Fuzzy Multi-objective Linear Programming Approach
Directory of Open Access Journals (Sweden)
Amna Rehmat
2007-07-01
Full Text Available Traveling salesman problem (TSP is one of the challenging real-life problems, attracting researchers of many fields including Artificial Intelligence, Operations Research, and Algorithm Design and Analysis. The problem has been well studied till now under different headings and has been solved with different approaches including genetic algorithms and linear programming. Conventional linear programming is designed to deal with crisp parameters, but information about real life systems is often available in the form of vague descriptions. Fuzzy methods are designed to handle vague terms, and are most suited to finding optimal solutions to problems with vague parameters. Fuzzy multi-objective linear programming, an amalgamation of fuzzy logic and multi-objective linear programming, deals with flexible aspiration levels or goals and fuzzy constraints with acceptable deviations. In this paper, a methodology, for solving a TSP with imprecise parameters, is deployed using fuzzy multi-objective linear programming. An example of TSP with multiple objectives and vague parameters is discussed.
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 ...
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.
An Approach for Solving Linear Fractional Programming Problems
Andrew Oyakhobo Odior
2012-01-01
Linear fractional programming problems are useful tools in production planning, financial and corporate planning, health care and hospital planning and as such have attracted considerable research interest. The paper presents a new approach for solving a fractional linear programming problem in which the objective function is a linear fractional function, while the constraint functions are in the form of linear inequalities. The approach adopted is based mainly upon solving the problem algebr...
An 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 ...
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.
A Fuzzy Linear Programming Approach for Aggregate Production Planning
DEFF Research Database (Denmark)
Iris, Cagatay; Cevikcan, Emre
2014-01-01
a mathematical programming framework for aggregate production planning problem under imprecise data environment. After providing background information about APP problem, together with fuzzy linear programming, the fuzzy linear programming model of APP is solved on an illustrative example for different a...
Discovery of Boolean metabolic networks: integer linear programming based approach.
Qiu, Yushan; Jiang, Hao; Ching, Wai-Ki; Cheng, Xiaoqing
2018-04-11
Traditional drug discovery methods focused on the efficacy of drugs rather than their toxicity. However, toxicity and/or lack of efficacy are produced when unintended targets are affected in metabolic networks. Thus, identification of biological targets which can be manipulated to produce the desired effect with minimum side-effects has become an important and challenging topic. Efficient computational methods are required to identify the drug targets while incurring minimal side-effects. In this paper, we propose a graph-based computational damage model that summarizes the impact of enzymes on compounds in metabolic networks. An efficient method based on Integer Linear Programming formalism is then developed to identify the optimal enzyme-combination so as to minimize the side-effects. The identified target enzymes for known successful drugs are then verified by comparing the results with those in the existing literature. Side-effects reduction plays a crucial role in the study of drug development. A graph-based computational damage model is proposed and the theoretical analysis states the captured problem is NP-completeness. The proposed approaches can therefore contribute to the discovery of drug targets. Our developed software is available at " http://hkumath.hku.hk/~wkc/APBC2018-metabolic-network.zip ".
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.
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 ...
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...
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.
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.
An Instructional Note on Linear Programming--A Pedagogically Sound Approach.
Mitchell, Richard
1998-01-01
Discusses the place of linear programming in college curricula and the advantages of using linear-programming software. Lists important characteristics of computer software used in linear programming for more effective teaching and learning. (ASK)
Mass Optimization of Battery/Supercapacitors Hybrid Systems Based on a Linear Programming Approach
Fleury, Benoit; Labbe, Julien
2014-08-01
The objective of this paper is to show that, on a specific launcher-type mission profile, a 40% gain of mass is expected using a battery/supercapacitors active hybridization instead of a single battery solution. This result is based on the use of a linear programming optimization approach to perform the mass optimization of the hybrid power supply solution.
Korman, Jonathan; McCann, Robert J.; Seis, Christian
2013-01-01
A new approach to linear programming duality is proposed which relies on quadratic penalization, so that the relation between solutions to the penalized primal and dual problems becomes affine. This yields a new proof of Levin's duality theorem for capacity-constrained optimal transport as an infinite-dimensional application.
International Nuclear Information System (INIS)
Romeijn, H Edwin; Ahuja, Ravindra K; Dempsey, James F; Kumar, Arvind; Li, Jonathan G
2003-01-01
We present a novel linear programming (LP) based approach for efficiently solving the intensity modulated radiation therapy (IMRT) fluence-map optimization (FMO) problem to global optimality. Our model overcomes the apparent limitations of a linear-programming approach by approximating any convex objective function by a piecewise linear convex function. This approach allows us to retain the flexibility offered by general convex objective functions, while allowing us to formulate the FMO problem as a LP problem. In addition, a novel type of partial-volume constraint that bounds the tail averages of the differential dose-volume histograms of structures is imposed while retaining linearity as an alternative approach to improve dose homogeneity in the target volumes, and to attempt to spare as many critical structures as possible. The goal of this work is to develop a very rapid global optimization approach that finds high quality dose distributions. Implementation of this model has demonstrated excellent results. We found globally optimal solutions for eight 7-beam head-and-neck cases in less than 3 min of computational time on a single processor personal computer without the use of partial-volume constraints. Adding such constraints increased the running times by a factor of 2-3, but improved the sparing of critical structures. All cases demonstrated excellent target coverage (>95%), target homogeneity (<10% overdosing and <7% underdosing) and organ sparing using at least one of the two models
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.
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.
Reduction of Linear Programming to Linear Approximation
Vaserstein, Leonid N.
2006-01-01
It is well known that every Chebyshev linear approximation problem can be reduced to a linear program. In this paper we show that conversely every linear program can be reduced to a Chebyshev linear approximation problem.
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
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.
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.
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.
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.
A novel approach based on preference-based index for interval bilevel linear programming problem
Directory of Open Access Journals (Sweden)
Aihong Ren
2017-05-01
Full Text Available Abstract This paper proposes a new methodology for solving the interval bilevel linear programming problem in which all coefficients of both objective functions and constraints are considered as interval numbers. In order to keep as much uncertainty of the original constraint region as possible, the original problem is first converted into an interval bilevel programming problem with interval coefficients in both objective functions only through normal variation of interval number and chance-constrained programming. With the consideration of different preferences of different decision makers, the concept of the preference level that the interval objective function is preferred to a target interval is defined based on the preference-based index. Then a preference-based deterministic bilevel programming problem is constructed in terms of the preference level and the order relation ⪯ m w $\\preceq_{mw}$ . Furthermore, the concept of a preference δ-optimal solution is given. Subsequently, the constructed deterministic nonlinear bilevel problem is solved with the help of estimation of distribution algorithm. Finally, several numerical examples are provided to demonstrate the effectiveness of the proposed approach.
International Nuclear Information System (INIS)
Sadeghi, Mehdi; Mirshojaeian Hosseini, Hossein
2006-01-01
For many years, energy models have been used in developed or developing countries to satisfy different needs in energy planning. One of major problems against energy planning and consequently energy models is uncertainty, spread in different economic, political and legal dimensions of energy planning. Confronting uncertainty, energy planners have often used two well-known strategies. The first strategy is stochastic programming, in which energy system planners define different scenarios and apply an explicit probability of occurrence to each scenario. The second strategy is Minimax Regret strategy that minimizes regrets of different decisions made in energy planning. Although these strategies have been used extensively, they could not flexibly and effectively deal with the uncertainties caused by fuzziness. 'Fuzzy Linear Programming (FLP)' is a strategy that can take fuzziness into account. This paper tries to demonstrate the method of application of FLP for optimization of supply energy system in Iran, as a case study. The used FLP model comprises fuzzy coefficients for investment costs. Following the mentioned purpose, it is realized that FLP is an easy and flexible approach that can be a serious competitor for other confronting uncertainties approaches, i.e. stochastic and Minimax Regret strategies. (author)
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.
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.
International Nuclear Information System (INIS)
Rogner, H.H.
1989-01-01
The submitted sections on linear programming are extracted from 'Theorie und Technik der Planung' (1978) by W. Blaas and P. Henseler and reformulated for presentation at the Workshop. They consider a brief introduction to the theory of linear programming and to some essential aspects of the SIMPLEX solution algorithm for the purposes of economic planning processes. 1 fig
A Nutritional Analysis of the Food Basket in BIH: A Linear Programming Approach
Directory of Open Access Journals (Sweden)
Arnaut-Berilo Almira
2017-04-01
Full Text Available This paper presents linear and goal programming optimization models for determining and analyzing the food basket in Bosnia and Herzegovina (BiH in terms of adequate nutritional needs according to World Health Organization (WHO standards and World Bank (WB recommendations. A linear programming (LP model and goal linear programming model (GLP are adequate since price and nutrient contents are linearly related to food weight. The LP model provides information about the minimal value and the structure of the food basket for an average person in BiH based on nutrient needs. GLP models are designed to give us information on minimal deviations from nutrient needs if the budget is fixed. Based on these results, poverty analysis can be performed. The data used for the models consisted of 158 food items from the general consumption of the population of BiH according to COICOP classifications, with average prices in 2015 for these products.
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.
A novel approach based on preference-based index for interval bilevel linear programming problem
Aihong Ren; Yuping Wang; Xingsi Xue
2017-01-01
This paper proposes a new methodology for solving the interval bilevel linear programming problem in which all coefficients of both objective functions and constraints are considered as interval numbers. In order to keep as much uncertainty of the original constraint region as possible, the original problem is first converted into an interval bilevel programming problem with interval coefficients in both objective functions only through normal variation of interval number and chance-constrain...
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.
A linear programming approach to max-sum problem: a review.
Werner, Tomás
2007-07-01
The max-sum labeling problem, defined as maximizing a sum of binary (i.e., pairwise) functions of discrete variables, is a general NP-hard optimization problem with many applications, such as computing the MAP configuration of a Markov random field. We review a not widely known approach to the problem, developed by Ukrainian researchers Schlesinger et al. in 1976, and show how it contributes to recent results, most importantly, those on the convex combination of trees and tree-reweighted max-product. In particular, we review Schlesinger et al.'s upper bound on the max-sum criterion, its minimization by equivalent transformations, its relation to the constraint satisfaction problem, the fact that this minimization is dual to a linear programming relaxation of the original problem, and the three kinds of consistency necessary for optimality of the upper bound. We revisit problems with Boolean variables and supermodular problems. We describe two algorithms for decreasing the upper bound. We present an example application for structural image analysis.
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
Brameier, Markus
2007-01-01
Presents a variant of Genetic Programming that evolves imperative computer programs as linear sequences of instructions, in contrast to the more traditional functional expressions or syntax trees. This book serves as a reference for researchers, but also contains sufficient introduction for students and those who are new to the field
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).
An Improved Search Approach for Solving Non-Convex Mixed-Integer Non Linear Programming Problems
Sitopu, Joni Wilson; Mawengkang, Herman; Syafitri Lubis, Riri
2018-01-01
The nonlinear mathematical programming problem addressed in this paper has a structure characterized by a subset of variables restricted to assume discrete values, which are linear and separable from the continuous variables. The strategy of releasing nonbasic variables from their bounds, combined with the “active constraint” method, has been developed. This strategy is used to force the appropriate non-integer basic variables to move to their neighbourhood integer points. Successful implementation of these algorithms was achieved on various test problems.
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.
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...
Impulsive Control for Continuous-Time Markov Decision Processes: A Linear Programming Approach
Energy Technology Data Exchange (ETDEWEB)
Dufour, F., E-mail: dufour@math.u-bordeaux1.fr [Bordeaux INP, IMB, UMR CNRS 5251 (France); Piunovskiy, A. B., E-mail: piunov@liv.ac.uk [University of Liverpool, Department of Mathematical Sciences (United Kingdom)
2016-08-15
In this paper, we investigate an optimization problem for continuous-time Markov decision processes with both impulsive and continuous controls. We consider the so-called constrained problem where the objective of the controller is to minimize a total expected discounted optimality criterion associated with a cost rate function while keeping other performance criteria of the same form, but associated with different cost rate functions, below some given bounds. Our model allows multiple impulses at the same time moment. The main objective of this work is to study the associated linear program defined on a space of measures including the occupation measures of the controlled process and to provide sufficient conditions to ensure the existence of an optimal control.
A Mixed Integer Linear Programming Approach to Electrical Stimulation Optimization Problems.
Abouelseoud, Gehan; Abouelseoud, Yasmine; Shoukry, Amin; Ismail, Nour; Mekky, Jaidaa
2018-02-01
Electrical stimulation optimization is a challenging problem. Even when a single region is targeted for excitation, the problem remains a constrained multi-objective optimization problem. The constrained nature of the problem results from safety concerns while its multi-objectives originate from the requirement that non-targeted regions should remain unaffected. In this paper, we propose a mixed integer linear programming formulation that can successfully address the challenges facing this problem. Moreover, the proposed framework can conclusively check the feasibility of the stimulation goals. This helps researchers to avoid wasting time trying to achieve goals that are impossible under a chosen stimulation setup. The superiority of the proposed framework over alternative methods is demonstrated through simulation examples.
Linear programming: an alternative approach for developing formulations for emergency food products.
Sheibani, Ershad; Dabbagh Moghaddam, Arasb; Sharifan, Anousheh; Afshari, Zahra
2018-03-01
To minimize the mortality rates of individuals affected by disasters, providing high-quality food relief during the initial stages of an emergency is crucial. The goal of this study was to develop a formulation for a high-energy, nutrient-dense prototype using linear programming (LP) model as a novel method for developing formulations for food products. The model consisted of the objective function and the decision variables, which were the formulation costs and weights of the selected commodities, respectively. The LP constraints were the Institute of Medicine and the World Health Organization specifications of the content of nutrients in the product. Other constraints related to the product's sensory properties were also introduced to the model. Nonlinear constraints for energy ratios of nutrients were linearized to allow their use in the LP. Three focus group studies were conducted to evaluate the palatability and other aspects of the optimized formulation. New constraints were introduced to the LP model based on the focus group evaluations to improve the formulation. LP is an appropriate tool for designing formulations of food products to meet a set of nutritional requirements. This method is an excellent alternative to the traditional 'trial and error' method in designing formulations. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.
Energy Technology Data Exchange (ETDEWEB)
Jana, C. [Indian Inst. of Social Welfare and Business Management, Kolkata (India); Chattopadhyay, R.N. [Indian Inst. of Technology, Kharagpur (India). Rural Development Centre
2004-09-01
Creating provisions for domestic lighting is important for rural development. Its significance in rural economy is unquestionable since some activities, like literacy, education and manufacture of craft items and other cottage products are largely dependent on domestic lighting facilities for their progress and prosperity. Thus, in rural energy planning, domestic lighting remains a key sector for allocation of investments. For rational allocation, decision makers need alternative strategies for identifying adequate and proper investment structure corresponding to appropriate sources and precise devices. The present study aims at designing a model of energy utilisation by developing a decision support frame for an optimised solution to the problem, taking into consideration four sources and six devices suitable for the study area, namely Narayangarh Block of Midnapore District in India. Since the data available from rural and unorganised sectors are often ill-defined and subjective in nature, many coefficients are fuzzy numbers, and hence several constraints appear to be fuzzy expressions. In this study, the energy allocation model is initiated with three separate objectives for optimisation, namely minimising the total cost, minimising the use of non-local sources of energy and maximising the overall efficiency of the system. Since each of the above objective-based solutions has relevance to the needs of the society and economy, it is necessary to build a model that makes a compromise among the three individual solutions. This multi-objective fuzzy linear programming (MOFLP) model, solved in a compromising decision support frame, seems to be a more rational alternative than single objective linear programming model in rural energy planning. (author)
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.
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...
International Nuclear Information System (INIS)
Nixon, J.D.
2016-01-01
This paper presents a method for optimising the design parameters of an anaerobic digestion (AD) system by using first-order kinetics and multi-objective non-linear goal programming. A model is outlined that determines the ideal operating tank temperature and hydraulic retention time, based on objectives for minimising levelised cost of electricity, and maximising energy potential and feedstock mass reduction. The model is demonstrated for a continuously stirred tank reactor processing food waste in two case study locations. These locations are used to investigate the influence of different environmental and economic climates on optimal conditions. A sensitivity analysis is performed to further examine the variation in optimal results for different financial assumptions and objective weightings. The results identify the conditions for the preferred tank temperature to be in the psychrophilic, mesophilic or thermophilic range. For a tank temperature of 35 °C, ideal hydraulic retention times, in terms of achieving a minimum levelised electricity cost, were found to range from 29.9 to 33 days. Whilst there is a need for more detailed information on rate constants for use in first-order models, multi-objective optimisation modelling is considered to be a promising option for AD design. - Highlights: • Nonlinear goal programming is used to optimise anaerobic digestion systems. • Multiple objectives are set including minimising the levelised cost of electricity. • A model is developed and applied to case studies for the UK and India. • Optimal decisions are made for tank temperature and retention time. • A sensitivity analysis is carried out to investigate different model objectives.
Shea, John E.
from a catalog of courses is difficult because of the many factors being considered. To assist this process, the multi-objective model and the curriculum requirements were incorporated in a linear program to select the "optimum" curriculum. The application of this tool was also beneficial in identifying the active constraints that limit curriculum development and content.
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…
Joint shape segmentation with linear programming
Huang, Qixing; Koltun, Vladlen; Guibas, Leonidas
2011-01-01
program is solved via a linear programming relaxation, using a block coordinate descent procedure that makes the optimization feasible for large databases. We evaluate the presented approach on the Princeton segmentation benchmark and show that joint shape
A Linear Programming Approach to Complex Games: An Application to Nuclear Exchange Models
National Research Council Canada - National Science Library
Oelrich, I
2002-01-01
.... Like the MESA model, the exchange is cast in terms of game theory, using linear approximations and an optimal allocation defined by a user-specified objective function Solutions are better using...
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.
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.
A primal-dual decomposition based interior point approach to two-stage stochastic linear programming
A.B. Berkelaar (Arjan); C.L. Dert (Cees); K.P.B. Oldenkamp; S. Zhang (Shuzhong)
1999-01-01
textabstractDecision making under uncertainty is a challenge faced by many decision makers. Stochastic programming is a major tool developed to deal with optimization with uncertainties that has found applications in, e.g. finance, such as asset-liability and bond-portfolio management.
Linear and nonlinear programming with Maple an interactive, applications-based approach
Fishback, Paul E
2009-01-01
""… this text could be ideal for the right course and the right group of students. An independent or directed study in mathematical programming using this book could be an excellent introduction to applied optimization for an interested group of undergraduates. …""-MAA Reviews, March 2010
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…
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
International Nuclear Information System (INIS)
Mashayekh, Salman; Stadler, Michael; Cardoso, Gonçalo; Heleno, Miguel
2017-01-01
Highlights: • This paper presents a MILP model for optimal design of multi-energy microgrids. • Our microgrid design includes optimal technology portfolio, placement, and operation. • Our model includes microgrid electrical power flow and heat transfer equations. • The case study shows advantages of our model over aggregate single-node approaches. • The case study shows the accuracy of the integrated linearized power flow model. - Abstract: Optimal microgrid design is a challenging problem, especially for multi-energy microgrids with electricity, heating, and cooling loads as well as sources, and multiple energy carriers. To address this problem, this paper presents an optimization model formulated as a mixed-integer linear program, which determines the optimal technology portfolio, the optimal technology placement, and the associated optimal dispatch, in a microgrid with multiple energy types. The developed model uses a multi-node modeling approach (as opposed to an aggregate single-node approach) that includes electrical power flow and heat flow equations, and hence, offers the ability to perform optimal siting considering physical and operational constraints of electrical and heating/cooling networks. The new model is founded on the existing optimization model DER-CAM, a state-of-the-art decision support tool for microgrid planning and design. The results of a case study that compares single-node vs. multi-node optimal design for an example microgrid show the importance of multi-node modeling. It has been shown that single-node approaches are not only incapable of optimal DER placement, but may also result in sub-optimal DER portfolio, as well as underestimation of investment costs.
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.
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...
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.
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
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…
Directory of Open Access Journals (Sweden)
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 .
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...
Linear programming computation
PAN, Ping-Qi
2014-01-01
With emphasis on computation, this book is a real breakthrough in the field of LP. In addition to conventional topics, such as the simplex method, duality, and interior-point methods, all deduced in a fresh and clear manner, it introduces the state of the art by highlighting brand-new and advanced results, including efficient pivot rules, Phase-I approaches, reduced simplex methods, deficient-basis methods, face methods, and pivotal interior-point methods. In particular, it covers the determination of the optimal solution set, feasible-point simplex method, decomposition principle for solving large-scale problems, controlled-branch method based on generalized reduced simplex framework for solving integer LP problems.
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...
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.
175 Years of Linear Programming
Indian Academy of Sciences (India)
polynomial-time solvability of linear programming, that is, testing if a polyhedron Q E ~ ... Q is rational, i.e. all extreme points and rays of Q are ra- tional vectors or ..... rithrll terminates with an interior solution, a post-processing step is usually ...
175 Years of Linear Programming
Indian Academy of Sciences (India)
Home; Journals; Resonance – Journal of Science Education; Volume 4; Issue 10. 175 Years of Linear Programming - Max Flow = Min Cut. Vijay Chandru M R Rao. Series Article Volume 4 Issue 10 October 1999 pp 22-39. Fulltext. Click here to view fulltext PDF. Permanent link:
175 Years of Linear Programming
Indian Academy of Sciences (India)
Home; Journals; Resonance – Journal of Science Education; Volume 4; Issue 5. 175 Years of Linear Programming - Pune's Gift. Vijay Chandru M R Rao. Series Article Volume 4 Issue 5 May ... Computer Science and Automation, IISc Bangalore 560012, India. Director, Indian Institute of Management, Bannerghatta Road, ...
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.
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.
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.
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.
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.
Dos Santos, Quenia; Sichieri, Rosely; Darmon, Nicole; Maillot, Matthieu; Verly-Junior, Eliseu
2018-06-01
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.
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.
New approach to solve symmetric fully fuzzy linear systems
Indian Academy of Sciences (India)
concepts of fuzzy set theory and then define a fully fuzzy linear system of equations. .... To represent the above problem as fully fuzzy linear system, we represent x .... Fully fuzzy linear systems can be solved by Linear programming approach, ...
The simplex method of linear programming
Ficken, Frederick A
1961-01-01
This concise but detailed and thorough treatment discusses the rudiments of the well-known simplex method for solving optimization problems in linear programming. Geared toward undergraduate students, the approach offers sufficient material for readers without a strong background in linear algebra. Many different kinds of problems further enrich the presentation. The text begins with examinations of the allocation problem, matrix notation for dual problems, feasibility, and theorems on duality and existence. Subsequent chapters address convex sets and boundedness, the prepared problem and boun
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.
El-Askary, H. M.; Sheta, W.; Prasad, A. K.; Ali, H.; Abdel rahman, M.; El-Desouki, A.; Kafatos, M.
2011-12-01
Water Vapor Low Mean, Atmospheric Water Vapor Mean, Mass Concentration Land Mean, Optical Depth Ratio Small Land and Ocean Mean, Small Mode Optical Depth Land and Ocean Mean, Cloud Top Pressure Day Mean, Cloud Top Pressure Mean, Cloud Top Temperature Mean. The suggested linear Genetic approach detected hidden anomalies and relationships that cannot be observed from the conventional statistical methods. A well-established model as an important contribution to show the relationships between particle size and the physical and chemical aerosols properties has been designed. Such coupling will provide insight into the micro physics of the phenomenon. The proposed research will reveal previously uncharacterized yet fundamental relations and dependencies among aerosols, cloud and meteorological related parameters. Moreover, it would aid in filling gaps of missing satellite parameters using other available ones.
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.
The linear programming bound for binary linear codes
Brouwer, A.E.
1993-01-01
Combining Delsarte's (1973) linear programming bound with the information that certain weights cannot occur, new upper bounds for dmin (n,k), the maximum possible minimum distance of a binary linear code with given word length n and dimension k, are derived.
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…
Experimental Approaches at Linear Colliders
International Nuclear Information System (INIS)
Jaros, John A
2002-01-01
Precision measurements have played a vital role in our understanding of elementary particle physics. Experiments performed using e + e - collisions have contributed an essential part. Recently, the precision measurements at LEP and SLC have probed the standard model at the quantum level and severely constrained the mass of the Higgs boson [1]. Coupled with the limits on the Higgs mass from direct searches [2], this enables the mass to be constrained to be in the range 115-205 GeV. Developments in accelerator R and D have matured to the point where one could contemplate construction of a linear collider with initial energy in the 500 GeV range and a credible upgrade path to ∼ 1 TeV. Now is therefore the correct time to critically evaluate the case for such a facility
M. ZANGIABADI; H. R. MALEKI
2007-01-01
In the real-world optimization problems, coefficients of the objective function are not known precisely and can be interpreted as fuzzy numbers. In this paper we define the concepts of optimality for linear programming problems with fuzzy parameters based on those for multiobjective linear programming problems. Then by using the concept of comparison of fuzzy numbers, we transform a linear programming problem with fuzzy parameters to a multiobjective linear programming problem. To this end, w...
