future missions. This mission will advance the state of the art in nanosatellite attitude determination,navigation and control systems, in addition to demonstrating relative navigation capabilities.The two CPOD satellites are scheduled to be launched together to low-Earth orbit no earlier than Dec. 1, 2015.
SHORT COMMUNICATION PROXIMATE COMPOSITION, MINERAL ...
African Journals Online (AJOL)
Preferred Customer
SHORT COMMUNICATION. PROXIMATE COMPOSITION, MINERAL CONTENT AND ANTINUTRITIONAL. FACTORS OF SOME CAPSICUM (Capsicum annum) VARIETIES GROWN IN. ETHIOPIA. Esayas K.1, Shimelis A.2, Ashebir F.3, Negussie R.3, Tilahun B.4 and Gulelat D.4*. 1Hawassa University, Department of Food ...
Directory of Open Access Journals (Sweden)
Baofeng Cai
2017-08-01
Full Text Available The Interconnected River System Network Project (IRSNP is a significant water supply engineering project, which is capable of effectively utilizing flood resources to generate ecological value, by connecting 198 lakes and ponds in western Jilin, northeast China. In this article, an optimization research approach has been proposed to maximize the incremental value of IRSNP ecosystem services. A double-sided chance-constrained integer linear program (DCCILP method has been proposed to support the optimization, which can deal with uncertainties presented as integers or random parameters that appear on both sides of the decision variable at the same time. The optimal scheme indicates that after rational optimization, the total incremental value of ecosystem services from the interconnected river system network project increased 22.25%, providing an increase in benefits of 3.26 × 109 ¥ compared to the original scheme. Most of the functional area is swamp wetland, which provides the greatest ecological benefits. Adjustment services increased obviously, implying that the optimization scheme prioritizes ecological benefits rather than supply and production services.
Ohno, Hajime; Matsubae, Kazuyo; Nakajima, Kenichi; Kondo, Yasushi; Nakamura, Shinichiro; Fukushima, Yasuhiro; Nagasaka, Tetsuya
2017-11-21
Importance of end-of-life vehicles (ELVs) as an urban mine is expected to grow, as more people in developing countries are experiencing increased standards of living, while the automobiles are increasingly made using high-quality materials to meet stricter environmental and safety requirements. While most materials in ELVs, particularly steel, have been recycled at high rates, quality issues have not been adequately addressed due to the complex use of automobile materials, leading to considerable losses of valuable alloying elements. This study highlights the maximal potential of quality-oriented recycling of ELV steel, by exploring the utilization methods of scrap, sorted by parts, to produce electric-arc-furnace-based crude alloy steel with minimal losses of alloying elements. Using linear programming on the case of Japanese economy in 2005, we found that adoption of parts-based scrap sorting could result in the recovery of around 94-98% of the alloying elements occurring in parts scrap (manganese, chromium, nickel, and molybdenum), which may replace 10% of the virgin sources in electric arc furnace-based crude alloy steel production.
Zhang, Liping; Zhang, Shiwen; Huang, Yajie; Cao, Meng; Huang, Yuanfang; Zhang, Hongyan
2016-03-24
Understanding abandoned mine land (AML) changes during land reclamation is crucial for reusing damaged land resources and formulating sound ecological restoration policies. This study combines the linear programming (LP) model and the CLUE-S model to simulate land-use dynamics in the Mentougou District (Beijing, China) from 2007 to 2020 under three reclamation scenarios, that is, the planning scenario based on the general land-use plan in study area (scenario 1), maximal comprehensive benefits (scenario 2), and maximal ecosystem service value (scenario 3). Nine landscape-scale graph metrics were then selected to describe the landscape characteristics. The results show that the coupled model presented can simulate the dynamics of AML effectively and the spatially explicit transformations of AML were different. New cultivated land dominates in scenario 1, while construction land and forest land account for major percentages in scenarios 2 and 3, respectively. Scenario 3 has an advantage in most of the selected indices as the patches combined most closely. To conclude, reclaiming AML by transformation into more forest can reduce the variability and maintain the stability of the landscape ecological system in study area. These findings contribute to better mapping AML dynamics and providing policy support for the management of AML.