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
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...
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
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.
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)
Sparsity Prevention Pivoting Method for Linear Programming
DEFF Research Database (Denmark)
Li, Peiqiang; Li, Qiyuan; Li, Canbing
2018-01-01
When the simplex algorithm is used to calculate a linear programming problem, if the matrix is a sparse matrix, it will be possible to lead to many zero-length calculation steps, and even iterative cycle will appear. To deal with the problem, a new pivoting method is proposed in this paper....... The principle of this method is avoided choosing the row which the value of the element in the b vector is zero as the row of the pivot element to make the matrix in linear programming density and ensure that most subsequent steps will improve the value of the objective function. One step following...... this principle is inserted to reselect the pivot element in the existing linear programming algorithm. Both the conditions for inserting this step and the maximum number of allowed insertion steps are determined. In the case study, taking several numbers of linear programming problems as examples, the results...
Sparsity Prevention Pivoting Method for Linear Programming
DEFF Research Database (Denmark)
Li, Peiqiang; Li, Qiyuan; Li, Canbing
2018-01-01
. The principle of this method is avoided choosing the row which the value of the element in the b vector is zero as the row of the pivot element to make the matrix in linear programming density and ensure that most subsequent steps will improve the value of the objective function. One step following......When the simplex algorithm is used to calculate a linear programming problem, if the matrix is a sparse matrix, it will be possible to lead to many zero-length calculation steps, and even iterative cycle will appear. To deal with the problem, a new pivoting method is proposed in this paper...... this principle is inserted to reselect the pivot element in the existing linear programming algorithm. Both the conditions for inserting this step and the maximum number of allowed insertion steps are determined. In the case study, taking several numbers of linear programming problems as examples, the results...
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.
Evaluation of film dosemeters by linear programming
International Nuclear Information System (INIS)
Kragh, P.; Nitschke, J.
1992-01-01
An evaluation method for multi-component dosemeters is described which uses linear programming in order to decrease the dependence on energy and direction. The results of this method are more accurate than those obtained with the evaluation methods so far applied in film dosimetry. In addition, systematic errors can be given when evaluating individual measurements. Combined linear programming, as a special case of the presented method, is described taking a film dosemeter of particular type as an example. (orig.) [de
Ebrahimnejad, Ali
2015-08-01
There are several methods, in the literature, for solving fuzzy variable linear programming problems (fuzzy linear programming in which the right-hand-side vectors and decision variables are represented by trapezoidal fuzzy numbers). In this paper, the shortcomings of some existing methods are pointed out and to overcome these shortcomings a new method based on the bounded dual simplex method is proposed to determine the fuzzy optimal solution of that kind of fuzzy variable linear programming problems in which some or all variables are restricted to lie within lower and upper bounds. To illustrate the proposed method, an application example is solved and the obtained results are given. The advantages of the proposed method over existing methods are discussed. Also, one application of this algorithm in solving bounded transportation problems with fuzzy supplies and demands is dealt with. The proposed method is easy to understand and to apply for determining the fuzzy optimal solution of bounded fuzzy variable linear programming problems occurring in real-life situations.
Introducing linear functions: an alternative statistical approach
Nolan, Caroline; Herbert, Sandra
2015-12-01
The introduction of linear functions is the turning point where many students decide if mathematics is useful or not. This means the role of parameters and variables in linear functions could be considered to be `threshold concepts'. There is recognition that linear functions can be taught in context through the exploration of linear modelling examples, but this has its limitations. Currently, statistical data is easily attainable, and graphics or computer algebra system (CAS) calculators are common in many classrooms. The use of this technology provides ease of access to different representations of linear functions as well as the ability to fit a least-squares line for real-life data. This means these calculators could support a possible alternative approach to the introduction of linear functions. This study compares the results of an end-of-topic test for two classes of Australian middle secondary students at a regional school to determine if such an alternative approach is feasible. In this study, test questions were grouped by concept and subjected to concept by concept analysis of the means of test results of the two classes. This analysis revealed that the students following the alternative approach demonstrated greater competence with non-standard questions.
Portfolio optimization using fuzzy linear programming
Pandit, Purnima K.
2013-09-01
Portfolio Optimization (PO) is a problem in Finance, in which investor tries to maximize return and minimize risk by carefully choosing different assets. Expected return and risk are the most important parameters with regard to optimal portfolios. In the simple form PO can be modeled as quadratic programming problem which can be put into equivalent linear form. PO problems with the fuzzy parameters can be solved as multi-objective fuzzy linear programming problem. In this paper we give the solution to such problems with an illustrative example.
Some Properties of Multiple Parameters Linear Programming
Directory of Open Access Journals (Sweden)
Maoqin Li
2010-01-01
Full Text Available We consider a linear programming problem in which the right-hand side vector depends on multiple parameters. We study the characters of the optimal value function and the critical regions based on the concept of the optimal partition. We show that the domain of the optimal value function f can be decomposed into finitely many subsets with disjoint relative interiors, which is different from the result based on the concept of the optimal basis. And any directional derivative of f at any point can be computed by solving a linear programming problem when only an optimal solution is available at the point.
Some Properties of Multiple Parameters Linear Programming
Directory of Open Access Journals (Sweden)
Yan Hong
2010-01-01
Full Text Available Abstract We consider a linear programming problem in which the right-hand side vector depends on multiple parameters. We study the characters of the optimal value function and the critical regions based on the concept of the optimal partition. We show that the domain of the optimal value function can be decomposed into finitely many subsets with disjoint relative interiors, which is different from the result based on the concept of the optimal basis. And any directional derivative of at any point can be computed by solving a linear programming problem when only an optimal solution is available at the point.
PCX, Interior-Point Linear Programming Solver
International Nuclear Information System (INIS)
Czyzyk, J.
2004-01-01
1 - Description of program or function: PCX solves linear programming problems using the Mehrota predictor-corrector interior-point algorithm. PCX can be called as a subroutine or used in stand-alone mode, with data supplied from an MPS file. The software incorporates modules that can be used separately from the linear programming solver, including a pre-solve routine and data structure definitions. 2 - Methods: The Mehrota predictor-corrector method is a primal-dual interior-point method for linear programming. The starting point is determined from a modified least squares heuristic. Linear systems of equations are solved at each interior-point iteration via a sparse Cholesky algorithm native to the code. A pre-solver is incorporated in the code to eliminate inefficiencies in the user's formulation of the problem. 3 - Restriction on the complexity of the problem: There are no size limitations built into the program. The size of problem solved is limited by RAM and swap space on the user's computer
Using linear programming to analyze and optimize stochastic flow lines
DEFF Research Database (Denmark)
Helber, Stefan; Schimmelpfeng, Katja; Stolletz, Raik
2011-01-01
This paper presents a linear programming approach to analyze and optimize flow lines with limited buffer capacities and stochastic processing times. The basic idea is to solve a huge but simple linear program that models an entire simulation run of a multi-stage production process in discrete time...... programming and hence allows us to solve buffer allocation problems. We show under which conditions our method works well by comparing its results to exact values for two-machine models and approximate simulation results for longer lines....
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
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.
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…
Optimized remedial groundwater extraction using linear programming
International Nuclear Information System (INIS)
Quinn, J.J.
1995-01-01
Groundwater extraction systems are typically installed to remediate contaminant plumes or prevent further spread of contamination. These systems are expensive to install and maintain. A traditional approach to designing such a wellfield uses a series of trial-and-error simulations to test the effects of various well locations and pump rates. However, the optimal locations and pump rates of extraction wells are difficult to determine when objectives related to the site hydrogeology and potential pumping scheme are considered. This paper describes a case study of an application of linear programming theory to determine optimal well placement and pump rates. The objectives of the pumping scheme were to contain contaminant migration and reduce contaminant concentrations while minimizing the total amount of water pumped and treated. Past site activities at the area under study included disposal of contaminants in pits. Several groundwater plumes have been identified, and others may be present. The area of concern is bordered on three sides by a wetland, which receives a portion of its input budget as groundwater discharge from the pits. Optimization of the containment pumping scheme was intended to meet three goals: (1) prevent discharge of contaminated groundwater to the wetland, (2) minimize the total water pumped and treated (cost benefit), and (3) avoid dewatering of the wetland (cost and ecological benefits). Possible well locations were placed at known source areas. To constrain the problem, the optimization program was instructed to prevent any flow toward the wetland along a user-specified border. In this manner, the optimization routine selects well locations and pump rates so that a groundwater divide is produced along this boundary
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).
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
Linear systems a measurement based approach
Bhattacharyya, S P; Mohsenizadeh, D N
2014-01-01
This brief presents recent results obtained on the analysis, synthesis and design of systems described by linear equations. It is well known that linear equations arise in most branches of science and engineering as well as social, biological and economic systems. The novelty of this approach is that no models of the system are assumed to be available, nor are they required. Instead, a few measurements made on the system can be processed strategically to directly extract design values that meet specifications without constructing a model of the system, implicitly or explicitly. These new concepts are illustrated by applying them to linear DC and AC circuits, mechanical, civil and hydraulic systems, signal flow block diagrams and control systems. These applications are preliminary and suggest many open problems. The results presented in this brief are the latest effort in this direction and the authors hope these will lead to attractive alternatives to model-based design of engineering and other systems.
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.
Optimal traffic control in highway transportation networks using linear programming
Li, Yanning; Canepa, Edward S.; Claudel, Christian G.
2014-01-01
of the Hamilton-Jacobi PDE, the problem of controlling the state of the system on a network link in a finite horizon can be posed as a Linear Program. Assuming all intersections in the network are controllable, we show that the optimization approach can
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...
International program on linear electric motors
Energy Technology Data Exchange (ETDEWEB)
Dawson, G.E.; Eastham, A.R.; Parker, J.H.
1992-05-01
The International Program on Linear Electric Motors (LEM) was initiated for the purposes of commumication and coordination between various centers of expertise in LEM technology in Germany, Japan and Canada. Furthermore, it was intended to provide assessment and support of the planning of technological developments and for dissemination of information to researchers, service operators and policy makers, and to ensure that full advantage can be taken if opportunities for technology transfer occur. In the process, the program was able to provide closer contacts between researchers, to enhance and encourage collaborative research and development, and to facilitate joint ventures in advanced transportation technologies. Work done under the program is documented, and seminar materials presented by Canadian researchers in Italy, and by Italian researchers at Queen's University in Canada are presented. Five separate abstracts have been prepared for the main body of the report and the seminar materials.
New approach to solve fully fuzzy system of linear equations using ...
Indian Academy of Sciences (India)
Known example problems are solved to illustrate the efficacy and ... The concept of fuzzy set and fuzzy number were first introduced by Zadeh .... (iii) Fully fuzzy linear systems can be solved by linear programming approach, Gauss elim-.
DEFF Research Database (Denmark)
Ommen, Torben Schmidt; Markussen, Wiebke Brix; Elmegaard, Brian
2014-01-01
In the paper, three frequently used operation optimisation methods are examined with respect to their impact on operation management of the combined utility technologies for electric power and DH (district heating) of eastern Denmark. The investigation focusses on individual plant operation...... differences and differences between the solution found by each optimisation method. One of the investigated approaches utilises LP (linear programming) for optimisation, one uses LP with binary operation constraints, while the third approach uses NLP (non-linear programming). The LP model is used...... as a benchmark, as this type is frequently used, and has the lowest amount of constraints of the three. A comparison of the optimised operation of a number of units shows significant differences between the three methods. Compared to the reference, the use of binary integer variables, increases operation...
Operator approach to linear control systems
Cheremensky, A
1996-01-01
Within the framework of the optimization problem for linear control systems with quadratic performance index (LQP), the operator approach allows the construction of a systems theory including a number of particular infinite-dimensional optimization problems with hardly visible concreteness. This approach yields interesting interpretations of these problems and more effective feedback design methods. This book is unique in its emphasis on developing methods for solving a sufficiently general LQP. Although this is complex material, the theory developed here is built on transparent and relatively simple principles, and readers with less experience in the field of operator theory will find enough material to give them a good overview of the current state of LQP theory and its applications. Audience: Graduate students and researchers in the fields of mathematical systems theory, operator theory, cybernetics, and control systems.
A program package for solving linear optimization problems
International Nuclear Information System (INIS)
Horikami, Kunihiko; Fujimura, Toichiro; Nakahara, Yasuaki
1980-09-01
Seven computer programs for the solution of linear, integer and quadratic programming (four programs for linear programming, one for integer programming and two for quadratic programming) have been prepared and tested on FACOM M200 computer, and auxiliary programs have been written to make it easy to use the optimization program package. The characteristics of each program are explained and the detailed input/output descriptions are given in order to let users know how to use them. (author)
Optimal selection for shielding materials by fuzzy linear programming
International Nuclear Information System (INIS)
Kanai, Y.; Miura, N.; Sugasawa, S.
1996-01-01
An application of fuzzy linear programming methods to optimization of a radiation shield is presented. The main purpose of the present study is the choice of materials and the search of the ratio of mixture-component as the first stage of the methodology on optimum shielding design according to individual requirements of nuclear reactor, reprocessing facility, shipping cask installing spent fuel, ect. The characteristic values for the shield optimization may be considered their cost, spatial space, weight and some shielding qualities such as activation rate and total dose rate for neutron and gamma ray (includes secondary gamma ray). This new approach can reduce huge combination calculations for conventional two-valued logic approaches to representative single shielding calculation by group-wised optimization parameters determined in advance. Using the fuzzy linear programming method, possibilities for reducing radiation effects attainable in optimal compositions hydrated, lead- and boron-contained materials are investigated
International Nuclear Information System (INIS)
Wouters, Carmen; Fraga, Eric S.; James, Adrian M.
2015-01-01
The integration of distributed generation units and microgrids in the current grid infrastructure requires an efficient and cost effective local energy system design. A mixed-integer linear programming model is presented to identify such optimal design. The electricity as well as the space heating and cooling demands of a small residential neighbourhood are satisfied through the consideration and combined use of distributed generation technologies, thermal units and energy storage with an optional interconnection with the central grid. Moreover, energy integration is allowed in the form of both optimised pipeline networks and microgrid operation. The objective is to minimise the total annualised cost of the system to meet its yearly energy demand. The model integrates the operational characteristics and constraints of the different technologies for several scenarios in a South Australian setting and is implemented in GAMS. The impact of energy integration is analysed, leading to the identification of key components for residential energy systems. Additionally, a multi-microgrid concept is introduced to allow for local clustering of households within neighbourhoods. The robustness of the model is shown through sensitivity analysis, up-scaling and an effort to address the variability of solar irradiation. - Highlights: • Distributed energy system planning is employed on a small residential scale. • Full energy integration is employed based on microgrid operation and tri-generation. • An MILP for local clustering of households in multi-microgrids is developed. • Micro combined heat and power units are key components for residential microgrids
Game Theory and its Relationship with Linear Programming Models ...
African Journals Online (AJOL)
Game Theory and its Relationship with Linear Programming Models. ... This paper shows that game theory and linear programming problem are closely related subjects since any computing method devised for ... AJOL African Journals Online.
Introduction to linear programming: Coalitional game experiments
Energy Technology Data Exchange (ETDEWEB)
Lucas, W.
1994-12-31
Many solution notions in the multiperson cooperative games (in characteristic function form) make use of linear programming (LP). The popular concept of the {open_quotes}core{close_quotes} of a coalitional game is a special type of LP. It can be introduced in a very simple and quite exciting manner by means of a group experiment. A total of fifty dollars will be given to three randomly selected attendees who will take part in an experiment during this talk, presuming they behave in a Pareto optimal manner. Furthermore, the dual of the particular LP for the core gives rise to the idea of {open_quotes}balanced sets{close_quotes} which is an interesting combinatorial structure in its own right.
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...
Simple Planar Truss (Linear, Nonlinear and Stochastic Approach
Directory of Open Access Journals (Sweden)
Frydrýšek Karel
2016-11-01
Full Text Available This article deals with a simple planar and statically determinate pin-connected truss. It demonstrates the processes and methods of derivations and solutions according to 1st and 2nd order theories. The article applies linear and nonlinear approaches and their simplifications via a Maclaurin series. Programming connected with the stochastic Simulation-Based Reliability Method (i.e. the direct Monte Carlo approach is used to conduct a probabilistic reliability assessment (i.e. a calculation of the probability that plastic deformation will occur in members of the truss.
Algorithmic Trading with Developmental and Linear Genetic Programming
Wilson, Garnett; Banzhaf, Wolfgang
A developmental co-evolutionary genetic programming approach (PAM DGP) and a standard linear genetic programming (LGP) stock trading systemare applied to a number of stocks across market sectors. Both GP techniques were found to be robust to market fluctuations and reactive to opportunities associated with stock price rise and fall, with PAMDGP generating notably greater profit in some stock trend scenarios. Both algorithms were very accurate at buying to achieve profit and selling to protect assets, while exhibiting bothmoderate trading activity and the ability to maximize or minimize investment as appropriate. The content of the trading rules produced by both algorithms are also examined in relation to stock price trend scenarios.
Introducing Linear Functions: An Alternative Statistical Approach
Nolan, Caroline; Herbert, Sandra
2015-01-01
The introduction of linear functions is the turning point where many students decide if mathematics is useful or not. This means the role of parameters and variables in linear functions could be considered to be "threshold concepts". There is recognition that linear functions can be taught in context through the exploration of linear…
Stability of Linear Equations--Algebraic Approach
Cherif, Chokri; Goldstein, Avraham; Prado, Lucio M. G.
2012-01-01
This article could be of interest to teachers of applied mathematics as well as to people who are interested in applications of linear algebra. We give a comprehensive study of linear systems from an application point of view. Specifically, we give an overview of linear systems and problems that can occur with the computed solution when the…
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.
No-signaling quantum key distribution: solution by linear programming
Hwang, Won-Young; Bae, Joonwoo; Killoran, Nathan
2015-02-01
We outline a straightforward approach for obtaining a secret key rate using only no-signaling constraints and linear programming. Assuming an individual attack, we consider all possible joint probabilities. Initially, we study only the case where Eve has binary outcomes, and we impose constraints due to the no-signaling principle and given measurement outcomes. Within the remaining space of joint probabilities, by using linear programming, we get bound on the probability of Eve correctly guessing Bob's bit. We then make use of an inequality that relates this guessing probability to the mutual information between Bob and a more general Eve, who is not binary-restricted. Putting our computed bound together with the Csiszár-Körner formula, we obtain a positive key generation rate. The optimal value of this rate agrees with known results, but was calculated in a more straightforward way, offering the potential of generalization to different scenarios.
A linear algebraic approach to electron-molecule collisions
International Nuclear Information System (INIS)
Collins, L.A.; Schnieder, B.I.
1982-01-01
The linear algebraic approach to electron-molecule collisions is examined by firstly deriving the general set of coupled integrodifferential equations that describe electron collisional processes and then describing the linear algebraic approach for obtaining a solution to the coupled equations. Application of the linear algebraic method to static-exchange, separable exchange and effective optical potential, is examined. (U.K.)
A Novel Approach for Solving Semidefinite Programs
Directory of Open Access Journals (Sweden)
Hong-Wei Jiao
2014-01-01
Full Text Available A novel linearizing alternating direction augmented Lagrangian approach is proposed for effectively solving semidefinite programs (SDP. For every iteration, by fixing the other variables, the proposed approach alternatively optimizes the dual variables and the dual slack variables; then the primal variables, that is, Lagrange multipliers, are updated. In addition, the proposed approach renews all the variables in closed forms without solving any system of linear equations. Global convergence of the proposed approach is proved under mild conditions, and two numerical problems are given to demonstrate the effectiveness of the presented approach.
Kinetic approach to plasma end loss from linear devices
International Nuclear Information System (INIS)
Dreicer, H.
1976-01-01
A first step in the direction of a kinetic approach to end loss has been presented. This approach brings to light some fundamental processes not uncovered by the magnetohydrodynamic or guiding center approach. Attention was focused on the basically transient phenomenon in a way that describes the quite different behavior of collision dominated and collisionless ions, but ignores the magnetic nozzle effects near the ends of the system. The treatment illuminates some of the roles played by the parameter l/sub ii//L, and suggests the direction for more detailed investigations. End loss from linear systems is a very many faceted problem. Kinetic effects, magnetic effects, heat flow, etc. are all intermixed, and it will require a strong long term experimental and theoretical program to unravel all of its mysteries
Linearized dynamical approach to current algebra
International Nuclear Information System (INIS)
Scadron, M.D.
1995-07-01
We study the original motivations searching for a nonlinear chiral Lagrangian to replace the linear sigma model while manifesting all the successful properties of current algebra and partial conservation of axial currents (PCAC). (author). 26 refs
A New Finite Continuation Algorithm for Linear Programming
DEFF Research Database (Denmark)
Madsen, Kaj; Nielsen, Hans Bruun; Pinar, Mustafa
1996-01-01
We describe a new finite continuation algorithm for linear programming. The dual of the linear programming problem with unit lower and upper bounds is formulated as an $\\ell_1$ minimization problem augmented with the addition of a linear term. This nondifferentiable problem is approximated...... by a smooth problem. It is shown that the minimizers of the smooth problem define a family of piecewise-linear paths as a function of a smoothing parameter. Based on this property, a finite algorithm that traces these paths to arrive at an optimal solution of the linear program is developed. The smooth...
Optimization Research of Generation Investment Based on Linear Programming Model
Wu, Juan; Ge, Xueqian
Linear programming is an important branch of operational research and it is a mathematical method to assist the people to carry out scientific management. GAMS is an advanced simulation and optimization modeling language and it will combine a large number of complex mathematical programming, such as linear programming LP, nonlinear programming NLP, MIP and other mixed-integer programming with the system simulation. In this paper, based on the linear programming model, the optimized investment decision-making of generation is simulated and analyzed. At last, the optimal installed capacity of power plants and the final total cost are got, which provides the rational decision-making basis for optimized investments.
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.
Fuzzy multiple linear regression: A computational approach
Juang, C. H.; Huang, X. H.; Fleming, J. W.
1992-01-01
This paper presents a new computational approach for performing fuzzy regression. In contrast to Bardossy's approach, the new approach, while dealing with fuzzy variables, closely follows the conventional regression technique. In this approach, treatment of fuzzy input is more 'computational' than 'symbolic.' The following sections first outline the formulation of the new approach, then deal with the implementation and computational scheme, and this is followed by examples to illustrate the new procedure.
DEFF Research Database (Denmark)
Xydis, George; Koroneos, C.
2012-01-01
In the present paper the mismatch between the energy supply levels and the end use, in a broader sense, was studied for the Hellenic energy system. The ultimate objective was to optimize the way to meet the country's energy needs in every different administrative and geographical region using...... 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...
An algorithm for the solution of dynamic linear programs
Psiaki, Mark L.
1989-01-01
The algorithm's objective is to efficiently solve Dynamic Linear Programs (DLP) by taking advantage of their special staircase structure. This algorithm constitutes a stepping stone to an improved algorithm for solving Dynamic Quadratic Programs, which, in turn, would make the nonlinear programming method of Successive Quadratic Programs more practical for solving trajectory optimization problems. The ultimate goal is to being trajectory optimization solution speeds into the realm of real-time control. The algorithm exploits the staircase nature of the large constraint matrix of the equality-constrained DLPs encountered when solving inequality-constrained DLPs by an active set approach. A numerically-stable, staircase QL factorization of the staircase constraint matrix is carried out starting from its last rows and columns. The resulting recursion is like the time-varying Riccati equation from multi-stage LQR theory. The resulting factorization increases the efficiency of all of the typical LP solution operations over that of a dense matrix LP code. At the same time numerical stability is ensured. The algorithm also takes advantage of dynamic programming ideas about the cost-to-go by relaxing active pseudo constraints in a backwards sweeping process. This further decreases the cost per update of the LP rank-1 updating procedure, although it may result in more changes of the active set that if pseudo constraints were relaxed in a non-stagewise fashion. The usual stability of closed-loop Linear/Quadratic optimally-controlled systems, if it carries over to strictly linear cost functions, implies that the saving due to reduced factor update effort may outweigh the cost of an increased number of updates. An aerospace example is presented in which a ground-to-ground rocket's distance is maximized. This example demonstrates the applicability of this class of algorithms to aerospace guidance. It also sheds light on the efficacy of the proposed pseudo constraint relaxation
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.
Portfolio optimization by using linear programing models based on genetic algorithm
Sukono; Hidayat, Y.; Lesmana, E.; Putra, A. S.; Napitupulu, H.; Supian, S.
2018-01-01
In this paper, we discussed the investment portfolio optimization using linear programming model based on genetic algorithms. It is assumed that the portfolio risk is measured by absolute standard deviation, and each investor has a risk tolerance on the investment portfolio. To complete the investment portfolio optimization problem, the issue is arranged into a linear programming model. Furthermore, determination of the optimum solution for linear programming is done by using a genetic algorithm. As a numerical illustration, we analyze some of the stocks traded on the capital market in Indonesia. Based on the analysis, it is shown that the portfolio optimization performed by genetic algorithm approach produces more optimal efficient portfolio, compared to the portfolio optimization performed by a linear programming algorithm approach. Therefore, genetic algorithms can be considered as an alternative on determining the investment portfolio optimization, particularly using linear programming models.
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.
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
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 ...
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.
Integrating Linear Programming and Analytical Hierarchical ...
African Journals Online (AJOL)
Study area is about 28000 ha of Keleibar- Chai Watershed, located in eastern Azerbaijan, Iran. Socio-economic information collected through a two-stage survey of 19 villages, including 300 samples. Thematic maps also have summarized Ecological factors, including physical and economic data. A comprehensive Linear ...
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.
Introductory Linear Regression Programs in Undergraduate Chemistry.
Gale, Robert J.
1982-01-01
Presented are simple programs in BASIC and FORTRAN to apply the method of least squares. They calculate gradients and intercepts and express errors as standard deviations. An introduction of undergraduate students to such programs in a chemistry class is reviewed, and issues instructors should be aware of are noted. (MP)
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...
Non-linear programming method in optimization of fast reactors
International Nuclear Information System (INIS)
Pavelesku, M.; Dumitresku, Kh.; Adam, S.
1975-01-01
Application of the non-linear programming methods on optimization of nuclear materials distribution in fast reactor is discussed. The programming task composition is made on the basis of the reactor calculation dependent on the fuel distribution strategy. As an illustration of this method application the solution of simple example is given. Solution of the non-linear program is done on the basis of the numerical method SUMT. (I.T.)
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
How to Use Linear Programming for Information System Performances Optimization
Directory of Open Access Journals (Sweden)
Hell Marko
2014-09-01
Full Text Available Background: Organisations nowadays operate in a very dynamic environment, and therefore, their ability of continuously adjusting the strategic plan to the new conditions is a must for achieving their strategic objectives. BSC is a well-known methodology for measuring performances enabling organizations to learn how well they are doing. In this paper, “BSC for IS” will be proposed in order to measure the IS impact on the achievement of organizations’ business goals. Objectives: The objective of this paper is to present the original procedure which is used to enhance the BSC methodology in planning the optimal targets of IS performances value in order to maximize the organization's effectiveness. Methods/Approach: The method used in this paper is the quantitative methodology - linear programming. In the case study, linear programming is used for optimizing organization’s strategic performance. Results: Results are shown on the example of a case study national park. An optimal performance value for the strategic objective has been calculated, as well as an optimal performance value for each DO (derived objective. Results are calculated in Excel, using Solver Add-in. Conclusions: The presentation of methodology through the case study of a national park shows that this methodology, though it requires a high level of formalisation, provides a very transparent performance calculation.
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…
Duality in non-linear programming
Jeyalakshmi, K.
2018-04-01
In this paper we consider duality and converse duality for a programming problem involving convex objective and constraint functions with finite dimensional range. We do not assume any constraint qualification. The dual is presented by reducing the problem to a standard Lagrange multiplier problem.
Directory of Open Access Journals (Sweden)
Yi-hua Zhong
2013-01-01
Full Text Available Recently, various methods have been developed for solving linear programming problems with fuzzy number, such as simplex method and dual simplex method. But their computational complexities are exponential, which is not satisfactory for solving large-scale fuzzy linear programming problems, especially in the engineering field. A new method which can solve large-scale fuzzy number linear programming problems is presented in this paper, which is named a revised interior point method. Its idea is similar to that of interior point method used for solving linear programming problems in crisp environment before, but its feasible direction and step size are chosen by using trapezoidal fuzzy numbers, linear ranking function, fuzzy vector, and their operations, and its end condition is involved in linear ranking function. Their correctness and rationality are proved. Moreover, choice of the initial interior point and some factors influencing the results of this method are also discussed and analyzed. The result of algorithm analysis and example study that shows proper safety factor parameter, accuracy parameter, and initial interior point of this method may reduce iterations and they can be selected easily according to the actual needs. Finally, the method proposed in this paper is an alternative method for solving fuzzy number linear programming problems.
Linear Parametric Sensitivity Analysis of the Constraint Coefficient Matrix in Linear Programs
Zuidwijk, Rob
2005-01-01
textabstractSensitivity analysis is used to quantify the impact of changes in the initial data of linear programs on the optimal value. In particular, parametric sensitivity analysis involves a perturbation analysis in which the effects of small changes of some or all of the initial data on an optimal solution are investigated, and the optimal solution is studied on a so-called critical range of the initial data, in which certain properties such as the optimal basis in linear programming are ...
Towards lexicographic multi-objective linear programming using grossone methodology
Cococcioni, Marco; Pappalardo, Massimo; Sergeyev, Yaroslav D.
2016-10-01
Lexicographic Multi-Objective Linear Programming (LMOLP) problems can be solved in two ways: preemptive and nonpreemptive. The preemptive approach requires the solution of a series of LP problems, with changing constraints (each time the next objective is added, a new constraint appears). The nonpreemptive approach is based on a scalarization of the multiple objectives into a single-objective linear function by a weighted combination of the given objectives. It requires the specification of a set of weights, which is not straightforward and can be time consuming. In this work we present both mathematical and software ingredients necessary to solve LMOLP problems using a recently introduced computational methodology (allowing one to work numerically with infinities and infinitesimals) based on the concept of grossone. The ultimate goal of such an attempt is an implementation of a simplex-like algorithm, able to solve the original LMOLP problem by solving only one single-objective problem and without the need to specify finite weights. The expected advantages are therefore obvious.
General guidelines solution for linear programming with fuzzy coefficients
Directory of Open Access Journals (Sweden)
Sergio Gerardo de los Cobos Silva
2013-08-01
Full Text Available This work introduce to the Possibilistic Programming and the Fuzzy Programming as paradigms that allow to resolve problems of linear programming when the coefficients of the model or the restrictions on the same are presented as fuzzy numbers, rather than exact numbers (crisp. This work presents some examples based on [1].
New Approaches to Linear and Nonlinear Programming
National Research Council Canada - National Science Library
Murray, Walter
1996-01-01
..., and financial modeling such as portfolio optimization. Progress on solution algorithms and software for such applications is ultimately reflected in improved techniques in many other areas of science and industry.
Scheduling Outpatient Services: A Linear Programming Approach
1990-07-05
25-32. Hartzke, L. (1983). Diagnosis related groups: Concept and use. Madison, WI! NTIS. Hollis, B. R. (1988). Methodology, myths , and maths of DRO’s...49 3.06 (A 19 368 INFECTIONS, FEMALE REPRODUCTIVE SYSTEM 15 69 4.60 20 360 VAGINA , CERVIX & VULVA PROCEDURES 13 24 1.85 21 358 UTERINE & ADNEXA PROC
Fuzzy linear programming approach for solving transportation ...
Indian Academy of Sciences (India)
ALI EBRAHIMNEJAD
Department of Mathematics, Qaemshahr Branch, Islamic Azad University, Qaemshahr, Iran e-mail: ..... est grade of membership at x are μ ˜AL (x) and μ ˜AU (x), respectively. ..... trapezoidal fuzzy numbers transportation problem (12) are.
Pricing Strategy Selection Using Fuzzy Linear Programming
Elif Alaybeyoğlu; Y. Esra Albayrak
2013-01-01
Marketing establishes a communication network between producers and consumers. Nowadays, marketing approach is customer-focused and products are directly oriented to meet customer needs. Marketing, which is a long process, needs organization and management. Therefore strategic marketing planning becomes more and more important in today’s competitive conditions. Main focus of this paper is to evaluate pricing strategies and select the best pricing strategy solution while considering internal a...
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
2018-05-01
Across biology, we are seeing rapid developments in scale of data production without a corresponding increase in data analysis capabilities. Here, we present Aether (http://aether.kosticlab.org), an intuitive, easy-to-use, cost-effective and scalable framework that uses linear programming to optimally bid on and deploy combinations of underutilized cloud computing resources. Our approach simultaneously minimizes the cost of data analysis and provides an easy transition from users' existing HPC pipelines. Data utilized are available at https://pubs.broadinstitute.org/diabimmune and with EBI SRA accession ERP005989. Source code is available at (https://github.com/kosticlab/aether). Examples, documentation and a tutorial are available at http://aether.kosticlab.org. chirag_patel@hms.harvard.edu or aleksandar.kostic@joslin.harvard.edu. Supplementary data are available at Bioinformatics online.
Compressor Surge Control Design Using Linear Matrix Inequality Approach
Uddin, Nur; Gravdahl, Jan Tommy
2017-01-01
A novel design for active compressor surge control system (ASCS) using linear matrix inequality (LMI) approach is presented and including a case study on piston-actuated active compressor surge control system (PAASCS). The non-linear system dynamics of the PAASCS is transformed into linear parameter varying (LPV) system dynamics. The system parameters are varying as a function of the compressor performance curve slope. A compressor surge stabilization problem is then formulated as a LMI probl...
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...
Evaluating forest management policies by parametric linear programing
Daniel I. Navon; Richard J. McConnen
1967-01-01
An analytical and simulation technique, parametric linear programing explores alternative conditions and devises an optimal management plan for each condition. Its application in solving policy-decision problems in the management of forest lands is illustrated in an example.
Formulated linear programming problems from game theory and its ...
African Journals Online (AJOL)
Formulated linear programming problems from game theory and its computer implementation using Tora package. ... Game theory, a branch of operations research examines the various concepts of decision ... AJOL African Journals Online.
Near-Regular Structure Discovery Using Linear Programming
Huang, Qixing; Guibas, Leonidas J.; Mitra, Niloy J.
2014-01-01
as an optimization and efficiently solve it using linear programming techniques. Our optimization has a discrete aspect, that is, the connectivity relationships among the elements, as well as a continuous aspect, namely the locations of the elements of interest. Both
A property of assignment type mixed integer linear programming problems
Benders, J.F.; van Nunen, J.A.E.E.
1982-01-01
In this paper we will proof that rather tight upper bounds can be given for the number of non-unique assignments that are achieved after solving the linear programming relaxation of some types of mixed integer linear assignment problems. Since in these cases the number of splitted assignments is
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.
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.
An overset grid approach to linear wave-structure interaction
DEFF Research Database (Denmark)
Read, Robert; Bingham, Harry B.
2012-01-01
A finite-difference based approach to wave-structure interaction is reported that employs the overset approach to grid generation. A two-dimensional code that utilizes the Overture C++ library has been developed to solve the linear radiation problem for a floating body of arbitrary form. This sof......A finite-difference based approach to wave-structure interaction is reported that employs the overset approach to grid generation. A two-dimensional code that utilizes the Overture C++ library has been developed to solve the linear radiation problem for a floating body of arbitrary form...
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,…
The RANDOM computer program: A linear congruential random number generator
Miles, R. F., Jr.
1986-01-01
The RANDOM Computer Program is a FORTRAN program for generating random number sequences and testing linear congruential random number generators (LCGs). The linear congruential form of random number generator is discussed, and the selection of parameters of an LCG for a microcomputer described. This document describes the following: (1) The RANDOM Computer Program; (2) RANDOM.MOD, the computer code needed to implement an LCG in a FORTRAN program; and (3) The RANCYCLE and the ARITH Computer Programs that provide computational assistance in the selection of parameters for an LCG. The RANDOM, RANCYCLE, and ARITH Computer Programs are written in Microsoft FORTRAN for the IBM PC microcomputer and its compatibles. With only minor modifications, the RANDOM Computer Program and its LCG can be run on most micromputers or mainframe computers.
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.
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 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…
A cutting- plane approach for semi- infinite mathematical programming
African Journals Online (AJOL)
Many situations ranging from industrial to social via economic and environmental problems may be cast into a Semi-infinite mathematical program. In this paper, the cutting-plane approach which lends itself better for standard non-linear programs is exploited with good reasons for grappling with linear, convex and ...
Alternate approaches to future electron-positron linear colliders
Energy Technology Data Exchange (ETDEWEB)
Loew, G.A. [Stanford Univ., CA (United States). Stanford Linear Accelerator Center
1998-07-01
The purpose of this article is two-fold: to review the current international status of various design approaches to the next generation of e{sup +}e{sup {minus}} linear colliders, and on the occasion of his 80th birthday, to celebrate Richard B. Neal`s many contributions to the field of linear accelerators. As it turns out, combining these two tasks is a rather natural enterprise because of Neal`s long professional involvement and insight into many of the problems and options which the international e{sup +}e{sup {minus}} linear collider community is currently studying to achieve a practical design for a future machine.
Alternate approaches to future electron-positron linear colliders
International Nuclear Information System (INIS)
Loew, G.A.
1998-01-01
The purpose of this article is two-fold: to review the current international status of various design approaches to the next generation of e + e - linear colliders, and on the occasion of his 80th birthday, to celebrate Richard B. Neal's many contributions to the field of linear accelerators. As it turns out, combining these two tasks is a rather natural enterprise because of Neal's long professional involvement and insight into many of the problems and options which the international e + e - linear collider community is currently studying to achieve a practical design for a future machine
Linear program differentiation for single-channel speech separation
DEFF Research Database (Denmark)
Pearlmutter, Barak A.; Olsson, Rasmus Kongsgaard
2006-01-01
Many apparently difficult problems can be solved by reduction to linear programming. Such problems are often subproblems within larger systems. When gradient optimisation of the entire larger system is desired, it is necessary to propagate gradients through the internally-invoked LP solver....... For instance, when an intermediate quantity z is the solution to a linear program involving constraint matrix A, a vector of sensitivities dE/dz will induce sensitivities dE/dA. Here we show how these can be efficiently calculated, when they exist. This allows algorithmic differentiation to be applied...... to algorithms that invoke linear programming solvers as subroutines, as is common when using sparse representations in signal processing. Here we apply it to gradient optimisation of over complete dictionaries for maximally sparse representations of a speech corpus. The dictionaries are employed in a single...
Linear Parametric Sensitivity Analysis of the Constraint Coefficient Matrix in Linear Programs
R.A. Zuidwijk (Rob)
2005-01-01
textabstractSensitivity analysis is used to quantify the impact of changes in the initial data of linear programs on the optimal value. In particular, parametric sensitivity analysis involves a perturbation analysis in which the effects of small changes of some or all of the initial data on an
Synthesizing Dynamic Programming Algorithms from Linear Temporal Logic Formulae
Rosu, Grigore; Havelund, Klaus
2001-01-01
The problem of testing a linear temporal logic (LTL) formula on a finite execution trace of events, generated by an executing program, occurs naturally in runtime analysis of software. We present an algorithm which takes an LTL formula and generates an efficient dynamic programming algorithm. The generated algorithm tests whether the LTL formula is satisfied by a finite trace of events given as input. The generated algorithm runs in linear time, its constant depending on the size of the LTL formula. The memory needed is constant, also depending on the size of the formula.
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.
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.
Non-linear nuclear engineering models as genetic programming application
International Nuclear Information System (INIS)
Domingos, Roberto P.; Schirru, Roberto; Martinez, Aquilino S.
1997-01-01
This work presents a Genetic Programming paradigm and a nuclear application. A field of Artificial Intelligence, based on the concepts of Species Evolution and Natural Selection, can be understood as a self-programming process where the computer is the main agent responsible for the discovery of a program able to solve a given problem. In the present case, the problem was to find a mathematical expression in symbolic form, able to express the existent relation between equivalent ratio of a fuel cell, the enrichment of fuel elements and the multiplication factor. Such expression would avoid repeatedly reactor physics codes execution for core optimization. The results were compared with those obtained by different techniques such as Neural Networks and Linear Multiple Regression. Genetic Programming has shown to present a performance as good as, and under some features superior to Neural Network and Linear Multiple Regression. (author). 10 refs., 8 figs., 1 tabs
A MICROCOMPUTER LINEAR PROGRAMMING PACKAGE: AN ALTERNATIVE TO MAINFRAMES
Laughlin, David H.
1984-01-01
This paper presents the capabilities and limitations of a microcomputer linear programming package. The solution algorithm is a version of the revised simplex. Rapid problem entry, user ease of operation, sensitivity analyses on objective function and right hand sides are advantages. A problem size of 150 activities and 64 constraints can be solved in present form. Due to problem size, limitations and lack of parametric and integer programming routines, this package is thought to have the mos...
Essential linear algebra with applications a problem-solving approach
Andreescu, Titu
2014-01-01
This textbook provides a rigorous introduction to linear algebra in addition to material suitable for a more advanced course while emphasizing the subject’s interactions with other topics in mathematics such as calculus and geometry. A problem-based approach is used to develop the theoretical foundations of vector spaces, linear equations, matrix algebra, eigenvectors, and orthogonality. Key features include: • a thorough presentation of the main results in linear algebra along with numerous examples to illustrate the theory; • over 500 problems (half with complete solutions) carefully selected for their elegance and theoretical significance; • an interleaved discussion of geometry and linear algebra, giving readers a solid understanding of both topics and the relationship between them. Numerous exercises and well-chosen examples make this text suitable for advanced courses at the junior or senior levels. It can also serve as a source of supplementary problems for a sophomore-level course. ...
Flow discharge prediction in compound channels using linear genetic programming
Azamathulla, H. Md.; Zahiri, A.
2012-08-01
SummaryFlow discharge determination in rivers is one of the key elements in mathematical modelling in the design of river engineering projects. Because of the inundation of floodplains and sudden changes in river geometry, flow resistance equations are not applicable for compound channels. Therefore, many approaches have been developed for modification of flow discharge computations. Most of these methods have satisfactory results only in laboratory flumes. Due to the ability to model complex phenomena, the artificial intelligence methods have recently been employed for wide applications in various fields of water engineering. Linear genetic programming (LGP), a branch of artificial intelligence methods, is able to optimise the model structure and its components and to derive an explicit equation based on the variables of the phenomena. In this paper, a precise dimensionless equation has been derived for prediction of flood discharge using LGP. The proposed model was developed using published data compiled for stage-discharge data sets for 394 laboratories, and field of 30 compound channels. The results indicate that the LGP model has a better performance than the existing models.
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.
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.
LCPT: a program for finding linear canonical transformations
International Nuclear Information System (INIS)
Char, B.W.; McNamara, B.
1979-01-01
This article describes a MACSYMA program to compute symbolically a canonical linear transformation between coordinate systems. The difficulties in implementation of this canonical small physics problem are also discussed, along with the implications that may be drawn from such difficulties about widespread MACSYMA usage by the community of computational/theoretical physicists
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.
Linear Programming, the Simplex Algorithm and Simple Polytopes
Directory of Open Access Journals (Sweden)
Das Bhusan
2010-09-01
Full Text Available In the first part of the paper we survey some far reaching applications of the basis facts of linear programming to the combinatorial theory of simple polytopes. In the second part we discuss some recent developments concurring the simplex algorithm. We describe sub-exponential randomized pivot roles and upper bounds on the diameter of graphs of polytopes.
A mixed integer linear program for an integrated fishery | Hasan ...
African Journals Online (AJOL)
... and labour allocation of quota based integrated fisheries. We demonstrate the workability of our model with a numerical example and sensitivity analysis based on data obtained from one of the major fisheries in New Zealand. Keywords: mixed integer linear program, fishing, trawler scheduling, processing, quotas ORiON: ...
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…
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…
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 BEHAVIORAL-APPROACH TO LINEAR EXACT MODELING
ANTOULAS, AC; WILLEMS, JC
1993-01-01
The behavioral approach to system theory provides a parameter-free framework for the study of the general problem of linear exact modeling and recursive modeling. The main contribution of this paper is the solution of the (continuous-time) polynomial-exponential time series modeling problem. Both
A convex optimization approach for solving large scale linear systems
Directory of Open Access Journals (Sweden)
Debora Cores
2017-01-01
Full Text Available The well-known Conjugate Gradient (CG method minimizes a strictly convex quadratic function for solving large-scale linear system of equations when the coefficient matrix is symmetric and positive definite. In this work we present and analyze a non-quadratic convex function for solving any large-scale linear system of equations regardless of the characteristics of the coefficient matrix. For finding the global minimizers, of this new convex function, any low-cost iterative optimization technique could be applied. In particular, we propose to use the low-cost globally convergent Spectral Projected Gradient (SPG method, which allow us to extend this optimization approach for solving consistent square and rectangular linear system, as well as linear feasibility problem, with and without convex constraints and with and without preconditioning strategies. Our numerical results indicate that the new scheme outperforms state-of-the-art iterative techniques for solving linear systems when the symmetric part of the coefficient matrix is indefinite, and also for solving linear feasibility problems.
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.
Train Repathing in Emergencies Based on Fuzzy Linear Programming
Directory of Open Access Journals (Sweden)
Xuelei Meng
2014-01-01
Full Text Available Train pathing is a typical problem which is to assign the train trips on the sets of rail segments, such as rail tracks and links. This paper focuses on the train pathing problem, determining the paths of the train trips in emergencies. We analyze the influencing factors of train pathing, such as transferring cost, running cost, and social adverse effect cost. With the overall consideration of the segment and station capability constraints, we build the fuzzy linear programming model to solve the train pathing problem. We design the fuzzy membership function to describe the fuzzy coefficients. Furthermore, the contraction-expansion factors are introduced to contract or expand the value ranges of the fuzzy coefficients, coping with the uncertainty of the value range of the fuzzy coefficients. We propose a method based on triangular fuzzy coefficient and transfer the train pathing (fuzzy linear programming model to a determinate linear model to solve the fuzzy linear programming problem. An emergency is supposed based on the real data of the Beijing-Shanghai Railway. The model in this paper was solved and the computation results prove the availability of the model and efficiency of the algorithm.
Train repathing in emergencies based on fuzzy linear programming.
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.
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 ...
Applications of equivalent linearization approaches to nonlinear piping systems
International Nuclear Information System (INIS)
Park, Y.; Hofmayer, C.; Chokshi, N.
1997-01-01
The piping systems in nuclear power plants, even with conventional snubber supports, are highly complex nonlinear structures under severe earthquake loadings mainly due to various mechanical gaps in support structures. Some type of nonlinear analysis is necessary to accurately predict the piping responses under earthquake loadings. The application of equivalent linearization approaches (ELA) to seismic analyses of nonlinear piping systems is presented. Two types of ELA's are studied; i.e., one based on the response spectrum method and the other based on the linear random vibration theory. The test results of main steam and feedwater piping systems supported by snubbers and energy absorbers are used to evaluate the numerical accuracy and limitations
Relaxation Methods for Strictly Convex Regularizations of Piecewise Linear Programs
International Nuclear Information System (INIS)
Kiwiel, K. C.
1998-01-01
We give an algorithm for minimizing the sum of a strictly convex function and a convex piecewise linear function. It extends several dual coordinate ascent methods for large-scale linearly constrained problems that occur in entropy maximization, quadratic programming, and network flows. In particular, it may solve exact penalty versions of such (possibly inconsistent) problems, and subproblems of bundle methods for nondifferentiable optimization. It is simple, can exploit sparsity, and in certain cases is highly parallelizable. Its global convergence is established in the recent framework of B -functions (generalized Bregman functions)
A LINEAR PROGRAMMING ALGORITHM FOR LEAST-COST SCHEDULING
Directory of Open Access Journals (Sweden)
AYMAN H AL-MOMANI
1999-12-01
Full Text Available In this research, some concepts of linear programming and critical path method are reviewed to describe recent modeling structures that have been of great value in analyzing extended planning horizon project time-cost trade-offs problems. A simplified representation of a small project and a linear programming model is formulated to represent this system. Procedures to solve these various problems formulations were cited and the final solution is obtained using LINDO program. The model developed represents many restrictions and management considerations of the project. It could be used by construction managers in a planning stage to explore numerous possible opportunities to the contractor and predict the effect of a decision on the construction to facilitate a preferred operating policy given different management objectives. An implementation using this method is shown to outperform several other techniques and a large class of test problems. Linear programming show that the algorithm is very promising in practice on a wide variety of time-cost trade-offs problems. This method is simple, applicable to a large network, and generates a shorter computational time at low cost, along with an increase in robustness.