Borbulevych, Oleg Y; Plumley, Joshua A; Martin, Roger I; Merz, Kenneth M; Westerhoff, Lance M
2014-05-01
Macromolecular crystallographic refinement relies on sometimes dubious stereochemical restraints and rudimentary energy functionals to ensure the correct geometry of the model of the macromolecule and any covalently bound ligand(s). The ligand stereochemical restraint file (CIF) requires a priori understanding of the ligand geometry within the active site, and creation of the CIF is often an error-prone process owing to the great variety of potential ligand chemistry and structure. Stereochemical restraints have been replaced with more robust functionals through the integration of the linear-scaling, semiempirical quantum-mechanics (SE-QM) program DivCon with the PHENIX X-ray refinement engine. The PHENIX/DivCon package has been thoroughly validated on a population of 50 protein-ligand Protein Data Bank (PDB) structures with a range of resolutions and chemistry. The PDB structures used for the validation were originally refined utilizing various refinement packages and were published within the past five years. PHENIX/DivCon does not utilize CIF(s), link restraints and other parameters for refinement and hence it does not make as many a priori assumptions about the model. Across the entire population, the method results in reasonable ligand geometries and low ligand strains, even when the original refinement exhibited difficulties, indicating that PHENIX/DivCon is applicable to both single-structure and high-throughput crystallography.
LINEAR - DERIVATION AND DEFINITION OF A LINEAR AIRCRAFT MODEL
Duke, E. L.
1994-01-01
The Derivation and Definition of a Linear Model program, LINEAR, provides the user with a powerful and flexible tool for the linearization of aircraft aerodynamic models. LINEAR was developed to provide a standard, documented, and verified tool to derive linear models for aircraft stability analysis and control law design. Linear system models define the aircraft system in the neighborhood of an analysis point and are determined by the linearization of the nonlinear equations defining vehicle dynamics and sensors. LINEAR numerically determines a linear system model using nonlinear equations of motion and a user supplied linear or nonlinear aerodynamic model. The nonlinear equations of motion used are six-degree-of-freedom equations with stationary atmosphere and flat, nonrotating earth assumptions. LINEAR is capable of extracting both linearized engine effects, such as net thrust, torque, and gyroscopic effects and including these effects in the linear system model. The point at which this linear model is defined is determined either by completely specifying the state and control variables, or by specifying an analysis point on a trajectory and directing the program to determine the control variables and the remaining state variables. The system model determined by LINEAR consists of matrices for both the state and observation equations. The program has been designed to provide easy selection of state, control, and observation variables to be used in a particular model. Thus, the order of the system model is completely under user control. Further, the program provides the flexibility of allowing alternate formulations of both the state and observation equations. Data describing the aircraft and the test case is input to the program through a terminal or formatted data files. All data can be modified interactively from case to case. The aerodynamic model can be defined in two ways: a set of nondimensional stability and control derivatives for the flight point of
Bourlès, Henri
2013-01-01
Linear systems have all the necessary elements (modeling, identification, analysis and control), from an educational point of view, to help us understand the discipline of automation and apply it efficiently. This book is progressive and organized in such a way that different levels of readership are possible. It is addressed both to beginners and those with a good understanding of automation wishing to enhance their knowledge on the subject. The theory is rigorously developed and illustrated by numerous examples which can be reproduced with the help of appropriate computation software. 60 exe
Linearly Adjustable International Portfolios
Fonseca, R. J.; Kuhn, D.; Rustem, B.
2010-09-01
We present an approach to multi-stage international portfolio optimization based on the imposition of a linear structure on the recourse decisions. Multiperiod decision problems are traditionally formulated as stochastic programs. Scenario tree based solutions however can become intractable as the number of stages increases. By restricting the space of decision policies to linear rules, we obtain a conservative tractable approximation to the original problem. Local asset prices and foreign exchange rates are modelled separately, which allows for a direct measure of their impact on the final portfolio value.
Photoactivated In Vivo Proximity Labeling.