A goal programming procedure for solving fuzzy multiobjective fractional linear programming problems
Directory of Open Access Journals (Sweden)
Tunjo Perić
2014-12-01
Full Text Available This paper presents a modification of Pal, Moitra and Maulik's goal programming procedure for fuzzy multiobjective linear fractional programming problem solving. The proposed modification of the method allows simpler solving of economic multiple objective fractional linear programming (MOFLP problems, enabling the obtained solutions to express the preferences of the decision maker defined by the objective function weights. The proposed method is tested on the production planning example.
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
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.
Fault detection and initial state verification by linear programming for a class of Petri nets
Rachell, Traxon; Meyer, David G.
1992-01-01
The authors present an algorithmic approach to determining when the marking of a LSMG (live safe marked graph) or a LSFC (live safe free choice) net is in the set of live safe markings M. Hence, once the marking of a net is determined to be in M, then if at some time thereafter the marking of this net is determined not to be in M, this indicates a fault. It is shown how linear programming can be used to determine if m is an element of M. The worst-case computational complexity of each algorithm is bounded by the number of linear programs necessary to compute.
Linear programming to build food-based dietary guidelines: Romanian food baskets
DEFF Research Database (Denmark)
Parlesak, Alexandr; Robertson, Aileen; Hondru, Gabriela
approach using linear programming methodology to design national dietary recommendations which aim to prevent both NCDs and micronutrient deficiencies and still be affordable by low income groups. This new approach is applied within the context of food availability in Romania in 2014. Eating the same food...... every day is unrealistic and too monotonous to be maintained, so this novel approach is used to select a wide range of diverse foods that can be recommended for a period of up to, for example, one month. The following are the key findings of this report. • The simplest version of the Romanian food.......65 lei (~€ 4.46) for a day. • Key nutrients, primarily vitamin D, calcium, potassium and iron, were found to control the overall price. • The least expensive basket (one day’s rations) is monotonous and the linear programming approach is used to select a wide range of foods that can be recommended...
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 programming approach to computability
Kfoury, A J; Arbib, Michael A
1982-01-01
Computability theory is at the heart of theoretical computer science. Yet, ironically, many of its basic results were discovered by mathematical logicians prior to the development of the first stored-program computer. As a result, many texts on computability theory strike today's computer science students as far removed from their concerns. To remedy this, we base our approach to computability on the language of while-programs, a lean subset of PASCAL, and postpone consideration of such classic models as Turing machines, string-rewriting systems, and p. -recursive functions till the final chapter. Moreover, we balance the presentation of un solvability results such as the unsolvability of the Halting Problem with a presentation of the positive results of modern programming methodology, including the use of proof rules, and the denotational semantics of programs. Computer science seeks to provide a scientific basis for the study of information processing, the solution of problems by algorithms, and the design ...
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...
Practical application of equivalent linearization approaches to nonlinear piping systems
International Nuclear Information System (INIS)
Park, Y.J.; Hofmayer, C.H.
1995-01-01
The use of mechanical energy absorbers as an alternative to conventional hydraulic and mechanical snubbers for piping supports has attracted a wide interest among researchers and practitioners in the nuclear industry. The basic design concept of energy absorbers (EA) is to dissipate the vibration energy of piping systems through nonlinear hysteretic actions of EA exclamation point s under design seismic loads. Therefore, some type of nonlinear analysis needs to be performed in the seismic design of piping systems with EA supports. The equivalent linearization approach (ELA) can be a practical analysis tool for this purpose, particularly when the response approach (RSA) is also incorporated in the analysis formulations. In this paper, the following ELA/RSA methods are presented and compared to each other regarding their practice and numerical accuracy: Response approach using the square root of sum of squares (SRSS) approximation (denoted RS in this paper). Classical ELA based on modal combinations and linear random vibration theory (denoted CELA in this paper). Stochastic ELA based on direct solution of response covariance matrix (denoted SELA in this paper). New algorithms to convert response spectra to the equivalent power spectral density (PSD) functions are presented for both the above CELA and SELA methods. The numerical accuracy of the three EL are studied through a parametric error analysis. Finally, the practicality of the presented analysis is demonstrated in two application examples for piping systems with EA supports
International Nuclear Information System (INIS)
Reibel, R.R.; Barber, Z.W.; Fischer, J.A.; Tian, M.; Babbitt, W.R.
2004-01-01
Linear sideband chirped (LSC) programming is introduced as a means of configuring spatial-spectral holographic gratings for optical coherent transient processors. Similar to linear frequency chirped programming, LSC programming allows the use of broadband integrated electro-optic phase modulators to produce chirps instead of using elaborate broadband chirped lasers. This approach has several advantages including the ability to use a stabilized laser for the optical carrier as well as stable, reproducible chirped optical signals when the modulator is driven digitally. Using LSC programming, we experimentally demonstrate broadband true-time delay as a proof of principle for the optical control of phased array radars. Here both cw phase modulated and binary phase shift keyed probe signals are true-time delayed with bandwidths of 1 GHz and delay resolutions better than 60 ps
Approach to assurance of reliability of linear accelerator operation observations
International Nuclear Information System (INIS)
Bakov, S.M.; Borovikov, A.A.; Kavkun, S.L.
1994-01-01
The system approach to solving the task of assuring reliability of observations over the linear accelerator operation is proposed. The basic principles of this method consist in application of dependences between the facility parameters, decrease in the number of the system apparatus channels for data acquisition without replacement of failed channel by reserve one. The signal commutation unit, the introduction whereof into the data acquisition system essentially increases the reliability of the measurement system on the account of active reserve, is considered detail. 8 refs. 6 figs
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.
Economic planning for electric energy systems: a multi objective linearized approach for solution
International Nuclear Information System (INIS)
Mata Medeiros Branco, T. da.
1986-01-01
The economic planning problem associated to the expansion and operation of electrical power systems is considered in this study, represented for a vectorial objective function in which the minimization of resources involved and maximization of attended demand constitute goals to be satisfied. Supposing all the variables involved with linear characteristic and considering the conflict existing among the objectives to be achieved, in order to find a solution, a multi objective linearized approach is proposed. This approximation utilizes the compromise programming technique and linear programming methods. Generation and transmission are simultaneously considered into the optimization process in which associated losses and the capacity of each line are included. Illustrated examples are also presented with results discussed. (author)
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 scalable parallel algorithm for multiple objective linear programs
Wiecek, Malgorzata M.; Zhang, Hong
1994-01-01
This paper presents an ADBASE-based parallel algorithm for solving multiple objective linear programs (MOLP's). Job balance, speedup and scalability are of primary interest in evaluating efficiency of the new algorithm. Implementation results on Intel iPSC/2 and Paragon multiprocessors show that the algorithm significantly speeds up the process of solving MOLP's, which is understood as generating all or some efficient extreme points and unbounded efficient edges. The algorithm gives specially good results for large and very large problems. Motivation and justification for solving such large MOLP's are also included.
The MARX Modulator Development Program for the International Linear Collider
International Nuclear Information System (INIS)
Leyh, G.E.
2006-01-01
The International Linear Collider (ILC) Marx Modulator Development Program at SLAC is working towards developing a full-scale ILC Marx ''Reference Design'' modulator prototype, with the goal of significantly reducing the size and cost of the ILC modulator while improving overall modulator efficiency and availability. The ILC Reference Design prototype will provide a proof-of-concept model to industry in advance of Phase II SBIR funding, and also allow operation of the new 10MW L-Band Klystron prototypes immediately upon their arrival at SLAC
Marginal cost of electricity conservation: an application of linear program
International Nuclear Information System (INIS)
Silveira, A.M. da; Hollanda, J.B. de
1987-01-01
This paper is addressed ti the planning of electricity industry when the use of energetically efficient appliances (conservation) is financed by the utilities. It is based on the Linear Programming Model proposed by Masse and Boiteaux for planning of conventional energy sources, where one unity of electricity (Kw/Kw h) saved is treated as if it were a generator of equivalent size. In spite of the formal simplicity of the models it can support interesting concessions on the subject of a electrical energy conservation policy. (author)
Angular spectrum approach for fast simulation of pulsed non-linear ultrasound fields
DEFF Research Database (Denmark)
Du, Yigang; Jensen, Henrik; Jensen, Jørgen Arendt
2011-01-01
The paper presents an Angular Spectrum Approach (ASA) for simulating pulsed non-linear ultrasound fields. The source of the ASA is generated by Field II, which can simulate array transducers of any arbitrary geometry and focusing. The non-linear ultrasound simulation program - Abersim, is used...... as the reference. A linear array transducer with 64 active elements is simulated by both Field II and Abersim. The excitation is a 2-cycle sine wave with a frequency of 5 MHz. The second harmonic field in the time domain is simulated using ASA. Pulse inversion is used in the Abersim simulation to remove...... the fundamental and keep the second harmonic field, since Abersim simulates non-linear fields with all harmonic components. ASA and Abersim are compared for the pulsed fundamental and second harmonic fields in the time domain at depths of 30 mm, 40 mm (focal depth) and 60 mm. Full widths at -6 dB (FWHM) are f0...
Polymorphic Uncertain Linear Programming for Generalized Production Planning Problems
Directory of Open Access Journals (Sweden)
Xinbo Zhang
2014-01-01
Full Text Available A polymorphic uncertain linear programming (PULP model is constructed to formulate a class of generalized production planning problems. In accordance with the practical environment, some factors such as the consumption of raw material, the limitation of resource and the demand of product are incorporated into the model as parameters of interval and fuzzy subsets, respectively. Based on the theory of fuzzy interval program and the modified possibility degree for the order of interval numbers, a deterministic equivalent formulation for this model is derived such that a robust solution for the uncertain optimization problem is obtained. Case study indicates that the constructed model and the proposed solution are useful to search for an optimal production plan for the polymorphic uncertain generalized production planning problems.
Novel Approach to Linear Accelerator Superconducting Magnet System
International Nuclear Information System (INIS)
Kashikhin, Vladimir
2011-01-01
Superconducting Linear Accelerators include a superconducting magnet system for particle beam transportation that provides the beam focusing and steering. This system consists of a large number of quadrupole magnets and dipole correctors mounted inside or between cryomodules with SCRF cavities. Each magnet has current leads and powered from its own power supply. The paper proposes a novel approach to magnet powering based on using superconducting persistent current switches. A group of magnets is powered from the same power supply through the common, for the group of cryomodules, electrical bus and pair of current leads. Superconducting switches direct the current to the chosen magnet and close the circuit providing the magnet operation in a persistent current mode. Two persistent current switches were fabricated and tested. In the paper also presented the results of magnetic field simulations, decay time constants analysis, and a way of improving quadrupole magnetic center stability. Such approach substantially reduces the magnet system cost and increases the reliability.
Review of the superconducting approach to linear colliders
International Nuclear Information System (INIS)
Padamsee, H.
1992-01-01
For the next linear collider of 500 GeV CM energy, the beam energy needs to be increased by a factor of 5 over the SLC, but the luminosity needs to be increased by 5 orders of magnitude. The superconducting (SRF) approach offers multiple relief from the many pressing challenges of achieving high luminosity. The major challenges for the SRF approach are to raise the gradients well above 5 MV/m possible today and at the same time to lower the costs. Progress in SRF technology is presented. A collaborative venture on a TESLA TEST FACILITY is now taking shape, these activities are summarized. (R.P.) 19 refs.; 4 figs.; 3 tabs
AN APPLICATION FOR EFFICIENT TELECOMMUNICATION NETWORKS PROVISIONING USING LINEAR PROGRAMMING
Directory of Open Access Journals (Sweden)
Maria Augusta Soares Machado
2015-03-01
Full Text Available This paper presents a practical proposition for the application of the Linear Programming quantitative method in order to assist planning and control of customer circuit delivery activities in telecommunications companies working with the corporative market. Based upon data provided for by a telecom company operating in Brazil, the Linear Programming method was employed for one of the classical problems of determining the optimum mix of production quantities for a set of five products of that company: Private Telephone Network, Internet Network, Intranet Network, Low Speed Data Network, and High Speed Data Network, in face of several limitations of the productive resources, seeking to maximize the company’s monthly revenue. By fitting the production data available into a primary model, observation was made as to what number of monthly activations for each product would be mostly optimized in order to achieve maximum revenues in the company. The final delivery of a complete network was not observed but the delivery of the circuits that make it up, and this was a limiting factor for the study herein, which, however, brings an innovative proposition for the planning of private telecommunications network provisioning.
Linear programming based on neural networks for radiotherapy treatment planning
International Nuclear Information System (INIS)
Xingen Wu; Limin Luo
2000-01-01
In this paper, we propose a neural network model for linear programming that is designed to optimize radiotherapy treatment planning (RTP). This kind of neural network can be easily implemented by using a kind of 'neural' electronic system in order to obtain an optimization solution in real time. We first give an introduction to the RTP problem and construct a non-constraint objective function for the neural network model. We adopt a gradient algorithm to minimize the objective function and design the structure of the neural network for RTP. Compared to traditional linear programming methods, this neural network model can reduce the time needed for convergence, the size of problems (i.e., the number of variables to be searched) and the number of extra slack and surplus variables needed. We obtained a set of optimized beam weights that result in a better dose distribution as compared to that obtained using the simplex algorithm under the same initial condition. The example presented in this paper shows that this model is feasible in three-dimensional RTP. (author)
A Study of Joint Cost Inclusion in Linear Programming Optimization
Directory of Open Access Journals (Sweden)
P. Armaos
2013-08-01
Full Text Available The concept of Structural Optimization has been a topic or research over the past century. Linear Programming Optimization has proved being the most reliable method of structural optimization. Global advances in linear programming optimization have been recently powered by University of Sheffield researchers, to include joint cost, self-weight and buckling considerations. A joint cost inclusion scopes to reduce the number of joints existing in an optimized structural solution, transforming it to a practically viable solution. The topic of the current paper is to investigate the effects of joint cost inclusion, as this is currently implemented in the optimization code. An extended literature review on this subject was conducted prior to familiarization with small scale optimization software. Using IntelliFORM software, a structured series of problems were set and analyzed. The joint cost tests examined benchmark problems and their consequent changes in the member topology, as the design domain was expanding. The findings of the analyses were remarkable and are being commented further on. The distinct topologies of solutions created by optimization processes are also recognized. Finally an alternative strategy of penalizing joints is presented.
A Compensatory Approach to Multiobjective Linear Transportation Problem with Fuzzy Cost Coefficients
Directory of Open Access Journals (Sweden)
Hale Gonce Kocken
2011-01-01
Full Text Available This paper deals with the Multiobjective Linear Transportation Problem that has fuzzy cost coefficients. In the solution procedure, many objectives may conflict with each other; therefore decision-making process becomes complicated. And also due to the fuzziness in the costs, this problem has a nonlinear structure. In this paper, fuzziness in the objective functions is handled with a fuzzy programming technique in the sense of multiobjective approach. And then we present a compensatory approach to solve Multiobjective Linear Transportation Problem with fuzzy cost coefficients by using Werner's and operator. Our approach generates compromise solutions which are both compensatory and Pareto optimal. A numerical example has been provided to illustrate the problem.
A Unique Technique to get Kaprekar Iteration in Linear Programming Problem
Sumathi, P.; Preethy, V.
2018-04-01
This paper explores about a frivolous number popularly known as Kaprekar constant and Kaprekar numbers. A large number of courses and the different classroom capacities with difference in study periods make the assignment between classrooms and courses complicated. An approach of getting the minimum value of number of iterations to reach the Kaprekar constant for four digit numbers and maximum value is also obtained through linear programming techniques.
Electrostatic Discharge Current Linear Approach and Circuit Design Method
Directory of Open Access Journals (Sweden)
Pavlos K. Katsivelis
2010-11-01
Full Text Available The Electrostatic Discharge phenomenon is a great threat to all electronic devices and ICs. An electric charge passing rapidly from a charged body to another can seriously harm the last one. However, there is a lack in a linear mathematical approach which will make it possible to design a circuit capable of producing such a sophisticated current waveform. The commonly accepted Electrostatic Discharge current waveform is the one set by the IEC 61000-4-2. However, the over-simplified circuit included in the same standard is incapable of producing such a waveform. Treating the Electrostatic Discharge current waveform of the IEC 61000-4-2 as reference, an approximation method, based on Prony’s method, is developed and applied in order to obtain a linear system’s response. Considering a known input, a method to design a circuit, able to generate this ESD current waveform in presented. The circuit synthesis assumes ideal active elements. A simulation is carried out using the PSpice software.
Aihong Ren
2016-01-01
This paper is concerned with a class of fully fuzzy bilevel linear programming problems where all the coefficients and decision variables of both objective functions and the constraints are fuzzy numbers. A new approach based on deviation degree measures and a ranking function method is proposed to solve these problems. We first introduce concepts of the feasible region and the fuzzy optimal solution of a fully fuzzy bilevel linear programming problem. In order to obtain a fuzzy optimal solut...
A Dynamic Linear Modeling Approach to Public Policy Change
DEFF Research Database (Denmark)
Loftis, Matthew; Mortensen, Peter Bjerre
2017-01-01
Theories of public policy change, despite their differences, converge on one point of strong agreement. The relationship between policy and its causes can and does change over time. This consensus yields numerous empirical implications, but our standard analytical tools are inadequate for testing...... them. As a result, the dynamic and transformative relationships predicted by policy theories have been left largely unexplored in time-series analysis of public policy. This paper introduces dynamic linear modeling (DLM) as a useful statistical tool for exploring time-varying relationships in public...... policy. The paper offers a detailed exposition of the DLM approach and illustrates its usefulness with a time series analysis of U.S. defense policy from 1957-2010. The results point the way for a new attention to dynamics in the policy process and the paper concludes with a discussion of how...
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.
CONTRIBUTION OF A LINEAR PROGRAMMING VBA MODULE TO STUDENTS PEFORMANCE
Directory of Open Access Journals (Sweden)
KUČÍRKOVÁ Lenka
2010-12-01
Full Text Available This paper deals with the application of freeware modules as a teaching support of Operations Research methods at the Department of Systems Engineering, Czech university of Life Sciences (CULS Prague. In particular, we concentrated on a linear programming module and measured the impact on student performance. The motivation for this evaluation is based on a current development of a new module that focuses on Traveling Salesman Problem. First, we explain the current situation both worldwide and in the Czech Republic and the CULS Prague. Subsequently, we describe the content of students’ exams and statistical methods applied to the evaluation. Finally, we analyze and generalize the obtained results. The students exams have show a positive impact of the modules. Further, our analysis has proven that this impact is statistically significant. The findings motivate us to made new modules for other methods.
Local beam angle optimization with linear programming and gradient search
International Nuclear Information System (INIS)
Craft, David
2007-01-01
The optimization of beam angles in IMRT planning is still an open problem, with literature focusing on heuristic strategies and exhaustive searches on discrete angle grids. We show how a beam angle set can be locally refined in a continuous manner using gradient-based optimization in the beam angle space. The gradient is derived using linear programming duality theory. Applying this local search to 100 random initial angle sets of a phantom pancreatic case demonstrates the method, and highlights the many-local-minima aspect of the BAO problem. Due to this function structure, we recommend a search strategy of a thorough global search followed by local refinement at promising beam angle sets. Extensions to nonlinear IMRT formulations are discussed. (note)
Optimization of refinery product blending by using linear programming
International Nuclear Information System (INIS)
Ristikj, Julija; Tripcheva-Trajkovska, Loreta; Rikaloski, Ice; Markovska, Liljana
1999-01-01
The product slate of a simple refinery consists mainly of liquefied petroleum gas, leaded and unleaded gasoline, jet fuel, diesel fuel, extra light heating oil and fuel oil. The quality of the oil products (fuels) for sale has to comply with the adopted standards for liquid fuels, and the produced quantities have to be comply with the market needs. The oil products are manufactured by blending two or more different fractions which quantities and physical-chemical properties depend on the crude oil type, the way and conditions of processing, and at the same time the fractions are used to blend one or more products. It is in producer's interest to do the blending in an optimal way, namely, to satisfy the requirements for the oil products quality and quantity with a maximal usage of the available fractions and, of course, with a maximal profit out of the sold products. This could be accomplished by applying linear programming, that is by using a linear model for oil products blending optimization. (Author)
C-program LINOP for the evaluation of film dosemeters by linear optimization. User manual
International Nuclear Information System (INIS)
Kragh, P.
1995-11-01
Linear programming results in an optimal measuring value for film dosemeters. The Linop program was developed to be used for linear programming. The program permits the evaluation and control of film dosemeters and of all other multi-component dosemeters. This user manual for the Linop program contains the source program, a description of the program and installation and use instructions. The data sets with programs and examples are available upon request. (orig.) [de
Linear mixed-effects modeling approach to FMRI group analysis.
Chen, Gang; Saad, Ziad S; Britton, Jennifer C; Pine, Daniel S; Cox, Robert W
2013-06-01
Conventional group analysis is usually performed with Student-type t-test, regression, or standard AN(C)OVA in which the variance-covariance matrix is presumed to have a simple structure. Some correction approaches are adopted when assumptions about the covariance structure is violated. However, as experiments are designed with different degrees of sophistication, these traditional methods can become cumbersome, or even be unable to handle the situation at hand. For example, most current FMRI software packages have difficulty analyzing the following scenarios at group level: (1) taking within-subject variability into account when there are effect estimates from multiple runs or sessions; (2) continuous explanatory variables (covariates) modeling in the presence of a within-subject (repeated measures) factor, multiple subject-grouping (between-subjects) factors, or the mixture of both; (3) subject-specific adjustments in covariate modeling; (4) group analysis with estimation of hemodynamic response (HDR) function by multiple basis functions; (5) various cases of missing data in longitudinal studies; and (6) group studies involving family members or twins. Here we present a linear mixed-effects modeling (LME) methodology that extends the conventional group analysis approach to analyze many complicated cases, including the six prototypes delineated above, whose analyses would be otherwise either difficult or unfeasible under traditional frameworks such as AN(C)OVA and general linear model (GLM). In addition, the strength of the LME framework lies in its flexibility to model and estimate the variance-covariance structures for both random effects and residuals. The intraclass correlation (ICC) values can be easily obtained with an LME model with crossed random effects, even at the presence of confounding fixed effects. The simulations of one prototypical scenario indicate that the LME modeling keeps a balance between the control for false positives and the sensitivity
DEFF Research Database (Denmark)
Cetin, Bilge Kartal; Prasad, Neeli R.; Prasad, Ramjee
2011-01-01
In wireless sensor networks, one of the key challenge is to achieve minimum energy consumption in order to maximize network lifetime. In fact, lifetime depends on many parameters: the topology of the sensor network, the data aggregation regime in the network, the channel access schemes, the routing...... protocols, and the energy model for transmission. In this paper, we tackle the routing challenge for maximum lifetime of the sensor network. We introduce a novel linear programming approach to the maximum lifetime routing problem. To the best of our knowledge, this is the first mathematical programming...
Mixed Integer Linear Programming model for Crude Palm Oil Supply Chain Planning
Sembiring, Pasukat; Mawengkang, Herman; Sadyadharma, Hendaru; Bu'ulolo, F.; Fajriana
2018-01-01
The production process of crude palm oil (CPO) can be defined as the milling process of raw materials, called fresh fruit bunch (FFB) into end products palm oil. The process usually through a series of steps producing and consuming intermediate products. The CPO milling industry considered in this paper does not have oil palm plantation, therefore the FFB are supplied by several public oil palm plantations. Due to the limited availability of FFB, then it is necessary to choose from which plantations would be appropriate. This paper proposes a mixed integer linear programming model the supply chain integrated problem, which include waste processing. The mathematical programming model is solved using neighborhood search approach.
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.
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.
Hlaing, Lwin Mar; Fahmida, Umi; Htet, Min Kyaw; Utomo, Budi; Firmansyah, Agus; Ferguson, Elaine L
2016-07-01
Poor feeding practices result in inadequate nutrient intakes in young children in developing countries. To improve practices, local food-based complementary feeding recommendations (CFR) are needed. This cross-sectional survey aimed to describe current food consumption patterns of 12-23-month-old Myanmar children (n 106) from Ayeyarwady region in order to identify nutrient requirements that are difficult to achieve using local foods and to formulate affordable and realistic CFR to improve dietary adequacy. Weekly food consumption patterns were assessed using a 12-h weighed dietary record, single 24-h recall and a 5-d food record. Food costs were estimated by market surveys. CFR were formulated by linear programming analysis using WHO Optifood software and evaluated among mothers (n 20) using trial of improved practices (TIP). Findings showed that Ca, Zn, niacin, folate and Fe were 'problem nutrients': nutrients that did not achieve 100 % recommended nutrient intake even when the diet was optimised. Chicken liver, anchovy and roselle leaves were locally available nutrient-dense foods that would fill these nutrient gaps. The final set of six CFR would ensure dietary adequacy for five of twelve nutrients at a minimal cost of 271 kyats/d (based on the exchange rate of 900 kyats/USD at the time of data collection: 3rd quarter of 2012), but inadequacies remained for niacin, folate, thiamin, Fe, Zn, Ca and vitamin B6. TIP showed that mothers believed liver and vegetables would cause worms and diarrhoea, but these beliefs could be overcome to successfully promote liver consumption. Therefore, an acceptable set of CFR were developed to improve the dietary practices of 12-23-month-old Myanmar children using locally available foods. Alternative interventions such as fortification, however, are still needed to ensure dietary adequacy of all nutrients.
Dzielski, John Edward
1988-01-01
Recent developments in the area of nonlinear control theory have shown how coordiante changes in the state and input spaces can be used with nonlinear feedback to transform certain nonlinear ordinary differential equations into equivalent linear equations. These feedback linearization techniques are applied to resolve two problems arising in the control of spacecraft equipped with control moment gyroscopes (CMGs). The first application involves the computation of rate commands for the gimbals that rotate the individual gyroscopes to produce commanded torques on the spacecraft. The second application is to the long-term management of stored momentum in the system of control moment gyroscopes using environmental torques acting on the vehicle. An approach to distributing control effort among a group of redundant actuators is described that uses feedback linearization techniques to parameterize sets of controls which influence a specified subsystem in a desired way. The approach is adapted for use in spacecraft control with double-gimballed gyroscopes to produce an algorithm that avoids problematic gimbal configurations by approximating sets of gimbal rates that drive CMG rotors into desirable configurations. The momentum management problem is stated as a trajectory optimization problem with a nonlinear dynamical constraint. Feedback linearization and collocation are used to transform this problem into an unconstrainted nonlinear program. The approach to trajectory optimization is fast and robust. A number of examples are presented showing applications to the proposed NASA space station.
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)
APPLYING ROBUST RANKING METHOD IN TWO PHASE FUZZY OPTIMIZATION LINEAR PROGRAMMING PROBLEMS (FOLPP
Directory of Open Access Journals (Sweden)
Monalisha Pattnaik
2014-12-01
Full Text Available Background: This paper explores the solutions to the fuzzy optimization linear program problems (FOLPP where some parameters are fuzzy numbers. In practice, there are many problems in which all decision parameters are fuzzy numbers, and such problems are usually solved by either probabilistic programming or multi-objective programming methods. Methods: In this paper, using the concept of comparison of fuzzy numbers, a very effective method is introduced for solving these problems. This paper extends linear programming based problem in fuzzy environment. With the problem assumptions, the optimal solution can still be theoretically solved using the two phase simplex based method in fuzzy environment. To handle the fuzzy decision variables can be initially generated and then solved and improved sequentially using the fuzzy decision approach by introducing robust ranking technique. Results and conclusions: The model is illustrated with an application and a post optimal analysis approach is obtained. The proposed procedure was programmed with MATLAB (R2009a version software for plotting the four dimensional slice diagram to the application. Finally, numerical example is presented to illustrate the effectiveness of the theoretical results, and to gain additional managerial insights.
Implementing corporate wellness programs: a business approach to program planning.
Helmer, D C; Dunn, L M; Eaton, K; Macedonio, C; Lubritz, L
1995-11-01
1. Support of key decision makers is critical to the successful implementation of a corporate wellness program. Therefore, the program implementation plan must be communicated in a format and language readily understood by business people. 2. A business approach to corporate wellness program planning provides a standardized way to communicate the implementation plan. 3. A business approach incorporates the program planning components in a format that ranges from general to specific. This approach allows for flexibility and responsiveness to changes in program planning. 4. Components of the business approach are the executive summary, purpose, background, ground rules, approach, requirements, scope of work, schedule, and financials.
A New Interpolation Approach for Linearly Constrained Convex Optimization
Espinoza, Francisco
2012-08-01
In this thesis we propose a new class of Linearly Constrained Convex Optimization methods based on the use of a generalization of Shepard\\'s interpolation formula. We prove the properties of the surface such as the interpolation property at the boundary of the feasible region and the convergence of the gradient to the null space of the constraints at the boundary. We explore several descent techniques such as steepest descent, two quasi-Newton methods and the Newton\\'s method. Moreover, we implement in the Matlab language several versions of the method, particularly for the case of Quadratic Programming with bounded variables. Finally, we carry out performance tests against Matab Optimization Toolbox methods for convex optimization and implementations of the standard log-barrier and active-set methods. We conclude that the steepest descent technique seems to be the best choice so far for our method and that it is competitive with other standard methods both in performance and empirical growth order.
International Nuclear Information System (INIS)
Shimizu, Yoshiaki
1981-01-01
A mathematical procedure is proposed to make a radioactive waste management plan comprehensively. Since such planning is relevant to some different goals in management, decision making has to be formulated as a multiobjective optimization problem. A mathematical programming method was introduced to make a decision through an interactive manner which enables us to assess the preference of decision maker step by step among the conflicting objectives. The reference system taken as an example is the radioactive waste management system at the Research Reactor Institute of Kyoto University (KUR). Its linear model was built based on the experience in the actual management at KUR. The best-compromise model was then formulated as a multiobjective linear programming by the aid of the computational analysis through a conventional optimization. It was shown from the numerical results that the proposed approach could provide some useful informations to make an actual management plan. (author)
Linear response theory an analytic-algebraic approach
De Nittis, Giuseppe
2017-01-01
This book presents a modern and systematic approach to Linear Response Theory (LRT) by combining analytic and algebraic ideas. LRT is a tool to study systems that are driven out of equilibrium by external perturbations. In particular the reader is provided with a new and robust tool to implement LRT for a wide array of systems. The proposed formalism in fact applies to periodic and random systems in the discrete and the continuum. After a short introduction describing the structure of the book, its aim and motivation, the basic elements of the theory are presented in chapter 2. The mathematical framework of the theory is outlined in chapters 3–5: the relevant von Neumann algebras, noncommutative $L^p$- and Sobolev spaces are introduced; their construction is then made explicit for common physical systems; the notion of isopectral perturbations and the associated dynamics are studied. Chapter 6 is dedicated to the main results, proofs of the Kubo and Kubo-Streda formulas. The book closes with a chapter about...
Approximate labeling via graph cuts based on linear programming.
Komodakis, Nikos; Tziritas, Georgios
2007-08-01
A new framework is presented for both understanding and developing graph-cut-based combinatorial algorithms suitable for the approximate optimization of a very wide class of Markov Random Fields (MRFs) that are frequently encountered in computer vision. The proposed framework utilizes tools from the duality theory of linear programming in order to provide an alternative and more general view of state-of-the-art techniques like the \\alpha-expansion algorithm, which is included merely as a special case. Moreover, contrary to \\alpha-expansion, the derived algorithms generate solutions with guaranteed optimality properties for a much wider class of problems, for example, even for MRFs with nonmetric potentials. In addition, they are capable of providing per-instance suboptimality bounds in all occasions, including discrete MRFs with an arbitrary potential function. These bounds prove to be very tight in practice (that is, very close to 1), which means that the resulting solutions are almost optimal. Our algorithms' effectiveness is demonstrated by presenting experimental results on a variety of low-level vision tasks, such as stereo matching, image restoration, image completion, and optical flow estimation, as well as on synthetic problems.
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.
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.
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.
Storage and distribution/Linear programming for storage operations
Energy Technology Data Exchange (ETDEWEB)
Coleman, D
1978-07-15
The techniques of linear programing to solve storage problems as applied in a tank farm tie-in with refinery throughput operation include: (1) the time-phased model which works on storage and refinery operations input parameters, e.g., production, distribution, cracking, etc., and is capable of representing product stockpiling in slack periods to meet future peak demands, and investigating alternative strategies such as exchange deals and purchase and leasing of additional storage, and (2) the Monte Carlo simulation method, which inputs parameters, e.g., arrival of crude products at refinery, tankage size, likely demand for products, etc., as probability distributions rather than single values, and is capable of showing the average utilization of facilities, potential bottlenecks, investment required to achieve an increase in utilization, and to enable the user to predict total investment, cash flow, and profit emanating from the original financing decision. The increasing use of computer techniques to solve refinery and storage problems is attributed to potential savings resulting from more effective planning, reduced computer costs, ease of access and more usable software. Diagrams.
Mixed integer linear programming for maximum-parsimony phylogeny inference.
Sridhar, Srinath; Lam, Fumei; Blelloch, Guy E; Ravi, R; Schwartz, Russell
2008-01-01
Reconstruction of phylogenetic trees is a fundamental problem in computational biology. While excellent heuristic methods are available for many variants of this problem, new advances in phylogeny inference will be required if we are to be able to continue to make effective use of the rapidly growing stores of variation data now being gathered. In this paper, we present two integer linear programming (ILP) formulations to find the most parsimonious phylogenetic tree from a set of binary variation data. One method uses a flow-based formulation that can produce exponential numbers of variables and constraints in the worst case. The method has, however, proven extremely efficient in practice on datasets that are well beyond the reach of the available provably efficient methods, solving several large mtDNA and Y-chromosome instances within a few seconds and giving provably optimal results in times competitive with fast heuristics than cannot guarantee optimality. An alternative formulation establishes that the problem can be solved with a polynomial-sized ILP. We further present a web server developed based on the exponential-sized ILP that performs fast maximum parsimony inferences and serves as a front end to a database of precomputed phylogenies spanning the human genome.
Modern linear control design a time-domain approach
Caravani, Paolo
2013-01-01
This book offers a compact introduction to modern linear control design. The simplified overview presented of linear time-domain methodology paves the road for the study of more advanced non-linear techniques. Only rudimentary knowledge of linear systems theory is assumed - no use of Laplace transforms or frequency design tools is required. Emphasis is placed on assumptions and logical implications, rather than abstract completeness; on interpretation and physical meaning, rather than theoretical formalism; on results and solutions, rather than derivation or solvability. The topics covered include transient performance and stabilization via state or output feedback; disturbance attenuation and robust control; regional eigenvalue assignment and constraints on input or output variables; asymptotic regulation and disturbance rejection. Lyapunov theory and Linear Matrix Inequalities (LMI) are discussed as key design methods. All methods are demonstrated with MATLAB to promote practical use and comprehension. ...
Pilkey, W. D.; Chen, Y. H.
1974-01-01
An indirect synthesis method is used in the efficient optimal design of multi-degree of freedom, multi-design element, nonlinear, transient systems. A limiting performance analysis which requires linear programming for a kinematically linear system is presented. The system is selected using system identification methods such that the designed system responds as closely as possible to the limiting performance. The efficiency is a result of the method avoiding the repetitive systems analyses accompanying other numerical optimization methods.
The use of linear programming in optimization of HDR implant dose distributions
International Nuclear Information System (INIS)
Jozsef, Gabor; Streeter, Oscar E.; Astrahan, Melvin A.
2003-01-01
The introduction of high dose rate brachytherapy enabled optimization of dose distributions to be used on a routine basis. The objective of optimization is to homogenize the dose distribution within the implant while simultaneously satisfying dose constraints on certain points. This is accomplished by varying the time the source dwells at different locations. As the dose at any point is a linear function of the dwell times, a linear programming approach seems to be a natural choice. The dose constraints are inherently linear inequalities. Homogeneity requirements are linearized by minimizing the maximum deviation of the doses at points inside the implant from a prescribed dose. The revised simplex method was applied for the solution of this linear programming problem. In the homogenization process the possible source locations were chosen as optimization points. To avoid the problem of the singular value of the dose at a source location from the source itself we define the 'self-contribution' as the dose at a small distance from the source. The effect of varying this distance is discussed. Test cases were optimized for planar, biplanar and cylindrical implants. A semi-irregular, fan-like implant with diverging needles was also investigated. Mean central dose calculation based on 3D Delaunay-triangulation of the source locations was used to evaluate the dose distributions. The optimization method resulted in homogeneous distributions (for brachytherapy). Additional dose constraints--when applied--were satisfied. The method is flexible enough to include other linear constraints such as the inclusion of the centroids of the Delaunay-triangulation for homogenization, or limiting the maximum allowable dwell time
NP-Hardness of optimizing the sum of Rational Linear Functions over an Asymptotic-Linear-Program
Chermakani, Deepak Ponvel
2012-01-01
We convert, within polynomial-time and sequential processing, an NP-Complete Problem into a real-variable problem of minimizing a sum of Rational Linear Functions constrained by an Asymptotic-Linear-Program. The coefficients and constants in the real-variable problem are 0, 1, -1, K, or -K, where K is the time parameter that tends to positive infinity. The number of variables, constraints, and rational linear functions in the objective, of the real-variable problem is bounded by a polynomial ...
Linear programming model can explain respiration of fermentation products
Möller, Philip; Liu, Xiaochen; Schuster, Stefan
2018-01-01
Many differentiated cells rely primarily on mitochondrial oxidative phosphorylation for generating energy in the form of ATP needed for cellular metabolism. In contrast most tumor cells instead rely on aerobic glycolysis leading to lactate to about the same extent as on respiration. Warburg found that cancer cells to support oxidative phosphorylation, tend to ferment glucose or other energy source into lactate even in the presence of sufficient oxygen, which is an inefficient way to generate ATP. This effect also occurs in striated muscle cells, activated lymphocytes and microglia, endothelial cells and several mammalian cell types, a phenomenon termed the “Warburg effect”. The effect is paradoxical at first glance because the ATP production rate of aerobic glycolysis is much slower than that of respiration and the energy demands are better to be met by pure oxidative phosphorylation. We tackle this question by building a minimal model including three combined reactions. The new aspect in extension to earlier models is that we take into account the possible uptake and oxidation of the fermentation products. We examine the case where the cell can allocate protein on several enzymes in a varying distribution and model this by a linear programming problem in which the objective is to maximize the ATP production rate under different combinations of constraints on enzymes. Depending on the cost of reactions and limitation of the substrates, this leads to pure respiration, pure fermentation, and a mixture of respiration and fermentation. The model predicts that fermentation products are only oxidized when glucose is scarce or its uptake is severely limited. PMID:29415045
Linear programming model can explain respiration of fermentation products.
Möller, Philip; Liu, Xiaochen; Schuster, Stefan; Boley, Daniel
2018-01-01
Many differentiated cells rely primarily on mitochondrial oxidative phosphorylation for generating energy in the form of ATP needed for cellular metabolism. In contrast most tumor cells instead rely on aerobic glycolysis leading to lactate to about the same extent as on respiration. Warburg found that cancer cells to support oxidative phosphorylation, tend to ferment glucose or other energy source into lactate even in the presence of sufficient oxygen, which is an inefficient way to generate ATP. This effect also occurs in striated muscle cells, activated lymphocytes and microglia, endothelial cells and several mammalian cell types, a phenomenon termed the "Warburg effect". The effect is paradoxical at first glance because the ATP production rate of aerobic glycolysis is much slower than that of respiration and the energy demands are better to be met by pure oxidative phosphorylation. We tackle this question by building a minimal model including three combined reactions. The new aspect in extension to earlier models is that we take into account the possible uptake and oxidation of the fermentation products. We examine the case where the cell can allocate protein on several enzymes in a varying distribution and model this by a linear programming problem in which the objective is to maximize the ATP production rate under different combinations of constraints on enzymes. Depending on the cost of reactions and limitation of the substrates, this leads to pure respiration, pure fermentation, and a mixture of respiration and fermentation. The model predicts that fermentation products are only oxidized when glucose is scarce or its uptake is severely limited.
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)
Linear algebraic approach to electron-molecule collisions
International Nuclear Information System (INIS)
Schneider, B.I.; Collins, L.A.
1983-01-01
The various levels of sophistication of the linear algebraic method are discussed and its application to electron-molecule collisions of H 2 , N 2 LiH, LiF and HCl is described. 13 references, 2 tables
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.
Fleming, P.
1983-01-01
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 nonlinear 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. One concerns helicopter longitudinal dynamics and the other the flight dynamics of an aerodynamically unstable aircraft.
A Unified Approach to Modeling and Programming
DEFF Research Database (Denmark)
Madsen, Ole Lehrmann; Møller-Pedersen, Birger
2010-01-01
of this paper is to go back to the future and get inspiration from SIMULA and propose a unied approach. In addition to reintroducing the contributions of SIMULA and the Scandinavian approach to object-oriented programming, we do this by discussing a number of issues in modeling and programming and argue3 why we......SIMULA was a language for modeling and programming and provided a unied approach to modeling and programming in contrast to methodologies based on structured analysis and design. The current development seems to be going in the direction of separation of modeling and programming. The goal...
Optimal placement of capacitors in a radial network using conic and mixed integer linear programming
Energy Technology Data Exchange (ETDEWEB)
Jabr, R.A. [Electrical, Computer and Communication Engineering Department, Notre Dame University, P.O. Box: 72, Zouk Mikhael, Zouk Mosbeh (Lebanon)
2008-06-15
This paper considers the problem of optimally placing fixed and switched type capacitors in a radial distribution network. The aim of this problem is to minimize the costs associated with capacitor banks, peak power, and energy losses whilst satisfying a pre-specified set of physical and technical constraints. The proposed solution is obtained using a two-phase approach. In phase-I, the problem is formulated as a conic program in which all nodes are candidates for placement of capacitor banks whose sizes are considered as continuous variables. A global solution of the phase-I problem is obtained using an interior-point based conic programming solver. Phase-II seeks a practical optimal solution by considering capacitor sizes as discrete variables. The problem in this phase is formulated as a mixed integer linear program based on minimizing the L1-norm of deviations from the phase-I state variable values. The solution to the phase-II problem is obtained using a mixed integer linear programming solver. The proposed method is validated via extensive comparisons with previously published results. (author)
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.
Energy Technology Data Exchange (ETDEWEB)
Zambon, Katia Livia
1997-07-01
A new approach for the Scheduling of Hydrothermal Systems, with a formulation that allows the solution of the problem through the linear programming techniques, otherwise the original form, which is complex and difficult is presented. The models were developed through a linear form for the generation function of hydroelectric plants, successive of the linearization of the cost function of the problem. The linear techniques used were the Simplex Method, with some modification that is is efficient, fast and simple. The important physical aspects of the system were preserved, like the individual representation of the hydroelectric plant, the features of cost function with the exponential increase and the head effect. Besides, this formulation can lead to stochastic approaches. All the optimization methods were implemented for the solution of the problem. The performance obtained were compared with each other and with that obtained through the non linear techniques. The algorithms showed to be efficient, with good results and very near to the optimal behavior of the reservoir operation planning obtained by traditional methods. (author)
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...
Partially Flipped Linear Algebra: A Team-Based Approach
Carney, Debra; Ormes, Nicholas; Swanson, Rebecca
2015-01-01
In this article we describe a partially flipped Introductory Linear Algebra course developed by three faculty members at two different universities. We give motivation for our partially flipped design and describe our implementation in detail. Two main features of our course design are team-developed preview videos and related in-class activities.…
New approach to solve symmetric fully fuzzy linear systems
Indian Academy of Sciences (India)
In this paper, we present a method to solve fully fuzzy linear systems with symmetric coefﬁcient matrix. The symmetric coefﬁcient matrix is decomposed into two systems of equations by using Cholesky method and then a solution can be obtained. Numerical examples are given to illustrate our method.
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.
A modified linear algebraic approach to electron scattering using cubic splines
International Nuclear Information System (INIS)
Kinney, R.A.
1986-01-01
A modified linear algebraic approach to the solution of the Schrodiner equation for low-energy electron scattering is presented. The method uses a piecewise cubic-spline approximation of the wavefunction. Results in the static-potential and the static-exchange approximations for e - +H s-wave scattering are compared with unmodified linear algebraic and variational linear algebraic methods. (author)
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.
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)
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.
DEFF Research Database (Denmark)
Ren, Jingzheng; Dong, Liang; Sun, Lu
2015-01-01
in this model, and the price of the resources, the yield of grain and the market demands were regarded as interval numbers instead of constants. An interval linear programming was developed, and a method for solving interval linear programming was presented. An illustrative case was studied by the proposed...
International Nuclear Information System (INIS)
Cullen, D.E.
1979-01-01
Program LINEAR converts evaluated cross sections in the ENDF/B format into a tabular form that is subject to linear-linear interpolation in energy and cross section. The code also thins tables of cross sections already in that form (i.e., removes points not needed for linear interpolability). The main advantage of the code is that it allows subsequent codes to consider only linear-linear data. A listing of the source deck is available on request
Effective radiological safety program for electron linear accelerators
International Nuclear Information System (INIS)
Swanson, W.P.
1980-10-01
An outline is presented of some of the main elements of an electron accelerator radiological safety program. The discussion includes types of accelerator facilities, types of radiations to be anticipated, activity induced in components, air and water, and production of toxic gases. Concepts of radiation shielding design are briefly discussed and organizational aspects are considered as an integral part of the overall safety program
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.
Leibov Roman
2017-01-01
This paper presents a bilinear approach to nonlinear differential equations system approximation problem. Sometimes the nonlinear differential equations right-hand sides linearization is extremely difficult or even impossible. Then piecewise-linear approximation of nonlinear differential equations can be used. The bilinear differential equations allow to improve piecewise-linear differential equations behavior and reduce errors on the border of different linear differential equations systems ...
Algorithmic Approach to Abstracting Linear Systems by Timed Automata
DEFF Research Database (Denmark)
Sloth, Christoffer; Wisniewski, Rafael
2011-01-01
This paper proposes an LMI-based algorithm for abstracting dynamical systems by timed automata, which enables automatic formal verification of linear systems. The proposed abstraction is based on partitioning the state space of the system using positive invariant sets, generated by Lyapunov...... functions. This partitioning ensures that the vector field of the dynamical system is transversal to all facets of the cells, which induces some desirable properties of the abstraction. The algorithm is based on identifying intersections of level sets of quadratic Lyapunov functions, and determining...
Zhao, Yingfeng; Liu, Sanyang
2016-01-01
We present a practical branch and bound algorithm for globally solving generalized linear multiplicative programming problem with multiplicative constraints. To solve the problem, a relaxation programming problem which is equivalent to a linear programming is proposed by utilizing a new two-phase relaxation technique. In the algorithm, lower and upper bounds are simultaneously obtained by solving some linear relaxation programming problems. Global convergence has been proved and results of some sample examples and a small random experiment show that the proposed algorithm is feasible and efficient.
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
Mixed-Integer Conic Linear Programming: Challenges and Perspectives
2013-10-01
The novel DCCs for MISOCO may be used in branch- and-cut algorithms when solving MISOCO problems. The experimental software CICLO was developed to...perform limited, but rigorous computational experiments. The CICLO solver utilizes continuous SOCO solvers, MOSEK, CPLES or SeDuMi, builds on the open...submitted Fall 2013. Software: 1. CICLO : Integer conic linear optimization package. Authors: J.C. Góez, T.K. Ralphs, Y. Fu, and T. Terlaky
International Nuclear Information System (INIS)
Zavaljevski, N.
1985-01-01
Proposed optimization procedure is fast due to application of linear programming. Non-linear constraints which demand iterative application of linear programming are slowing down the calculation. Linearization can be done by different procedures starting from simple empirical rules for fuel in-core management to complicated general perturbation theory with higher order of corrections. A mathematical model was formulated for optimization of improved fuel cycle. A detailed algorithm for determining minimum of fresh fuel at the beginning of each fuel cycle is shown and the problem is linearized by first order perturbation theory and it is optimized by linear programming. Numerical illustration of the proposed method was done for the experimental reactor mostly for saving computer time
Design and analysis approach for linear aerospike nozzle
International Nuclear Information System (INIS)
Khan, S.U.; Khan, A.A.; Munir, A.