Beck, David B; Bonasio, Roberto
2017-06-19
Identification of molecular interactions is paramount to understanding how cells function. Most available technologies rely on co-purification of a protein of interest and its binding partners. Therefore, they are limited in their ability to detect low-affinity interactions and cannot be applied to proteins that localize to difficult-to-solubilize cellular compartments. In vivo proximity labeling (IPL) overcomes these obstacles by covalently tagging proteins and RNAs based on their proximity in vivo to a protein of interest. In IPL, a heterobifunctional probe comprising a photoactivatable moiety and biotin is recruited by a monomeric streptavidin tag fused to a protein of interest. Following UV irradiation, candidate interacting proteins and RNAs are covalently biotinylated with tight spatial and temporal control and subsequently recovered using biotin as an affinity handle. Here, we describe experimental protocols to discover novel protein-protein and protein-RNA interactions using IPL. © 2017 by John Wiley & Sons, Inc. Copyright © 2017 John Wiley & Sons, Inc.
Li, Yuan H.; Yang, Yu N.; Tompkins, Leroy J.; Modarresi, Shahpar
2005-01-01
The statistical technique, "Zero-One Linear Programming," that has successfully been used to create multiple tests with similar characteristics (e.g., item difficulties, test information and test specifications) in the area of educational measurement, was deemed to be a suitable method for creating multiple sets of matched samples to be…
Prox-1 Automated Proximity Operations
2016-01-13
on demonstrating the functionality required to meet minimum mission success criteria. The minimum mission includes on- orbit spacecraft checkout of...also includes deployment of LightSail-B from the P-POD, and imaging of LightSail-B for 20 minutes as it recedes from Prox-1. small satellite ; proximity...criteria. The minimum mission includes on- orbit spacecraft checkout of all spacecraft subsystems, including flight qualification of the following new
Talsma, Elise F; Borgonjen-van den Berg, Karin J; Melse-Boonstra, Alida; Mayer, Eva V; Verhoef, Hans; Demir, Ayşe Y; Ferguson, Elaine L; Kok, Frans J; Brouwer, Inge D
2018-02-01
Introduction of biofortified cassava as school lunch can increase vitamin A intake, but may increase risk of other deficiencies due to poor nutrient profile of cassava. We assessed the potential effect of introducing a yellow cassava-based school lunch combined with additional food-based recommendations (FBR) on vitamin A and overall nutrient adequacy using Optifood (linear programming tool). Cross-sectional study to assess dietary intakes (24 h recall) and derive model parameters (list of foods consumed, median serving sizes, food and food (sub)group frequency distributions, food cost). Three scenarios were modelled, namely daily diet including: (i) no school lunch; (ii) standard 5d school lunch with maize/beans; and (iii) 5d school lunch with yellow cassava. Each scenario and scenario 3 with additional FBR were assessed on overall nutrient adequacy using recommended nutrient intakes (RNI). Eastern Kenya. Primary-school children (n 150) aged 7-9 years. Best food pattern of yellow cassava-based lunch scenario achieved 100 % RNI for six nutrients compared with no lunch (three nutrients) or standard lunch (five nutrients) scenario. FBR with yellow cassava and including small dried fish improved nutrient adequacy, but could not ensure adequate intake of fat (52 % of average requirement), riboflavin (50 % RNI), folate (59 % RNI) and vitamin A (49 % RNI). Introduction of yellow cassava-based school lunch complemented with FBR potentially improved vitamin A adequacy, but alternative interventions are needed to ensure dietary adequacy. Optifood is useful to assess potential contribution of a biofortified crop to nutrient adequacy and to develop additional FBR to address remaining nutrient gaps.
Zaghian, Maryam; Cao, Wenhua; Liu, Wei; Kardar, Laleh; Randeniya, Sharmalee; Mohan, Radhe; Lim, Gino
2017-03-01
Robust optimization of intensity-modulated proton therapy (IMPT) takes uncertainties into account during spot weight optimization and leads to dose distributions that are resilient to uncertainties. Previous studies demonstrated benefits of linear programming (LP) for IMPT in terms of delivery efficiency by considerably reducing the number of spots required for the same quality of plans. However, a reduction in the number of spots may lead to loss of robustness. The purpose of this study was to evaluate and compare the performance in terms of plan quality and robustness of two robust optimization approaches using LP and nonlinear programming (NLP) models. The so-called "worst case dose" and "minmax" robust optimization approaches and conventional planning target volume (PTV)-based optimization approach were applied to designing IMPT plans for five patients: two with prostate cancer, one with skull-based cancer, and two with head and neck cancer. For each approach, both LP and NLP models were used. Thus, for each case, six sets of IMPT plans were generated and assessed: LP-PTV-based, NLP-PTV-based, LP-worst case dose, NLP-worst case dose, LP-minmax, and NLP-minmax. The four robust optimization methods behaved differently from patient to patient, and no method emerged as superior to the others in terms of nominal plan quality and robustness against uncertainties. The plans generated using LP-based robust optimization were more robust regarding patient setup and range uncertainties than were those generated using NLP-based robust optimization for the prostate cancer patients. However, the robustness of plans generated using NLP-based methods was superior for the skull-based and head and neck cancer patients. Overall, LP-based methods were suitable for the less challenging cancer cases in which all uncertainty scenarios were able to satisfy tight dose constraints, while NLP performed better in more difficult cases in which most uncertainty scenarios were hard to meet
Lopez, Cesar
2014-01-01
MATLAB is a high-level language and environment for numerical computation, visualization, and programming. Using MATLAB, you can analyze data, develop algorithms, and create models and applications. The language, tools, and built-in math functions enable you to explore multiple approaches and reach a solution faster than with spreadsheets or traditional programming languages, such as C/C++ or Java. MATLAB Linear Algebra introduces you to the MATLAB language with practical hands-on instructions and results, allowing you to quickly achieve your goals. In addition to giving an introduction to
PROXIMATE AND ELEMENTAL COMPOSITION OF WHITE GRUBS
African Journals Online (AJOL)
DR. AMINU
PROXIMATE AND ELEMENTAL COMPOSITION OF WHITE GRUBS. 1 Alhassan, A. J. 1M .S. Sule, 1J. ... ABSTRACT. This study determined the proximate and mineral element composition of whole white grubs using standard methods of analysis. Proximate ... days, before pulverized to powder and kept in plastic container.
Fahmida, Umi; Kolopaking, Risatianti; Santika, Otte; Sriani, Sriani; Umar, Jahja; Htet, Min Kyaw; Ferguson, Elaine
2015-03-01
Complementary feeding recommendations (CFRs) with the use of locally available foods can be developed by using linear programming (LP). Although its potential has been shown for planning phases of food-based interventions, the effectiveness in the community setting has not been tested to our knowledge. We aimed to assess effectiveness of promoting optimized CFRs for improving maternal knowledge, feeding practices, and child intakes of key problem nutrients (calcium, iron, niacin, and zinc). A community-intervention trial with a quasi-experimental design was conducted in East Lombok, West Nusa Tenggara Province, Indonesia, on children aged 9-16 mo at baseline. A CFR group (n = 240) was compared with a non-CFR group (n = 215). The CFRs, which were developed using LP, were promoted in an intervention that included monthly cooking sessions and weekly home visits. The mother's nutrition knowledge and her child's feeding practices and the child's nutrient intakes were measured before and after the 6-mo intervention by using a structured interview, 24-h recall, and 1-wk food-frequency questionnaire. The CFR intervention improved mothers' knowledge and children's feeding practices