2014-01-01
The paper presents an aerodynamic design of a simplified linear aerospike nozzle and its detailed exhaust flow analysis with no spike truncation. Analytical method with isentropic planar flow was used to generate the nozzle contour through MATLAB . The developed code produces a number of outputs comprising nozzle wall profile, flow properties along the nozzle wall, thrust coefficient, thrust, as well as amount of nozzle truncation. Results acquired from design code and numerical analyses are compared for observing differences. The numerical analysis adopted an inviscid model carried out through commercially available and reliable computational fluid dynamics (CFD) software. Use of the developed code would assist the readers to perform quick analysis of different aerodynamic design parameters for the aerospike nozzle that has tremendous scope of application in future launch vehicles. Keyword: Rocket propulsion, Aerospike Nozzle, Control Design, Computational Fluid Dynamics. (author)
Linear Motion Systems. A Modular Approach for Improved Straightness Performance
Nijsse, G.J.P.
2001-01-01
This thesis deals with straight motion systems. A modular approach has been applied in order to find ways to improve the performance. The main performance parameters that are considered are position accuracy, repeatability and, to a lesser extent, cost. Because of the increasing requirements to
International Nuclear Information System (INIS)
Shaban Boloukat, Mohammad Hadi; Akbari Foroud, Asghar
2016-01-01
This paper represents a stochastic approach for long-term optimal resource expansion planning of a grid-connected microgrid (MG) containing different technologies as intermittent renewable energy resources, energy storage systems and thermal resources. Maximizing profit and reliability, along with minimizing investment and operation costs, are major objectives which have been considered in this model. Also, the impacts of intermittency and uncertainty in renewable energy resources were investigated. The interval linear programming (ILP) was applied for modelling inherent stochastic nature of the renewable energy resources. ILP presents some superiority in modelling of uncertainties in MG planning. The problem was formulated as a mixed-integer linear programming. It has been demonstrated previously that the benders decomposition (BD) served as an effective tool for solving such problems. BD divides the original problem into a master (investment) problem and operation and reliability subproblems. In this paper a multiperiod MG planning is presented, considering life time, maximum penetration limit of each technology, interest rate, capital recovery factor and investment fund. Real-time energy exchange with the utility is covered, with a consideration of variable tariffs at different load blocks. The presented approach can help MG planners to adopt best decision under various uncertainty levels based on their budgetary policies. - Highlights: • Considering uncertain nature of the renewable resources with applying ILP. • Considering the effect of intermittency of renewable in MG planning. • Multiobjective MG planning problem which covers cost, profit and reliability. • Multiperiod approach for MG planning considering life time and MPL of technologies. • Presenting real-time energy exchange with the utility considering variable tariffs.
A new linear induction voltage adder approach to radiography
International Nuclear Information System (INIS)
Mazarakis, M.G.; Poukey, J.W.; Frost, C.A.; Johnson, D.L.; Shope, S.L.; Halbleib, J.A.; Prestwich, K.R.; Turman, B.N.; Smith, I.
1992-01-01
At present, two types of accelerators are being utilized for x-ray radiography: first a linear RF or induction accelerator with multiple accelerating gaps and beam vacuum magnetic transport systems; and second, single gap pulse-power devices with a high voltage Blumlein pulse forming line. The authors present a conceptual design of a new type of linear induction accelerator that can bridge the gap between the two devices. It can produce 30--50-kA electron currents small diameter (∼ 1 mm) and high energy (12--20-MV) beams. There is no beam drifting through the device. The voltage addition of the accelerating gaps occurs at the central self-magnetically insulated cathode electrode. The electron beam is created at the high voltage end in a single gap diode. A magnetically-immersed foilless diode can produce high quality 0.5 mm radius 30--50 kA beams. A short 100--200-kG small bore solenoidal coil is required to maintain the beam radius during transport from the cathode tips to the x-ray converter target, 50--70 cm downstream. The idea of very high impedance MITL voltage adder accelerators was first tested with RADLAC II/SMILE experiments where 12--14-MV, 50-kA 1 cm radius beams were produced with 2--3 mm annulus thickness. A 12.5 m eight-stage voltage adder was utilized, coupled to a 20 kG magnetically immersed foilless diode. In addition the magnetically-immersed foilless diodes with very thin (mm diameter) cathode tips were investigated in experiments with the IBEX accelerator. As an example of this new accelerator technology the authors present the following point design for a 16-MV, 50-kA accelerator producing 1-mm diameter electron beams. The design is based on a cavity fed MITL voltage adder which performs the series addition of the voltage pulses from 16 identical inductively-isolated cavity feed systems. Each cavity is a structure that is driven by one 14 ohm pulse-forming line, providing a 1 MV voltage pulse to the accelerating gap
A fixed recourse integer programming approach towards a ...
African Journals Online (AJOL)
Regardless of the success that linear programming and integer linear programming has had in applications in engineering, business and economics, one has to challenge the assumed reality that these optimization models represent. In this paper the certainty assumptions of an integer linear program application is ...
International Nuclear Information System (INIS)
Hutchinson, W.
1983-04-01
The report takes the form of a user guide to a computer program using linear programming techniques to aid the assignment and scheduling of radioactive wastes for disposal to sea. The program is aimed at the identification of 'optimum' amounts of each waste stream for disposal to sea without violating specific constraints values and/or fairness parameters. (author)
Fitting boxes to Manhattan scenes using linear integer programming
Li, Minglei; Nan, Liangliang; Liu, Shaochuang
2016-01-01
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
Comparing approaches to generic programming in Haskell
Hinze, R.; Jeuring, J.T.; Löh, A.
2006-01-01
The last decade has seen a number of approaches to generic programming: PolyP, Functorial ML, `Scrap Your Boilerplate', Generic Haskell, `Generics for the Masses', etc. The approaches vary in sophistication and target audience: some propose full-blown pro- gramming languages, some suggest
Comparing approaches to generic programming in Haskell
Hinze, R.; Jeuring, J.T.; Löh, A.
2006-01-01
The last decade has seen a number of approaches to data- type-generic programming: PolyP, Functorial ML, `Scrap Your Boiler- plate', Generic Haskell, `Generics for the Masses', etc. The approaches vary in sophistication and target audience: some propose full-blown pro- gramming languages, some
Directory of Open Access Journals (Sweden)
Aihong Ren
2016-01-01
Full Text Available This paper is concerned with a class of fully fuzzy bilevel linear programming problems where all the coefficients and decision variables of both objective functions and the constraints are fuzzy numbers. A new approach based on deviation degree measures and a ranking function method is proposed to solve these problems. We first introduce concepts of the feasible region and the fuzzy optimal solution of a fully fuzzy bilevel linear programming problem. In order to obtain a fuzzy optimal solution of the problem, we apply deviation degree measures to deal with the fuzzy constraints and use a ranking function method of fuzzy numbers to rank the upper and lower level fuzzy objective functions. Then the fully fuzzy bilevel linear programming problem can be transformed into a deterministic bilevel programming problem. Considering the overall balance between improving objective function values and decreasing allowed deviation degrees, the computational procedure for finding a fuzzy optimal solution is proposed. Finally, a numerical example is provided to illustrate the proposed approach. The results indicate that the proposed approach gives a better optimal solution in comparison with the existing method.
A reliability program approach to operational safety
International Nuclear Information System (INIS)
Mueller, C.J.; Bezella, W.A.
1985-01-01
A Reliability Program (RP) model based on proven reliability techniques is being formulated for potential application in the nuclear power industry. Methods employed under NASA and military direction, commercial airline and related FAA programs were surveyed and a review of current nuclear risk-dominant issues conducted. The need for a reliability approach to address dependent system failures, operating and emergency procedures and human performance, and develop a plant-specific performance data base for safety decision making is demonstrated. Current research has concentrated on developing a Reliability Program approach for the operating phase of a nuclear plant's lifecycle. The approach incorporates performance monitoring and evaluation activities with dedicated tasks that integrate these activities with operation, surveillance, and maintenance of the plant. The detection, root-cause evaluation and before-the-fact correction of incipient or actual systems failures as a mechanism for maintaining plant safety is a major objective of the Reliability Program. (orig./HP)
A combined stochastic programming and optimal control approach to personal finance and pensions
DEFF Research Database (Denmark)
Konicz, Agnieszka Karolina; Pisinger, David; Rasmussen, Kourosh Marjani
2015-01-01
The paper presents a model that combines a dynamic programming (stochastic optimal control) approach and a multi-stage stochastic linear programming approach (SLP), integrated into one SLP formulation. Stochastic optimal control produces an optimal policy that is easy to understand and implement....
Liang, Bin; Li, Yongbao; Wei, Ran; Guo, Bin; Xu, Xuang; Liu, Bo; Li, Jiafeng; Wu, Qiuwen; Zhou, Fugen
2018-01-01
With robot-controlled linac positioning, robotic radiotherapy systems such as CyberKnife significantly increase freedom of radiation beam placement, but also impose more challenges on treatment plan optimization. The resampling mechanism in the vendor-supplied treatment planning system (MultiPlan) cannot fully explore the increased beam direction search space. Besides, a sparse treatment plan (using fewer beams) is desired to improve 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 tapers. The requirements on dosimetry distribution are modeled as hard and soft constraints, and the sparsity of the treatment plan is achieved by compressive sensing. The proposed linear programming (LP) model optimizes beam weights by minimizing the deviation of soft constraints subject to hard constraints, with a constraint on the l 1 norm of the beam weight. A singular value decomposition (SVD) based acceleration technique was developed for the LP model. Based on the degeneracy of the 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 weights of the 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. Furthermore, the beam reduction achieves a similar plan quality to the globally optimal plan obtained by the MIP model, but is one to two orders of magnitude faster. Furthermore, the SVDLP
Liang, Bin; Li, Yongbao; Wei, Ran; Guo, Bin; Xu, Xuang; Liu, Bo; Li, Jiafeng; Wu, Qiuwen; Zhou, Fugen
2018-01-05
With robot-controlled linac positioning, robotic radiotherapy systems such as CyberKnife significantly increase freedom of radiation beam placement, but also impose more challenges on treatment plan optimization. The resampling mechanism in the vendor-supplied treatment planning system (MultiPlan) cannot fully explore the increased beam direction search space. Besides, a sparse treatment plan (using fewer beams) is desired to improve 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 tapers. The requirements on dosimetry distribution are modeled as hard and soft constraints, and the sparsity of the treatment plan is achieved by compressive sensing. The proposed linear programming (LP) model optimizes beam weights by minimizing the deviation of soft constraints subject to hard constraints, with a constraint on the l 1 norm of the beam weight. A singular value decomposition (SVD) based acceleration technique was developed for the LP model. Based on the degeneracy of the 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 weights of the 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. Furthermore, the beam reduction achieves a similar plan quality to the globally optimal plan obtained by the MIP model, but is one to two orders of magnitude faster. Furthermore, the SVDLP
Linear-programming approach to nonconvex variational problems
Czech Academy of Sciences Publication Activity Database
Bartels, S.; Roubíček, Tomáš
2004-01-01
Roč. 99, č. 2 (2004), s. 251-287 ISSN 0029-599X R&D Projects: GA AV ČR IAA1075005 Institutional research plan: CEZ:AV0Z1075907 Keywords : young measures * convex approximations * adaptive scheme Subject RIV: BA - General Mathematics Impact factor: 1.011, year: 2004
PAPR reduction in FBMC using an ACE-based linear programming optimization
van der Neut, Nuan; Maharaj, Bodhaswar TJ; de Lange, Frederick; González, Gustavo J.; Gregorio, Fernando; Cousseau, Juan
2014-12-01
This paper presents four novel techniques for peak-to-average power ratio (PAPR) reduction in filter bank multicarrier (FBMC) modulation systems. The approach extends on current PAPR reduction active constellation extension (ACE) methods, as used in orthogonal frequency division multiplexing (OFDM), to an FBMC implementation as the main contribution. The four techniques introduced can be split up into two: linear programming optimization ACE-based techniques and smart gradient-project (SGP) ACE techniques. The linear programming (LP)-based techniques compensate for the symbol overlaps by utilizing a frame-based approach and provide a theoretical upper bound on achievable performance for the overlapping ACE techniques. The overlapping ACE techniques on the other hand can handle symbol by symbol processing. Furthermore, as a result of FBMC properties, the proposed techniques do not require side information transmission. The PAPR performance of the techniques is shown to match, or in some cases improve, on current PAPR techniques for FBMC. Initial analysis of the computational complexity of the SGP techniques indicates that the complexity issues with PAPR reduction in FBMC implementations can be addressed. The out-of-band interference introduced by the techniques is investigated. As a result, it is shown that the interference can be compensated for, whilst still maintaining decent PAPR performance. Additional results are also provided by means of a study of the PAPR reduction of the proposed techniques at a fixed clipping probability. The bit error rate (BER) degradation is investigated to ensure that the trade-off in terms of BER degradation is not too severe. As illustrated by exhaustive simulations, the SGP ACE-based technique proposed are ideal candidates for practical implementation in systems employing the low-complexity polyphase implementation of FBMC modulators. The methods are shown to offer significant PAPR reduction and increase the feasibility of FBMC as
adapta~k>n -11 of the surrogate memods for linear programming ...
African Journals Online (AJOL)
2005-08-02
Aug 2, 2005 ... inequality problem is made uj~ of the primal and dual optimal solutions for the given primal ... KEYWORDS: Linear Programming, Duality Theory, Surrogate Methods. ..... replaces x and the process IS repeated with the new x.
Development of demand functions and their inclusion in linear programming forecasting models
International Nuclear Information System (INIS)
Chamberlin, J.H.
1976-05-01
The purpose of the paper is to present a method for including demand directly within a linear programming model, and to use this method to analyze the effect of the Liquid Metal Fast Breeder Reactor upon the nuclear energy system
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.
Fuzzy Multi Objective Linear Programming Problem with Imprecise Aspiration Level and Parameters
Directory of Open Access Journals (Sweden)
Zahra Shahraki
2015-07-01
Full Text Available This paper considers the multi-objective linear programming problems with fuzzygoal for each of the objective functions and constraints. Most existing works deal withlinear membership functions for fuzzy goals. In this paper, exponential membershipfunction is used.
International Nuclear Information System (INIS)
Ureba, A.; Palma, B. A.; Leal, A.
2011-01-01
Develop a more efficient method of optimization in relation to time, based on linear programming designed to implement a multi objective penalty function which also permits a simultaneous solution integrated boost situations considering two white volumes simultaneously.
SPICE SDM: Innovative Approaches for Linear Motion and Heat Management
Relecom, Ken; Larcheveque, Cyril; Constant, Joël; Autissier, Nordahl; Pornin, Arnaud; Martini, Nicolas
2015-09-01
The SPICE Door Mechanism (SDM) is foreseen to be flown on Solar Orbiter, to close the SPICE instrument aperture and shield it from the solar flux and from contamination. The environment it is exposed to is particularly extreme, as the Solar Orbiter mission will reach a distance of 0.28 AU (41’887’403.8 km) to the Sun, and the SPICE instrument will be looking directly at it. Because of its position at the far end of a cantilevered structure, the SDM is also exposed to amplified launch loads and must remain very light and compact. The cleanliness constraints are also very tight, as the mechanism is positioned directly at the aperture of the SPICE spectrometer.To tackle these issues, two novelties were introduced on the SPICE Door Mechanism:- A specifically engineered reflective coating toprotect the Aluminium door from the heat generatedby the solar flux- The use of miniature profile rail type linearbearings to support the door during launch andallow its motion during the missionThis paper details the design and verification approach applied for these two innovations and for the mechanism as a whole, as well as the results and findings from the testing carried out on the Bread Board, Qualification and Flight models.
Portfolio selection problem: a comparison of fuzzy goal programming and linear physical programming
Directory of Open Access Journals (Sweden)
Fusun Kucukbay
2016-04-01
Full Text Available Investors have limited budget and they try to maximize their return with minimum risk. Therefore this study aims to deal with the portfolio selection problem. In the study two criteria are considered which are expected return, and risk. In this respect, linear physical programming (LPP technique is applied on Bist 100 stocks to be able to find out the optimum portfolio. The analysis covers the period April 2009- March 2015. This period is divided into two; April 2009-March 2014 and April 2014 – March 2015. April 2009-March 2014 period is used as data to find an optimal solution. April 2014-March 2015 period is used to test the real performance of portfolios. The performance of the obtained portfolio is compared with that obtained from fuzzy goal programming (FGP. Then the performances of both method, LPP and FGP are compared with BIST 100 in terms of their Sharpe Indexes. The findings reveal that LPP for portfolio selection problem is a good alternative to FGP.
Combinatorial therapy discovery using mixed integer linear programming.
Pang, Kaifang; Wan, Ying-Wooi; Choi, William T; Donehower, Lawrence A; Sun, Jingchun; Pant, Dhruv; Liu, Zhandong
2014-05-15
Combinatorial therapies play increasingly important roles in combating complex diseases. Owing to the huge cost associated with experimental methods in identifying optimal drug combinations, computational approaches can provide a guide to limit the search space and reduce cost. However, few computational approaches have been developed for this purpose, and thus there is a great need of new algorithms for drug combination prediction. Here we proposed to formulate the optimal combinatorial therapy problem into two complementary mathematical algorithms, Balanced Target Set Cover (BTSC) and Minimum Off-Target Set Cover (MOTSC). Given a disease gene set, BTSC seeks a balanced solution that maximizes the coverage on the disease genes and minimizes the off-target hits at the same time. MOTSC seeks a full coverage on the disease gene set while minimizing the off-target set. Through simulation, both BTSC and MOTSC demonstrated a much faster running time over exhaustive search with the same accuracy. When applied to real disease gene sets, our algorithms not only identified known drug combinations, but also predicted novel drug combinations that are worth further testing. In addition, we developed a web-based tool to allow users to iteratively search for optimal drug combinations given a user-defined gene set. Our tool is freely available for noncommercial use at http://www.drug.liuzlab.org/. zhandong.liu@bcm.edu Supplementary data are available at Bioinformatics online.
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...
Identifying predictors of physics item difficulty: A linear regression approach
Mesic, Vanes; Muratovic, Hasnija
2011-06-01
Large-scale assessments of student achievement in physics are often approached with an intention to discriminate students based on the attained level of their physics competencies. Therefore, for purposes of test design, it is important that items display an acceptable discriminatory behavior. To that end, it is recommended to avoid extraordinary difficult and very easy items. Knowing the factors that influence physics item difficulty makes it possible to model the item difficulty even before the first pilot study is conducted. Thus, by identifying predictors of physics item difficulty, we can improve the test-design process. Furthermore, we get additional qualitative feedback regarding the basic aspects of student cognitive achievement in physics that are directly responsible for the obtained, quantitative test results. In this study, we conducted a secondary analysis of data that came from two large-scale assessments of student physics achievement at the end of compulsory education in Bosnia and Herzegovina. Foremost, we explored the concept of “physics competence” and performed a content analysis of 123 physics items that were included within the above-mentioned assessments. Thereafter, an item database was created. Items were described by variables which reflect some basic cognitive aspects of physics competence. For each of the assessments, Rasch item difficulties were calculated in separate analyses. In order to make the item difficulties from different assessments comparable, a virtual test equating procedure had to be implemented. Finally, a regression model of physics item difficulty was created. It has been shown that 61.2% of item difficulty variance can be explained by factors which reflect the automaticity, complexity, and modality of the knowledge structure that is relevant for generating the most probable correct solution, as well as by the divergence of required thinking and interference effects between intuitive and formal physics knowledge
Identifying predictors of physics item difficulty: A linear regression approach
Directory of Open Access Journals (Sweden)
Hasnija Muratovic
2011-06-01
Full Text Available Large-scale assessments of student achievement in physics are often approached with an intention to discriminate students based on the attained level of their physics competencies. Therefore, for purposes of test design, it is important that items display an acceptable discriminatory behavior. To that end, it is recommended to avoid extraordinary difficult and very easy items. Knowing the factors that influence physics item difficulty makes it possible to model the item difficulty even before the first pilot study is conducted. Thus, by identifying predictors of physics item difficulty, we can improve the test-design process. Furthermore, we get additional qualitative feedback regarding the basic aspects of student cognitive achievement in physics that are directly responsible for the obtained, quantitative test results. In this study, we conducted a secondary analysis of data that came from two large-scale assessments of student physics achievement at the end of compulsory education in Bosnia and Herzegovina. Foremost, we explored the concept of “physics competence” and performed a content analysis of 123 physics items that were included within the above-mentioned assessments. Thereafter, an item database was created. Items were described by variables which reflect some basic cognitive aspects of physics competence. For each of the assessments, Rasch item difficulties were calculated in separate analyses. In order to make the item difficulties from different assessments comparable, a virtual test equating procedure had to be implemented. Finally, a regression model of physics item difficulty was created. It has been shown that 61.2% of item difficulty variance can be explained by factors which reflect the automaticity, complexity, and modality of the knowledge structure that is relevant for generating the most probable correct solution, as well as by the divergence of required thinking and interference effects between intuitive and formal
Stochastic Modelling of Linear Programming Application to Brewing Operational Systems
Directory of Open Access Journals (Sweden)
Akanbi O.P.
2014-07-01
Full Text Available System where a large number of interrelated operations exist, technically-based operational mechanism is always required to achieve potential. An intuitive solution, which is common practice in most of the breweries, perhaps may not uncover the optimal solution, as there is hardly any guarantee to satisfy the best policy application. There is always high foreign exchange involved in procurement of imported raw materials and thus increases the cost of production, abandonment and poor utilization of available locally-sourced raw materials. This study focuses on the approaches which highlight the steps and mechanisms involved in optimizing the wort extract by the use of different types of adjuncts and formulating wort production models which are useful in proffering expected solutions. Optimization techniques, the generalized models and an overview of typical brewing processes were considered.
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.
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.
Stochastic Control of Energy Efficient Buildings: A Semidefinite Programming Approach
Energy Technology Data Exchange (ETDEWEB)
Ma, Xiao [ORNL; Dong, Jin [ORNL; Djouadi, Seddik M [ORNL; Nutaro, James J [ORNL; Kuruganti, Teja [ORNL
2015-01-01
The key goal in energy efficient buildings is to reduce energy consumption of Heating, Ventilation, and Air- Conditioning (HVAC) systems while maintaining a comfortable temperature and humidity in the building. This paper proposes a novel stochastic control approach for achieving joint performance and power control of HVAC. We employ a constrained Stochastic Linear Quadratic Control (cSLQC) by minimizing a quadratic cost function with a disturbance assumed to be Gaussian. The problem is formulated to minimize the expected cost subject to a linear constraint and a probabilistic constraint. By using cSLQC, the problem is reduced to a semidefinite optimization problem, where the optimal control can be computed efficiently by Semidefinite programming (SDP). Simulation results are provided to demonstrate the effectiveness and power efficiency by utilizing the proposed control approach.
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.
Decision-making methodology of optimal shielding materials by using fuzzy linear programming
International Nuclear Information System (INIS)
Kanai, Y.; Miura, T.; Hirao, Y.
2000-01-01
The main purpose of our studies are to select materials and determine the ratio of constituent materials as the first stage of optimum shielding design to suit the individual requirements of nuclear reactors, reprocessing facilities, casks for shipping spent fuel, etc. The parameters of the shield optimization are cost, space, weight and some shielding properties such as activation rates or individual irradiation and cooling time, and total dose rate for neutrons (including secondary gamma ray) and for primary gamma ray. Using conventional two-valued logic (i.e. crisp) approaches, huge combination calculations are needed to identify suitable materials for optimum shielding design. Also, re-computation is required for minor changes, as the approach does not react sensitively to the computation result. Present approach using a fuzzy linear programming method is much of the decision-making toward the satisfying solution might take place in fuzzy environment. And it can quickly and easily provide a guiding principle of optimal selection of shielding materials under the above-mentioned conditions. The possibility or reducing radiation effects by optimizing the ratio of constituent materials is investigated. (author)
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.
Improved harmonic balance approach to periodic solutions of non-linear jerk equations
International Nuclear Information System (INIS)
Wu, B.S.; Lim, C.W.; Sun, W.P.