and improved children's intakes of calcium, iron, and zinc. At the end line, median (IQR) nutrient densities were significantly higher in the CFR group than in the non-CFR group for iron [i.e., 0.6 mg/100 kcal (0.4-0.8 mg/100 kcal) compared with 0.5 mg/100 kcal (0.4-0.7 mg/100 kcal)] and niacin [i.e., 0.8 mg/100 kcal (0.5-1.0 mg/100 kcal) compared with 0.6 mg/100 kcal (0.4-0.8 mg/100 kcal)]. However, median nutrient densities for calcium, iron, niacin, and zinc in the CFR group (23, 0.6, 0.7, and 0.5 mg/100 kcal, respectively) were still below desired densities (63, 1.0, 0.9, and 0.6 mg/100 kcal, respectively). The CFRs significantly increased intakes of calcium, iron, niacin, and zinc, but nutrient densities were still below desired nutrient densities. When the adoption of optimized CFRs is
Skau, Jutta K H; Bunthang, Touch; Chamnan, Chhoun; Wieringa, Frank T; Dijkhuizen, Marjoleine A; Roos, Nanna; Ferguson, Elaine L
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. This study discusses the use of Optifood for predicting whether formulated complementary food (CF) products can ensure dietary adequacy for target populations in Cambodia. Dietary data were collected by 24-h recall in a cross-sectional survey of 6- to 11-mo-old infants (n = 78). LP model parameters were derived from these data, including a list of foods, median serving sizes, and dietary patterns. Five series of LP analyses were carried out to model the target population's baseline diet and 4 formulated CF products [WinFood (WF), WinFood-Lite (WF-L), Corn-Soy-Blend Plus (CSB+), and Corn-Soy-Blend Plus Plus (CSB++)], which were added to the diet in portions of 33 g/d dry weight (DW) for infants aged 6-8 mo and 40 g/d DW for infants aged 9-11 mo. In each series of analyses, the nutritionally optimal diet and theoretical range, in diet nutrient contents, were determined. The LP analysis showed that baseline diets could not achieve the Recommended Nutrient Intake (RNI) for thiamin, riboflavin, niacin, folate, vitamin B-12, calcium, iron, and zinc (range: 14-91% of RNI in the optimal diets) and that none of the formulated CF products could cover the nutrient gaps for thiamin, niacin, iron, and folate (range: 22-86% of the RNI). Iron was the key limiting nutrient, for all modeled diets, achieving a maximum of only 48% of the RNI when CSB++ was included in the diet. Only WF and WF-L filled the nutrient gap for calcium. WF-L, CSB+, and CSB++ filled the nutrient gap for zinc (9- to 11-mo-olds). The formulated CF products improved the nutrient adequacy of complementary feeding diets but could not entirely cover the nutrient gaps. These results emphasize the value of using LP to evaluate special CF products during the intervention planning phase. The WF study was registered at controlled-trials.com as ISRCTN19918531.
Finger Proximal Interphalangeal Joint Dislocation.
Ramponi, Denise; Cerepani, Mary Jo
2015-01-01
Finger dislocations are common injuries that are often managed by emergency nurse practitioners. A systematic physical examination following these injuries is imperative to avoid complications. Radiographic views, including the anteroposterior, lateral, and oblique views, are imperative to evaluate these finger dislocations. A dorsal dislocation of the proximal interphalangeal (PIP) joint is the most common finger dislocation type often easily reduced. A volar PIP dislocation can often be difficult to reduce and may result in finger deformity. Finger dislocations should be reduced promptly. Referral to an orthopedic hand specialist is required if the dislocation is unable to be reduced or if the finger joint is unstable following reduction attempts.
Equilibrium properties of proximity effect
Energy Technology Data Exchange (ETDEWEB)
Esteve, D.; Pothier, H.; Gueron, S.; Birge, N.O.; Devoret, M.
1996-12-31
The proximity effect in diffusive normal-superconducting (NS) nano-structures is described by the Usadel equations for the electron pair correlations. We show that these equations obey a variational principle with a potential which generalizes the Ginzburg-Landau energy functional. We discuss simple examples of NS circuits using this formalism. In order to test the theoretical predictions of the Usadel equations, we have measured the density of states as a function of energy on a long N wire in contact with a S wire at one end, at different distances from the NS interface. (authors). 12 refs.
Metternicht, Graciela; Blanco, Paula; del Valle, Hector; Laterra, Pedro; Hardtke, Leonardo; Bouza, Pablo
2015-04-01
Wildlife is part of the Patagonian rangelands sheep farming environment, with the potential of providing extra revenue to livestock owners. As sheep farming became less profitable, farmers and ranchers could focus on sustainable wildlife harvesting. It has been argued that sustainable wildlife harvesting is ecologically one of the most rational forms of land use because of its potential to provide multiple products of high value, while reducing pressure on ecosystems. The guanaco (Lama guanicoe) is the most conspicuous wild ungulate of Patagonia. Guanaco ?bre, meat, pelts and hides are economically valuable and have the potential to be used within the present Patagonian context of production systems. Guanaco populations in South America, including Patagonia, have experienced a sustained decline. Causes for this decline are related to habitat alteration, competition for forage with sheep, and lack of reasonable management plans to develop livelihoods for ranchers. In this study we propose an approach to explicitly determinate optimal stocking rates based on trade-offs between guanaco density and livestock grazing intensity on rangelands. The focus of our research is on finding optimal sheep stocking rates at paddock level, to ensure the highest production outputs while: a) meeting requirements of sustainable conservation of guanacos over their minimum viable population; b) maximizing soil carbon sequestration, and c) minimizing soil erosion. In this way, determination of optimal stocking rate in rangelands becomes a multi-objective optimization problem that can be addressed using a Fuzzy Multi-Objective Linear Programming (MOLP) approach. Basically, this approach converts multi-objective problems into single-objective optimizations, by introducing a set of objective weights. Objectives are represented using fuzzy set theory and fuzzy memberships, enabling each objective function to adopt a value between 0 and 1. Each objective function indicates the satisfaction of
Complications in proximal humeral fractures.
Calori, Giorgio Maria; Colombo, Massimiliano; Bucci, Miguel Simon; Fadigati, Piero; Colombo, Alessandra Ines Maria; Mazzola, Simone; Cefalo, Vittorio; Mazza, Emilio
2016-10-01
Necrosis of the humeral head, infections and non-unions are among the most dangerous and difficult-to-treat complications of proximal humeral fractures. The aim of this work was to analyse in detail non-unions and post-traumatic bone defects and to suggest an algorithm of care. Treatment options are based not only on the radiological frame, but also according to a detailed analysis of the patient, who is classified using a risk factor analysis. This method enables the surgeon to choose the most suitable treatment for the patient, thereby facilitating return of function in the shortest possible time. The treatment of such serious complications requires the surgeon to be knowledgeable about the following possible solutions: increased mechanical stability; biological stimulation; and reconstructive techniques in two steps, with application of biotechnologies and prosthetic substitution. Copyright © 2016 Elsevier Ltd. All rights reserved.
Linear Algebra and Smarandache Linear Algebra
Vasantha, Kandasamy
2003-01-01
The present book, on Smarandache linear algebra, not only studies the Smarandache analogues of linear algebra and its applications, it also aims to bridge the need for new research topics pertaining to linear algebra, purely in the algebraic sense. We have introduced Smarandache semilinear algebra, Smarandache bilinear algebra and Smarandache anti-linear algebra and their fuzzy equivalents. Moreover, in this book, we have brought out the study of linear algebra and ve...
Energy Technology Data Exchange (ETDEWEB)
Miller, Naomi J.; Perrin, Tess E.; Royer, Michael P.; Wilkerson, Andrea M.; Beeson, Tracy A.
2014-05-20
Although lensed troffers are numerous, there are many other types of optical systems as well. This report looked at the performance of three linear (T8) LED lamps chosen primarily based on their luminous intensity distributions (narrow, medium, and wide beam angles) as well as a benchmark fluorescent lamp in five different troffer types. Also included are the results of a subjective evaluation. Results show that linear (T8) LED lamps can improve luminaire efficiency in K12-lensed and parabolic-louvered troffers, effect little change in volumetric and high-performance diffuse-lensed type luminaires, but reduce efficiency in recessed indirect troffers. These changes can be accompanied by visual appearance and visual comfort consequences, especially when LED lamps with clear lenses and narrow distributions are installed. Linear (T8) LED lamps with diffuse apertures exhibited wider beam angles, performed more similarly to fluorescent lamps, and received better ratings from observers. Guidance is provided on which luminaires are the best candidates for retrofitting with linear (T8) LED lamps.
Proximity sensor technology for manipulator end effectors
Johnston, A. R.
1975-01-01
Optical proximity sensing techniques which could be used to help control the critical grasping phase of a remote manipulation are described. The proximity sensors described use a triangulation geometry to detect a surface located in a pre-determined region. The design of the proximity sensors themselves is discussed, as well as their application to manipulator control with a local control loop, and possibilities for future development are discussed.