2006-01-01
An analytical approximate approach for determining periodic solutions of non-linear jerk equations involving third-order time-derivative is presented. This approach incorporates salient features of both Newton's method and the method of harmonic balance. By appropriately imposing the method of harmonic balance to the linearized equation, the approach requires only one or two iterations to predict very accurate analytical approximate solutions for a large range of initial velocity amplitude. One typical example is used to verify and illustrate the usefulness and effectiveness of the proposed approach
Study and program implementation of transient curves' piecewise linearization
International Nuclear Information System (INIS)
Shi Yang; Zu Hongbiao
2014-01-01
Background: Transient curves are essential for the stress analysis of related equipment in nuclear power plant (NPP). The actually operating data or the design transient data of a NPP usually consist of a large number of data points with very short time intervals. To simplify the analysis, transient curves are generally piecewise linearized in advance. Up to now, the piecewise linearization of transient curves is accomplished manually, Purpose: The aim is to develop a method for the piecewise linearization of transient curves, and to implement it by programming. Methods: First of all, the fitting line of a number of data points was obtained by the least square method. The segment of the fitting line is set while the accumulation error of linearization exceeds the preset limit with the increasing number of points. Then the linearization of subsequent data points was begun from the last point of the preceding curve segment to get the next segment in the same way, and continue until the final data point involved. Finally, averaging of junction points is taken for the segment connection. Results: A computer program named PLTC (Piecewise Linearization for Transient Curves) was implemented and verified by the linearization of the standard sine curve and typical transient curves of a NPP. Conclusion: The method and the PLTC program can be well used to the piecewise linearization of transient curves, with improving efficiency and precision. (authors)
The Computer Program LIAR for Beam Dynamics Calculations in Linear Accelerators
International Nuclear Information System (INIS)
Assmann, R.W.; Adolphsen, C.; Bane, K.; Raubenheimer, T.O.; Siemann, R.H.; Thompson, K.
2011-01-01
Linear accelerators are the central components of the proposed next generation of linear colliders. They need to provide acceleration of up to 750 GeV per beam while maintaining very small normalized emittances. Standard simulation programs, mainly developed for storage rings, do not meet the specific requirements for high energy linear accelerators. We present a new program LIAR ('LInear Accelerator Research code') that includes wakefield effects, a 6D coupled beam description, specific optimization algorithms and other advanced features. Its modular structure allows to use and to extend it easily for different purposes. The program is available for UNIX workstations and Windows PC's. It can be applied to a broad range of accelerators. We present examples of simulations for SLC and NLC.
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.
Directory of Open Access Journals (Sweden)
Orhan Dengiz
2018-01-01
Full Text Available Land evaluation analysis is a prerequisite to achieving optimum utilization of the available land resources. Lack of knowledge on best combination of factors that suit production of yields has contributed to the low production. The aim of this study was to determine the most suitable areas for agricultural uses. For that reasons, in order to determine land suitability classes of the study area, multi-criteria approach was used with linear combination technique and analytical hierarchy process by taking into consideration of some land and soil physico-chemical characteristic such as slope, texture, depth, derange, stoniness, erosion, pH, EC, CaCO3 and organic matter. These data and land mapping unites were taken from digital detailed soil map scaled as 1:5.000. In addition, in order to was produce land suitability map GIS was program used for the study area. This study was carried out at Mahmudiye, Karaamca, Yazılı, Çiçeközü, Orhaniye and Akbıyık villages in Yenişehir district of Bursa province. Total study area is 7059 ha. 6890 ha of total study area has been used as irrigated agriculture, dry farming agriculture, pasture while, 169 ha has been used for non-agricultural activities such as settlement, road water body etc. Average annual temperature and precipitation of the study area are 16.1oC and 1039.5 mm, respectively. Finally after determination of land suitability distribution classes for the study area, it was found that 15.0% of the study area has highly (S1 and moderately (S2 while, 85% of the study area has marginally suitable and unsuitable coded as S3 and N. It was also determined some relation as compared results of linear combination technique with other hierarchy approaches such as Land Use Capability Classification and Suitability Class for Agricultural Use methods.
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...
A linear programming algorithm to test for jamming in hard-sphere packings
International Nuclear Information System (INIS)
Donev, Aleksandar; Torquato, Salvatore.; Stillinger, Frank H.; Connelly, Robert
2004-01-01
Jamming in hard-particle packings has been the subject of considerable interest in recent years. In a paper by Torquato and Stillinger [J. Phys. Chem. B 105 (2001)], a classification scheme of jammed packings into hierarchical categories of locally, collectively and strictly jammed configurations has been proposed. They suggest that these jamming categories can be tested using numerical algorithms that analyze an equivalent contact network of the packing under applied displacements, but leave the design of such algorithms as a future task. In this work, we present a rigorous and practical algorithm to assess whether an ideal hard-sphere packing in two or three dimensions is jammed according to the aforementioned categories. The algorithm is based on linear programming and is applicable to regular as well as random packings of finite size with hard-wall and periodic boundary conditions. If the packing is not jammed, the algorithm yields representative multi-particle unjamming motions. Furthermore, we extend the jamming categories and the testing algorithm to packings with significant interparticle gaps. We describe in detail two variants of the proposed randomized linear programming approach to test for jamming in hard-sphere packings. The first algorithm treats ideal packings in which particles form perfect contacts. Another algorithm treats the case of jamming in packings with significant interparticle gaps. This extended algorithm allows one to explore more fully the nature of the feasible particle displacements. We have implemented the algorithms and applied them to ordered as well as random packings of circular disks and spheres with periodic boundary conditions. Some representative results for large disordered disk and sphere packings are given, but more robust and efficient implementations as well as further applications (e.g., non-spherical particles) are anticipated for the future
International program on linear electric motors. CIGGT report No. 92-1
Energy Technology Data Exchange (ETDEWEB)
Dawson, G.E.; Eastham, A.R.; Parker, J.H.
1992-12-31
The International Program for Linear Electric Motors (LEM) was begun in April 1989 to communicate and coordinate activities with centers of expertise in Germany, Canada, and Japan; to provide for the assessment and support of the planning of technological developments and for dissemination of information to researchers, service operators, and policy makers; and to ensure that full advantage can be taken if opportunities for technology transfer occur. This report documents the work done under the program, including standardizing linear induction motor (LIM) design characteristics; test procedures and measurement methods; rating; database for design data; criteria for evaluation of designs; computer programs for modelling performance; and a design study for an agreed application.
Developmental Programming of Renal Function and Re-Programming Approaches.
Nüsken, Eva; Dötsch, Jörg; Weber, Lutz T; Nüsken, Kai-Dietrich
2018-01-01
Chronic kidney disease affects more than 10% of the population. Programming studies have examined the interrelationship between environmental factors in early life and differences in morbidity and mortality between individuals. A number of important principles has been identified, namely permanent structural modifications of organs and cells, long-lasting adjustments of endocrine regulatory circuits, as well as altered gene transcription. Risk factors include intrauterine deficiencies by disturbed placental function or maternal malnutrition, prematurity, intrauterine and postnatal stress, intrauterine and postnatal overnutrition, as well as dietary dysbalances in postnatal life. This mini-review discusses critical developmental periods and long-term sequelae of renal programming in humans and presents studies examining the underlying mechanisms as well as interventional approaches to "re-program" renal susceptibility toward disease. Clinical manifestations of programmed kidney disease include arterial hypertension, proteinuria, aggravation of inflammatory glomerular disease, and loss of kidney function. Nephron number, regulation of the renin-angiotensin-aldosterone system, renal sodium transport, vasomotor and endothelial function, myogenic response, and tubuloglomerular feedback have been identified as being vulnerable to environmental factors. Oxidative stress levels, metabolic pathways, including insulin, leptin, steroids, and arachidonic acid, DNA methylation, and histone configuration may be significantly altered by adverse environmental conditions. Studies on re-programming interventions focused on dietary or anti-oxidative approaches so far. Further studies that broaden our understanding of renal programming mechanisms are needed to ultimately develop preventive strategies. Targeted re-programming interventions in animal models focusing on known mechanisms will contribute to new concepts which finally will have to be translated to human application. Early
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)
M.S. Osman
2018-03-01
Full Text Available In this paper, an interactive approach for solving multi-level multi-objective fractional programming (ML-MOFP problems with fuzzy parameters is presented. The proposed interactive approach makes an extended work of Shi and Xia (1997. In the first phase, the numerical crisp model of the ML-MOFP problem has been developed at a confidence level without changing the fuzzy gist of the problem. Then, the linear model for the ML-MOFP problem is formulated. In the second phase, the interactive approach simplifies the linear multi-level multi-objective model by converting it into separate multi-objective programming problems. Also, each separate multi-objective programming problem of the linear model is solved by the ∊-constraint method and the concept of satisfactoriness. Finally, illustrative examples and comparisons with the previous approaches are utilized to evince the feasibility of the proposed approach.
Development and adjustment of programs for solving systems of linear equations
International Nuclear Information System (INIS)
Fujimura, Toichiro
1978-03-01
Programs for solving the systems of linear equations have been adjusted and developed in expanding the scientific subroutine library SSL. The principal programs adjusted are based on the congruent method, method of product form of the inverse, orthogonal method, Crout's method for sparse system, and acceleration of iterative methods. The programs developed are based on the escalator method, direct parallel residue method and block tridiagonal method for band system. Described are usage of the programs developed and their future improvement. FORTRAN lists with simple examples in tests of the programs are also given. (auth.)
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.
Developmental Programming of Renal Function and Re-Programming Approaches
Directory of Open Access Journals (Sweden)
Eva Nüsken
2018-02-01
Full Text Available Chronic kidney disease affects more than 10% of the population. Programming studies have examined the interrelationship between environmental factors in early life and differences in morbidity and mortality between individuals. A number of important principles has been identified, namely permanent structural modifications of organs and cells, long-lasting adjustments of endocrine regulatory circuits, as well as altered gene transcription. Risk factors include intrauterine deficiencies by disturbed placental function or maternal malnutrition, prematurity, intrauterine and postnatal stress, intrauterine and postnatal overnutrition, as well as dietary dysbalances in postnatal life. This mini-review discusses critical developmental periods and long-term sequelae of renal programming in humans and presents studies examining the underlying mechanisms as well as interventional approaches to “re-program” renal susceptibility toward disease. Clinical manifestations of programmed kidney disease include arterial hypertension, proteinuria, aggravation of inflammatory glomerular disease, and loss of kidney function. Nephron number, regulation of the renin–angiotensin–aldosterone system, renal sodium transport, vasomotor and endothelial function, myogenic response, and tubuloglomerular feedback have been identified as being vulnerable to environmental factors. Oxidative stress levels, metabolic pathways, including insulin, leptin, steroids, and arachidonic acid, DNA methylation, and histone configuration may be significantly altered by adverse environmental conditions. Studies on re-programming interventions focused on dietary or anti-oxidative approaches so far. Further studies that broaden our understanding of renal programming mechanisms are needed to ultimately develop preventive strategies. Targeted re-programming interventions in animal models focusing on known mechanisms will contribute to new concepts which finally will have to be translated
Developmental Programming of Renal Function and Re-Programming Approaches
Nüsken, Eva; Dötsch, Jörg; Weber, Lutz T.; Nüsken, Kai-Dietrich
2018-01-01
Chronic kidney disease affects more than 10% of the population. Programming studies have examined the interrelationship between environmental factors in early life and differences in morbidity and mortality between individuals. A number of important principles has been identified, namely permanent structural modifications of organs and cells, long-lasting adjustments of endocrine regulatory circuits, as well as altered gene transcription. Risk factors include intrauterine deficiencies by disturbed placental function or maternal malnutrition, prematurity, intrauterine and postnatal stress, intrauterine and postnatal overnutrition, as well as dietary dysbalances in postnatal life. This mini-review discusses critical developmental periods and long-term sequelae of renal programming in humans and presents studies examining the underlying mechanisms as well as interventional approaches to “re-program” renal susceptibility toward disease. Clinical manifestations of programmed kidney disease include arterial hypertension, proteinuria, aggravation of inflammatory glomerular disease, and loss of kidney function. Nephron number, regulation of the renin–angiotensin–aldosterone system, renal sodium transport, vasomotor and endothelial function, myogenic response, and tubuloglomerular feedback have been identified as being vulnerable to environmental factors. Oxidative stress levels, metabolic pathways, including insulin, leptin, steroids, and arachidonic acid, DNA methylation, and histone configuration may be significantly altered by adverse environmental conditions. Studies on re-programming interventions focused on dietary or anti-oxidative approaches so far. Further studies that broaden our understanding of renal programming mechanisms are needed to ultimately develop preventive strategies. Targeted re-programming interventions in animal models focusing on known mechanisms will contribute to new concepts which finally will have to be translated to human application
Directory of Open Access Journals (Sweden)
Yan Han
2013-01-01
Full Text Available An interval-parameter fuzzy linear programming with stochastic vertices (IFLPSV method is developed for water resources management under uncertainty by coupling interval-parameter fuzzy linear programming (IFLP with stochastic programming (SP. As an extension of existing interval parameter fuzzy linear programming, the developed IFLPSV approach has advantages in dealing with dual uncertainty optimization problems, which uncertainty presents as interval parameter with stochastic vertices in both of the objective functions and constraints. The developed IFLPSV method improves upon the IFLP method by allowing dual uncertainty parameters to be incorporated into the optimization processes. A hybrid intelligent algorithm based on genetic algorithm and artificial neural network is used to solve the developed model. The developed method is then applied to water resources allocation in Beijing city of China in 2020, where water resources shortage is a challenging issue. The results indicate that reasonable solutions have been obtained, which are helpful and useful for decision makers. Although the amount of water supply from Guanting and Miyun reservoirs is declining with rainfall reduction, water supply from the South-to-North Water Transfer project will have important impact on water supply structure of Beijing city, particularly in dry year and extraordinary dry year.
DESIGN OF EDUCATIONAL PROBLEMS ON LINEAR PROGRAMMING USING SYSTEMS OF COMPUTER MATHEMATICS
Directory of Open Access Journals (Sweden)
Volodymyr M. Mykhalevych
2013-11-01
Full Text Available From a perspective of the theory of educational problems a problem of substitution in the conditions of ICT use of one discipline by an educational problem of another discipline is represented. Through the example of mathematical problems of linear programming it is showed that a student’s method of operation in the course of an educational problem solving is determinant in the identification of an educational problem in relation to a specific discipline: linear programming, informatics, mathematical modeling, methods of optimization, automatic control theory, calculus etc. It is substantiated the necessity of linear programming educational problems renovation with the purpose of making students free of bulky similar arithmetic calculations and notes which often becomes a barrier to a deeper understanding of key ideas taken as a basis of algorithms used by them.
A novel approach to linearization of the electromagnetic parameters of tokamaks with an iron core
Energy Technology Data Exchange (ETDEWEB)
Fu, P. E-mail: fupeng@mail.ipp.ac.cn; Liu, Z.Z.; Zou, J.H
2002-05-01
The equivalent model of an iron core tokamak is developed, in which the electromagnetic parameters of several pairs of coils in opposite series (PCOS) are not dependent on the saturation of the iron core during tokamak operation. With this the electromagnetic parameters of all the coils in an iron core tokamak can be linearized, As an example, the electromagnetic parameters of Hefei Super-conductive Tokamak with iron core (HT-7) are linearized, and it is in good agreement with the experimental results. The linearization approach can be applied in real time plasma control and electromagnetic analysis.
Memristance controlling approach based on modification of linear M—q curve
International Nuclear Information System (INIS)
Liu Hai-Jun; Li Zhi-Wei; Yu Hong-Qi; Sun Zhao-Lin; Nie Hong-Shan
2014-01-01
The memristor has broad application prospects in many fields, while in many cases, those fields require accurate impedance control. The nonlinear model is of great importance for realizing memristance control accurately, but the implementing complexity caused by iteration has limited the actual application of this model. Considering the approximate linear characteristics at the middle region of the memristance-charge (M—q) curve of the nonlinear model, this paper proposes a memristance controlling approach, which is achieved by linearizing the middle region of the M—q curve of the nonlinear memristor, and establishes the linear relationship between memristances M and input excitations so that it can realize impedance control precisely by only adjusting input signals briefly. First, it analyzes the feasibility for linearizing the middle part of the M—q curve of the memristor with a nonlinear model from the qualitative perspective. Then, the linearization equations of the middle region of the M—q curve is constructed by using the shift method, and under a sinusoidal excitation case, the analytical relation between the memristance M and the charge time t is derived through the Taylor series expansions. At last, the performance of the proposed approach is demonstrated, including the linearizing capability for the middle part of the M—q curve of the nonlinear model memristor, the controlling ability for memristance M, and the influence of input excitation on linearization errors. (interdisciplinary physics and related areas of science and technology)
Accommodation of practical constraints by a linear programming jet select. [for Space Shuttle
Bergmann, E.; Weiler, P.
1983-01-01
An experimental spacecraft control system will be incorporated into the Space Shuttle flight software and exercised during a forthcoming mission to evaluate its performance and handling qualities. The control system incorporates a 'phase space' control law to generate rate change requests and a linear programming jet select to compute jet firings. Posed as a linear programming problem, jet selection must represent the rate change request as a linear combination of jet acceleration vectors where the coefficients are the jet firing times, while minimizing the fuel expended in satisfying that request. This problem is solved in real time using a revised Simplex algorithm. In order to implement the jet selection algorithm in the Shuttle flight control computer, it was modified to accommodate certain practical features of the Shuttle such as limited computer throughput, lengthy firing times, and a large number of control jets. To the authors' knowledge, this is the first such application of linear programming. It was made possible by careful consideration of the jet selection problem in terms of the properties of linear programming and the Simplex algorithm. These modifications to the jet select algorithm may by useful for the design of reaction controlled spacecraft.
Method for solving fully fuzzy linear programming problems using deviation degree measure
Institute of Scientific and Technical Information of China (English)
Haifang Cheng; Weilai Huang; Jianhu Cai
2013-01-01
A new ful y fuzzy linear programming (FFLP) prob-lem with fuzzy equality constraints is discussed. Using deviation degree measures, the FFLP problem is transformed into a crispδ-parametric linear programming (LP) problem. Giving the value of deviation degree in each constraint, the δ-fuzzy optimal so-lution of the FFLP problem can be obtained by solving this LP problem. An algorithm is also proposed to find a balance-fuzzy optimal solution between two goals in conflict: to improve the va-lues of the objective function and to decrease the values of the deviation degrees. A numerical example is solved to il ustrate the proposed method.
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.
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.
Ji, Zhiwei; Wang, Bing; Yan, Ke; Dong, Ligang; Meng, Guanmin; Shi, Lei
2017-12-21
In recent years, the integration of 'omics' technologies, high performance computation, and mathematical modeling of biological processes marks that the systems biology has started to fundamentally impact the way of approaching drug discovery. The LINCS public data warehouse provides detailed information about cell responses with various genetic and environmental stressors. It can be greatly helpful in developing new drugs and therapeutics, as well as improving the situations of lacking effective drugs, drug resistance and relapse in cancer therapies, etc. In this study, we developed a Ternary status based Integer Linear Programming (TILP) method to infer cell-specific signaling pathway network and predict compounds' treatment efficacy. The novelty of our study is that phosphor-proteomic data and prior knowledge are combined for modeling and optimizing the signaling network. To test the power of our approach, a generic pathway network was constructed for a human breast cancer cell line MCF7; and the TILP model was used to infer MCF7-specific pathways with a set of phosphor-proteomic data collected from ten representative small molecule chemical compounds (most of them were studied in breast cancer treatment). Cross-validation indicated that the MCF7-specific pathway network inferred by TILP were reliable predicting a compound's efficacy. Finally, we applied TILP to re-optimize the inferred cell-specific pathways and predict the outcomes of five small compounds (carmustine, doxorubicin, GW-8510, daunorubicin, and verapamil), which were rarely used in clinic for breast cancer. In the simulation, the proposed approach facilitates us to identify a compound's treatment efficacy qualitatively and quantitatively, and the cross validation analysis indicated good accuracy in predicting effects of five compounds. In summary, the TILP model is useful for discovering new drugs for clinic use, and also elucidating the potential mechanisms of a compound to targets.
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
BEAMPATH: a program library for beam dynamics simulation in linear accelerators
International Nuclear Information System (INIS)
Batygin, Y.K.
1992-01-01
A structured programming technique was used to develop software for space charge dominated beams investigation in linear accelerators. The method includes hierarchical program design using program independent modules and a flexible combination of modules to provide a most effective version of structure for every specific case of simulation. A modular program BEAMPATH was developed for 2D and 3D particle-in-cell simulation of beam dynamics in a structure containing RF gaps, radio-frequency quadrupoles (RFQ), multipole lenses, waveguides, bending magnets and solenoids. (author) 5 refs.; 2 figs
Linear genetic programming application for successive-station monthly streamflow prediction
Danandeh Mehr, Ali; Kahya, Ercan; Yerdelen, Cahit
2014-09-01
In recent decades, artificial intelligence (AI) techniques have been pronounced as a branch of computer science to model wide range of hydrological phenomena. A number of researches have been still comparing these techniques in order to find more effective approaches in terms of accuracy and applicability. In this study, we examined the ability of linear genetic programming (LGP) technique to model successive-station monthly streamflow process, as an applied alternative for streamflow prediction. A comparative efficiency study between LGP and three different artificial neural network algorithms, namely feed forward back propagation (FFBP), generalized regression neural networks (GRNN), and radial basis function (RBF), has also been presented in this study. For this aim, firstly, we put forward six different successive-station monthly streamflow prediction scenarios subjected to training by LGP and FFBP using the field data recorded at two gauging stations on Çoruh River, Turkey. Based on Nash-Sutcliffe and root mean squared error measures, we then compared the efficiency of these techniques and selected the best prediction scenario. Eventually, GRNN and RBF algorithms were utilized to restructure the selected scenario and to compare with corresponding FFBP and LGP. Our results indicated the promising role of LGP for successive-station monthly streamflow prediction providing more accurate results than those of all the ANN algorithms. We found an explicit LGP-based expression evolved by only the basic arithmetic functions as the best prediction model for the river, which uses the records of the both target and upstream stations.
Directory of Open Access Journals (Sweden)
Winasis Winasis
2013-06-01
Full Text Available One of hydro power plant operational problem is how to maximize available water resouces to gather optimal electric power generation. Water availability which is limited and can be stored in a reservoir will influence electrical energy generated by the plant. This paper present a new approach of short term optimization of hydro power plant operation. The objective function is to maximize energy which is produced by power plant on scheduling operation period, with consider water resource availability in reservoir as operational constraint. The optimization problem is formulated in Linear Programming Method, in which this method is a commonly used to solve optimization problem in hydro power plant. Based on simulation results on Ketenger Hydro Power Plant using water flow data on June 1st 2013 shows that this method can be used to solve hydro power plant operation optimization problem well. Electrical energy as main objective function is maximized and all prevailing constrain is satisfied. On this short term operation (24 hour simulation, total energy can be produced is 96121,55 kWh, or 1427 kWh (1,51% greater comparing with real generation condition with 96694 kWh.
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.
A linear bi-level multi-objective program for optimal allocation of water resources.
Directory of Open Access Journals (Sweden)
Ijaz Ahmad
Full Text Available This paper presents a simple bi-level multi-objective linear program (BLMOLP with a hierarchical structure consisting of reservoir managers and several water use sectors under a multi-objective framework for the optimal allocation of limited water resources. Being the upper level decision makers (i.e., leader in the hierarchy, the reservoir managers control the water allocation system and tend to create a balance among the competing water users thereby maximizing the total benefits to the society. On the other hand, the competing water use sectors, being the lower level decision makers (i.e., followers in the hierarchy, aim only to maximize individual sectoral benefits. This multi-objective bi-level optimization problem can be solved using the simultaneous compromise constraint (SICCON technique which creates a compromise between upper and lower level decision makers (DMs, and transforms the multi-objective function into a single decision-making problem. The bi-level model developed in this study has been applied to the Swat River basin in Pakistan for the optimal allocation of water resources among competing water demand sectors and different scenarios have been developed. The application of the model in this study shows that the SICCON is a simple, applicable and feasible approach to solve the BLMOLP problem. Finally, the comparisons of the model results show that the optimization model is practical and efficient when it is applied to different conditions with priorities assigned to various water users.
Interactive Fuzzy Goal Programming approach in multi-response stratified sample surveys
Directory of Open Access Journals (Sweden)
Gupta Neha
2016-01-01
Full Text Available In this paper, we applied an Interactive Fuzzy Goal Programming (IFGP approach with linear, exponential and hyperbolic membership functions, which focuses on maximizing the minimum membership values to determine the preferred compromise solution for the multi-response stratified surveys problem, formulated as a Multi- Objective Non Linear Programming Problem (MONLPP, and by linearizing the nonlinear objective functions at their individual optimum solution, the problem is approximated to an Integer Linear Programming Problem (ILPP. A numerical example based on real data is given, and comparison with some existing allocations viz. Cochran’s compromise allocation, Chatterjee’s compromise allocation and Khowaja’s compromise allocation is made to demonstrate the utility of the approach.