Scaffolding, the zone of proximal development, and novice programmers
Directory of Open Access Journals (Sweden)
Nadia Kastro Awbi
Full Text Available The work reported here is part of a larger research program that aims to explore the learning strategies that novice computer programmers adopt, the ways in which they integrate knowledge, and the processes they employ when applying their knowledge and skills in different contexts. Our findings, based on a narrative analysis of think-aloud retrospective interviews, indicate that scaffolding can influence progression in learning and can extend a student\\'s zone of proximal development (Vygotsky, 1978.
Proximate composition and antinutrient content of pumpkin ...
African Journals Online (AJOL)
Proximate composition and antinutrient content of pumpkin ( Cucurbita pepo ) and sorghum ( Sorghum bicolor ) flour blends fermented with Lactobacillus plantarum , Aspergillus niger and Bacillus subtilis.
Thyagarajan David; Haridas Samarth; Jones Denise; Dent Colin; Evans Richard; Williams Rhys
2009-01-01
Aim: To assess the functional outcome following internal fixation with the PHILOS (proximal humeral interlocking system) for displaced proximal humeral fractures. Patients and Methods: We reviewed 30 consecutive patients treated surgically with the proximal humeral locking plate for a displaced proximal humeral fracture. Functional outcome was determined using the American Shoulder and Elbow Society (ASES) score and Constant Murley score. Results: Average age of the patients was 58 years...
Best Proximity Points for a New Class of Generalized Proximal Mappings
Directory of Open Access Journals (Sweden)
Tayyab Kamran
2017-03-01
Full Text Available The best proximity points are usually used to find the optimal approximate solution of the operator equation Tx = x, when T has no fixed point. In this paper, we prove some best proximity point theorems for nonself multivalued operators, following the foot steps of Basha and Shahzad [Best proximity point theorems for generalized proximal contractions, Fixed Point Theory Appl., 2012, 2012:42].
Preliminary phytochemical screening, proximate and elemental ...
African Journals Online (AJOL)
The seed powder of Moringa oleifera was analysed for its phytochemical, proximate and elemental composition using Folin-Denis spectrophotometric method, gravimetric method and energy dispersing X-ray fluorescence (EDXRF) transmission emission technique respectively. The seed powder had the following proximate ...
Bimalleolar ankle fracture with proximal fibular fracture
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
Grouping by Proximity in Haptic Contour Detection
Overvliet, Krista E.; Krampe, Ralf Th.; Wagemans, Johan
2013-01-01
We investigated the applicability of the Gestalt principle of perceptual grouping by proximity in the haptic modality. To do so, we investigated the influence of element proximity on haptic contour detection. In the course of four sessions ten participants performed a haptic contour detection task in which they freely explored a haptic random dot display that contained a contour in 50% of the trials. A contour was defined by a higher density of elements (raised dots), relative to the background surface. Proximity of the contour elements as well as the average proximity of background elements was systematically varied. We hypothesized that if proximity of contour elements influences haptic contour detection, detection will be more likely when contour elements are in closer proximity. This should be irrespective of the ratio with the proximity of the background elements. Results showed indeed that the closer the contour elements were, the higher the detection rates. Moreover, this was the case independent of the contour/background ratio. We conclude that the Gestalt law of proximity applies to haptic contour detection. PMID:23762364
Proximate analysis on four edible mushrooms ADEDAYO ...
African Journals Online (AJOL)
Michael Horsfall
Vol. 15 (1) 9 - 11. Full-text Available Online at www.bioline.org.br/ja. Proximate analysis on four edible mushrooms. ADEDAYO, MAJEKODUNMI RACHEL. Nigerian Stored Product Research Institute, P.M.B.3032, Kano. ABSTRACT: Proximate study was conducted on four edible mushrooms commonly found in farmlands in.
Proximate Sources of Collective Teacher Efficacy
Adams, Curt M.; Forsyth, Patrick B.
2006-01-01
Purpose: Recent scholarship has augmented Bandura's theory underlying efficacy formation by pointing to more proximate sources of efficacy information involved in forming collective teacher efficacy. These proximate sources of efficacy information theoretically shape a teacher's perception of the teaching context, operationalizing the difficulty…