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 L 1 Minimization Estimator). Compared with existing packages for this problem such as clime and flare, our package has three advantages: (1) it efficiently calculates the full piecewise-linear regularization path; (2) it provides an accurate dual certificate as stopping criterion; (3) it is completely coded in C and is highly portable. This package is designed to be useful to statisticians and machine learning researchers for solving a wide range of problems.
Groups, matrices, and vector spaces a group theoretic approach to linear algebra
Carrell, James B
2017-01-01
This unique text provides a geometric approach to group theory and linear algebra, bringing to light the interesting ways in which these subjects interact. Requiring few prerequisites beyond understanding the notion of a proof, the text aims to give students a strong foundation in both geometry and algebra. Starting with preliminaries (relations, elementary combinatorics, and induction), the book then proceeds to the core topics: the elements of the theory of groups and fields (Lagrange's Theorem, cosets, the complex numbers and the prime fields), matrix theory and matrix groups, determinants, vector spaces, linear mappings, eigentheory and diagonalization, Jordan decomposition and normal form, normal matrices, and quadratic forms. The final two chapters consist of a more intensive look at group theory, emphasizing orbit stabilizer methods, and an introduction to linear algebraic groups, which enriches the notion of a matrix group. Applications involving symm etry groups, determinants, linear coding theory ...
International Nuclear Information System (INIS)
Loock, Peter van; Nemoto, Kae; Munro, William J.; Raynal, Philippe; Luetkenhaus, Norbert
2006-01-01
We discuss the problem of implementing generalized measurements [positive operator-valued measures (POVMs)] with linear optics, either based upon a static linear array or including conditional dynamics. In our approach, a given POVM shall be identified as a solution to an optimization problem for a chosen cost function. We formulate a general principle: the implementation is only possible if a linear-optics circuit exists for which the quantum mechanical optimum (minimum) is still attainable after dephasing the corresponding quantum states. The general principle enables us, for instance, to derive a set of necessary conditions for the linear-optics implementation of the POVM that realizes the quantum mechanically optimal unambiguous discrimination of two pure nonorthogonal states. This extends our previous results on projection measurements and the exact discrimination of orthogonal states
Electromagnetic response in kinetic energy driven cuprate superconductors: Linear response approach
International Nuclear Information System (INIS)
Krzyzosiak, Mateusz; Huang, Zheyu; Feng, Shiping; Gonczarek, Ryszard
2010-01-01
Within the framework of the kinetic energy driven superconductivity, the electromagnetic response in cuprate superconductors is studied in the linear response approach. The kernel of the response function is evaluated and employed to calculate the local magnetic field profile, the magnetic field penetration depth, and the superfluid density, based on the specular reflection model for a purely transverse vector potential. It is shown that the low temperature magnetic field profile follows an exponential decay at the surface, while the magnetic field penetration depth depends linearly on temperature, except for the strong deviation from the linear characteristics at extremely low temperatures. The superfluid density is found to decrease linearly with decreasing doping concentration in the underdoped regime. The problem of gauge invariance is addressed and an approximation for the dressed current vertex, which does not violate local charge conservation is proposed and discussed.
Optimal local dimming for LED-backlit LCD displays via linear programming
DEFF Research Database (Denmark)
Shu, Xiao; Wu, Xiaolin; Forchhammer, Søren
2012-01-01
and the attenuations of LCD pixels. The objective is to minimize the distortion in luminance reproduction due to the leakage of LCD and the coarse granularity of the LED lights. The optimization problem is formulated as one of linear programming, and both exact and approximate algorithms are proposed. Simulation...
DEFF Research Database (Denmark)
Hernández, Adriana Carolina Luna; Aldana, Nelson Leonardo Diaz; Graells, Moises
2017-01-01
-side strategy, defined as a general mixed-integer linear programming by taking into account two stages for proper charging of the storage units. This model is considered as a deterministic problem that aims to minimize operating costs and promote self-consumption based on 24-hour ahead forecast data...
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
Discounted semi-Markov decision processes : linear programming and policy iteration
Wessels, J.; van Nunen, J.A.E.E.
1975-01-01
For semi-Markov decision processes with discounted rewards we derive the well known results regarding the structure of optimal strategies (nonrandomized, stationary Markov strategies) and the standard algorithms (linear programming, policy iteration). Our analysis is completely based on a primal
Fuzzy chance constrained linear programming model for scrap charge optimization in steel production
DEFF Research Database (Denmark)
Rong, Aiying; Lahdelma, Risto
2008-01-01
the uncertainty based on fuzzy set theory and constrain the failure risk based on a possibility measure. Consequently, the scrap charge optimization problem is modeled as a fuzzy chance constrained linear programming problem. Since the constraints of the model mainly address the specification of the product...
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.)…
Discounted semi-Markov decision processes : linear programming and policy iteration
Wessels, J.; van Nunen, J.A.E.E.
1974-01-01
For semi-Markov decision processes with discounted rewards we derive the well known results regarding the structure of optimal strategies (nonrandomized, stationary Markov strategies) and the standard algorithms (linear programming, policy iteration). Our analysis is completely based on a primal
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 (...
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.
Huitzing, Hiddo A.
2004-01-01
This article shows how set covering with item sampling (SCIS) methods can be used in the analysis and preanalysis of linear programming models for test assembly (LPTA). LPTA models can construct tests, fulfilling a set of constraints set by the test assembler. Sometimes, no solution to the LPTA model exists. The model is then said to be…
An Interactive Method to Solve Infeasibility in Linear Programming Test Assembling Models
Huitzing, Hiddo A.
2004-01-01
In optimal assembly of tests from item banks, linear programming (LP) models have proved to be very useful. Assembly by hand has become nearly impossible, but these LP techniques are able to find the best solutions, given the demands and needs of the test to be assembled and the specifics of the item bank from which it is assembled. However,…
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…
The effect of workload constraints in linear programming models for production planning
Jansen, M.M.; Kok, de A.G.; Adan, I.J.B.F.
2011-01-01
Linear programming (LP) models for production planning incorporate a model of the manufacturing system that is necessarily deterministic. Although these deterministic models are the current state-of-the-art, it should be recognized that they are used in an environment that is inherently stochastic.
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,
Cooke, C. H.
1975-01-01
STICAP (Stiff Circuit Analysis Program) is a FORTRAN 4 computer program written for the CDC-6400-6600 computer series and SCOPE 3.0 operating system. It provides the circuit analyst a tool for automatically computing the transient responses and frequency responses of large linear time invariant networks, both stiff and nonstiff (algorithms and numerical integration techniques are described). The circuit description and user's program input language is engineer-oriented, making simple the task of using the program. Engineering theories underlying STICAP are examined. A user's manual is included which explains user interaction with the program and gives results of typical circuit design applications. Also, the program structure from a systems programmer's viewpoint is depicted and flow charts and other software documentation are given.
Proposing an Aggregate Production Planning Model by Goal Programming Approach, a Case Study
Directory of Open Access Journals (Sweden)
Mansoureh Farzam Rad
2014-06-01
Full Text Available Production planning is one of the most important functions in the process of production management. Production planning in the intermediate range of time is termed as aggregate production planning (APP. Aggregate production planning is an important upper level planning activity in a production management system. The present study tries to suggest an aggregate production planning model for products of Hafez tile factory during one year. Due to this fact that the director of the company seeks 3 main objectives to determine the optimal production rate, the linear goal planning method was employed. After solving the problem, in order to examine the efficiency and the distinctiveness of this method in compare to linear programming, the problem was modeled just by considering one objective then was solved by linear programming approach. The findings revealed the goal programming with multi objectives resulted more appropriate solution rather than linear programming with just one objective.
International Nuclear Information System (INIS)
Aref'ev, A.V.; Blokhov, M.V.; Gerasimov, V.F.
1981-01-01
A program of physical investigations and the corresponding requirements to accelerated beam parameters are discussed in brief. The state and working capacity of separate units and the accelerator as a whole for the 8-year operating period are analyzed. The aim and principal program points of linear electron accelerator modernization are defined. The program of accelerator modernization assumes: electron beam energy increase up to 100-120 MeV; mounting of three additional accelerating sections; clystron efficiency increase; development of a highly reliable modulator; stabilized power supply sources; a system of synchronous start-up; a focusing system; a beam separation system and etc [ru
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. .
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.
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.
Performance improvement of shunt active power filter based on non-linear least-square approach
DEFF Research Database (Denmark)
Terriche, Yacine
2018-01-01
. This paper proposes an improved open loop strategy which is unconditionally stable and flexible. The proposed method which is based on non-linear least square (NLS) approach can extract the fundamental voltage and estimates its phase within only half cycle, even in the presence of odd harmonics and dc offset......). The synchronous reference frame (SRF) approach is widely used for generating the RCC due to its simplicity and computation efficiency. However, the SRF approach needs precise information of the voltage phase which becomes a challenge under adverse grid conditions. A typical solution to answer this need...
A data fusion based approach for damage detection in linear systems
Directory of Open Access Journals (Sweden)
Ernesto Grande
2014-07-01
Full Text Available The aim of the present paper is to propose innovative approaches able to improve the capability of classical damage indicators in detecting the damage position in linear systems. In particular, starting from classical indicators based on the change of the flexibility matrix and on the change of the modal strain energy, the proposed approaches consider two data fusion procedures both based on the Dempster-Shafer theory. Numerical applications are reported in the paper in order to assess the reliability of the proposed approaches considering different damage scenarios, different sets of modes of vibration and the presence of errors affecting the accounted modes of vibrations.
GREIT: a unified approach to 2D linear EIT reconstruction of lung images.
Adler, Andy; Arnold, John H; Bayford, Richard; Borsic, Andrea; Brown, Brian; Dixon, Paul; Faes, Theo J C; Frerichs, Inéz; Gagnon, Hervé; Gärber, Yvo; Grychtol, Bartłomiej; Hahn, Günter; Lionheart, William R B; Malik, Anjum; Patterson, Robert P; Stocks, Janet; Tizzard, Andrew; Weiler, Norbert; Wolf, Gerhard K
2009-06-01
Electrical impedance tomography (EIT) is an attractive method for clinically monitoring patients during mechanical ventilation, because it can provide a non-invasive continuous image of pulmonary impedance which indicates the distribution of ventilation. However, most clinical and physiological research in lung EIT is done using older and proprietary algorithms; this is an obstacle to interpretation of EIT images because the reconstructed images are not well characterized. To address this issue, we develop a consensus linear reconstruction algorithm for lung EIT, called GREIT (Graz consensus Reconstruction algorithm for EIT). This paper describes the unified approach to linear image reconstruction developed for GREIT. The framework for the linear reconstruction algorithm consists of (1) detailed finite element models of a representative adult and neonatal thorax, (2) consensus on the performance figures of merit for EIT image reconstruction and (3) a systematic approach to optimize a linear reconstruction matrix to desired performance measures. Consensus figures of merit, in order of importance, are (a) uniform amplitude response, (b) small and uniform position error, (c) small ringing artefacts, (d) uniform resolution, (e) limited shape deformation and (f) high resolution. Such figures of merit must be attained while maintaining small noise amplification and small sensitivity to electrode and boundary movement. This approach represents the consensus of a large and representative group of experts in EIT algorithm design and clinical applications for pulmonary monitoring. All software and data to implement and test the algorithm have been made available under an open source license which allows free research and commercial use.
GREIT: a unified approach to 2D linear EIT reconstruction of lung images
International Nuclear Information System (INIS)
Adler, Andy; Arnold, John H; Bayford, Richard; Tizzard, Andrew; Borsic, Andrea; Brown, Brian; Dixon, Paul; Faes, Theo J C; Frerichs, Inéz; Weiler, Norbert; Gagnon, Hervé; Gärber, Yvo; Grychtol, Bartłomiej; Hahn, Günter; Lionheart, William R B; Malik, Anjum; Patterson, Robert P; Stocks, Janet; Wolf, Gerhard K
2009-01-01
Electrical impedance tomography (EIT) is an attractive method for clinically monitoring patients during mechanical ventilation, because it can provide a non-invasive continuous image of pulmonary impedance which indicates the distribution of ventilation. However, most clinical and physiological research in lung EIT is done using older and proprietary algorithms; this is an obstacle to interpretation of EIT images because the reconstructed images are not well characterized. To address this issue, we develop a consensus linear reconstruction algorithm for lung EIT, called GREIT (Graz consensus Reconstruction algorithm for EIT). This paper describes the unified approach to linear image reconstruction developed for GREIT. The framework for the linear reconstruction algorithm consists of (1) detailed finite element models of a representative adult and neonatal thorax, (2) consensus on the performance figures of merit for EIT image reconstruction and (3) a systematic approach to optimize a linear reconstruction matrix to desired performance measures. Consensus figures of merit, in order of importance, are (a) uniform amplitude response, (b) small and uniform position error, (c) small ringing artefacts, (d) uniform resolution, (e) limited shape deformation and (f) high resolution. Such figures of merit must be attained while maintaining small noise amplification and small sensitivity to electrode and boundary movement. This approach represents the consensus of a large and representative group of experts in EIT algorithm design and clinical applications for pulmonary monitoring. All software and data to implement and test the algorithm have been made available under an open source license which allows free research and commercial use
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.
International Nuclear Information System (INIS)
Feng, H.; Zheng, Y.; Ding, S.
2007-01-01
Infrared multiphoton vibrational excitation of the linear triatomic molecule has been studied using the quadratic anharmonic Lie-algebra model, unitary transformations, and Magnus approximation. An explicit Lie-algebra expression for the vibrational transition probability is obtained by using a Lie-algebra approach. This explicit Lie-algebra expressions for time-evolution operator and vibrational transition probabilities make the computation clearer and easier. The infrared multiphoton vibrational excitation of the DCN linear tri-atomic molecule is discussed as an example
Transition to Coherence in Populations of Coupled Chaotic Oscillators: A Linear Response Approach
International Nuclear Information System (INIS)
Topaj, Dmitri; Kye, Won-Ho; Pikovsky, Arkady
2001-01-01
We consider the collective dynamics in an ensemble of globally coupled chaotic maps. The transition to the coherent state with a macroscopic mean field is analyzed in the framework of the linear response theory. The linear response function for the chaotic system is obtained using the perturbation approach to the Frobenius-Perron operator. The transition point is defined from this function by virtue of the self-excitation condition for the feedback loop. Analytical results for the coupled Bernoulli maps are confirmed by the numerics
Stability of multi-objective bi-level linear programming problems under fuzziness
Directory of Open Access Journals (Sweden)
Abo-Sinna Mahmoud A.
2013-01-01
Full Text Available This paper deals with multi-objective bi-level linear programming problems under fuzzy environment. In the proposed method, tentative solutions are obtained and evaluated by using the partial information on preference of the decision-makers at each level. The existing results concerning the qualitative analysis of some basic notions in parametric linear programming problems are reformulated to study the stability of multi-objective bi-level linear programming problems. An algorithm for obtaining any subset of the parametric space, which has the same corresponding Pareto optimal solution, is presented. Also, this paper established the model for the supply-demand interaction in the age of electronic commerce (EC. First of all, the study uses the individual objectives of both parties as the foundation of the supply-demand interaction. Subsequently, it divides the interaction, in the age of electronic commerce, into the following two classifications: (i Market transactions, with the primary focus on the supply demand relationship in the marketplace; and (ii Information service, with the primary focus on the provider and the user of information service. By applying the bi-level programming technique of interaction process, the study will develop an analytical process to explain how supply-demand interaction achieves a compromise or why the process fails. Finally, a numerical example of information service is provided for the sake of illustration.
Fast simulation of non-linear pulsed ultrasound fields using an angular spectrum approach
DEFF Research Database (Denmark)
Du, Yigang; Jensen, Jørgen Arendt
2013-01-01
A fast non-linear pulsed ultrasound field simulation is presented. It is implemented based on an angular spectrum approach (ASA), which analytically solves the non-linear wave equation. The ASA solution to the Westervelt equation is derived in detail. The calculation speed is significantly...... increased compared to a numerical solution using an operator splitting method (OSM). The ASA has been modified and extended to pulsed non-linear ultrasound fields in combination with Field II, where any array transducer with arbitrary geometry, excitation, focusing and apodization can be simulated...... with a center frequency of 5 MHz. The speed is increased approximately by a factor of 140 and the calculation time is 12 min with a standard PC, when simulating the second harmonic pulse at the focal point. For the second harmonic point spread function the full width error is 1.5% at 6 dB and 6.4% at 12 d...
Wireless Positioning Based on a Segment-Wise Linear Approach for Modeling the Target Trajectory
DEFF Research Database (Denmark)
Figueiras, Joao; Pedersen, Troels; Schwefel, Hans-Peter
2008-01-01
Positioning solutions in infrastructure-based wireless networks generally operate by exploiting the channel information of the links between the Wireless Devices and fixed networking Access Points. The major challenge of such solutions is the modeling of both the noise properties of the channel...... measurements and the user mobility patterns. One class of typical human being movement patterns is the segment-wise linear approach, which is studied in this paper. Current tracking solutions, such as the Constant Velocity model, hardly handle such segment-wise linear patterns. In this paper we propose...... a segment-wise linear model, called the Drifting Points model. The model results in an increased performance when compared with traditional solutions....
Dynamics and control of quadcopter using linear model predictive control approach
Islam, M.; Okasha, M.; Idres, M. M.
2017-12-01
This paper investigates the dynamics and control of a quadcopter using the Model Predictive Control (MPC) approach. The dynamic model is of high fidelity and nonlinear, with six degrees of freedom that include disturbances and model uncertainties. The control approach is developed based on MPC to track different reference trajectories ranging from simple ones such as circular to complex helical trajectories. In this control technique, a linearized model is derived and the receding horizon method is applied to generate the optimal control sequence. Although MPC is computer expensive, it is highly effective to deal with the different types of nonlinearities and constraints such as actuators’ saturation and model uncertainties. The MPC parameters (control and prediction horizons) are selected by trial-and-error approach. Several simulation scenarios are performed to examine and evaluate the performance of the proposed control approach using MATLAB and Simulink environment. Simulation results show that this control approach is highly effective to track a given reference trajectory.
School District Program Cost Accounting: An Alternative Approach
Hentschke, Guilbert C.
1975-01-01
Discusses the value for school districts of a program cost accounting system and examines different approaches to generating program cost data, with particular emphasis on the "cost allocation to program system" (CAPS) and the traditional "transaction-based system." (JG)
Mixed integer linear programming model for dynamic supplier selection problem considering discounts
Directory of Open Access Journals (Sweden)
Adi Wicaksono Purnawan
2018-01-01
Full Text Available Supplier selection is one of the most important elements in supply chain management. This function involves evaluation of many factors such as, material costs, transportation costs, quality, delays, supplier capacity, storage capacity and others. Each of these factors varies with time, therefore, supplier identified for one period is not necessarily be same for the next period to supply the same product. So, mixed integer linear programming (MILP was developed to overcome the dynamic supplier selection problem (DSSP. In this paper, a mixed integer linear programming model is built to solve the lot-sizing problem with multiple suppliers, multiple periods, multiple products and quantity discounts. The buyer has to make a decision for some products which will be supplied by some suppliers for some periods cosidering by discount. To validate the MILP model with randomly generated data. The model is solved by Lingo 16.
Visualizing measurement for 3D smooth density distributions by means of linear programming
International Nuclear Information System (INIS)
Tayama, Norio; Yang, Xue-dong
1994-01-01
This paper is concerned with a theoretical possibility of a new visualizing measurement method based on an optimum 3D reconstruction from a few selected projections. A theory of optimum 3D reconstruction by a linear programming is discussed, utilizing a few projections for sampled 3D smooth-density-distribution model which satisfies the condition of the 3D sampling theorem. First by use of the sampling theorem, it is shown that we can set up simultaneous simple equations which corresponds to the case of the parallel beams. Then we solve the simultaneous simple equations by means of linear programming algorithm, and we can get an optimum 3D density distribution images with minimum error in the reconstruction. The results of computer simulation with the algorithm are presented. (author)
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.
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.
CiOpt: a program for optimization of the frequency response of linear circuits
Miró Sans, Joan Maria; Palà Schönwälder, Pere
1991-01-01
An interactive personal-computer program for optimizing the frequency response of linear lumped circuits (CiOpt) is presented. CiOpt has proved to be an efficient tool in improving designs where the inclusion of more accurate device models distorts the desired frequency response, as well as in device modeling. The outputs of CiOpt are the element values which best match the obtained and the desired frequency response. The optimization algorithms used (the Fletcher-Powell and Newton's methods,...
Roslee Rajikan; Nurul Izza Ahmad Zaidi; Siti Masitah Elias; Suzana Shahar; Zahara Abd Manaf; Noor Aini Md Yusoff
2017-01-01
Differences in socioeconomic profile may influences healthy food choices, particularly among individuals with low socioeconomic status. Thus, high-energy dense foods become the preferences compared to high nutritional content foods due to their cheaper price. The present study aims to develop healthy and palatable diet at the minimum cost based on Malaysian Dietary Guidelines 2010 and Recommended Nutrient Intake 2005 via linear programming. A total of 96 female adults from low socioeconomic f...
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....
Fuzzy solution of the linear programming problem with interval coefficients in the constraints
Dorota Kuchta
2005-01-01
A fuzzy concept of solving the linear programming problem with interval coefficients is proposed. For each optimism level of the decision maker (where the optimism concerns the certainty that no errors have been committed in the estimation of the interval coefficients and the belief that optimistic realisations of the interval coefficients will occur) another interval solution of the problem will be generated and the decision maker will be able to choose the final solution having a complete v...
A Mixed Integer Linear Programming Model for the North Atlantic Aircraft Trajectory Planning
Sbihi , Mohammed; Rodionova , Olga; Delahaye , Daniel; Mongeau , Marcel
2015-01-01
International audience; This paper discusses the trajectory planning problem for ights in the North Atlantic oceanic airspace (NAT). We develop a mathematical optimization framework in view of better utilizing available capacity by re-routing aircraft. The model is constructed by discretizing the problem parameters. A Mixed integer linear program (MILP) is proposed. Based on the MILP a heuristic to solve real-size instances is also introduced
Learning Bayesian network structure: towards the essential graph by integer linear programming tools
Czech Academy of Sciences Publication Activity Database
Studený, Milan; Haws, D.
2014-01-01
Roč. 55, č. 4 (2014), s. 1043-1071 ISSN 0888-613X R&D Projects: GA ČR GA13-20012S Institutional support: RVO:67985556 Keywords : learning Bayesian network structure * integer linear programming * characteristic imset * essential graph Subject RIV: BA - General Mathematics Impact factor: 2.451, year: 2014 http://library.utia.cas.cz/separaty/2014/MTR/studeny-0427002.pdf
International Nuclear Information System (INIS)
Ghandour, J; Aberkane, S; Ponsart, J-C
2014-01-01
In this paper the control problem of a quadrotor vehicle experiencing a rotor failure is investigated. We develop a Feedback linearization approach to design a controller whose task is to make the vehicle performs trajectory following. Then we use the same approach to design a controller whose task is to make the vehicle enter a stable spin around its vertical axis, while retaining zero angular velocities around the other axis when a rotor failure is present. These conditions can be exploited to design a second control loop, which is used to perform trajectory following. The proposed double control loop architecture allows the vehicle to perform both trajectory and roll/pitch control. At last, to test the robustness of the feedback linearization technique, we applied wind to the quadrotor in mid flight
International Nuclear Information System (INIS)
Winicour, Jeffrey
2017-01-01
An algebraic-hyperbolic method for solving the Hamiltonian and momentum constraints has recently been shown to be well posed for general nonlinear perturbations of the initial data for a Schwarzschild black hole. This is a new approach to solving the constraints of Einstein’s equations which does not involve elliptic equations and has potential importance for the construction of binary black hole data. In order to shed light on the underpinnings of this approach, we consider its application to obtain solutions of the constraints for linearized perturbations of Minkowski space. In that case, we find the surprising result that there are no suitable Cauchy hypersurfaces in Minkowski space for which the linearized algebraic-hyperbolic constraint problem is well posed. (note)
New approach to derive linear power/burnup history input for CANDU fuel codes
International Nuclear Information System (INIS)
Lac Tang, T.; Richards, M.; Parent, G.
2003-01-01
The fuel element linear power / burnup history is a required input for the ELESTRES code in order to simulate CANDU fuel behavior during normal operating conditions and also to provide input for the accident analysis codes ELOCA and SOURCE. The purpose of this paper is to present a new approach to derive 'true', or at least more realistic linear power / burnup histories. Such an approach can be used to recreate any typical bundle power history if only a single pair of instantaneous values of bundle power and burnup, together with the position in the channel, are known. The histories obtained could be useful to perform more realistic simulations for safety analyses for cases where the reference (overpower) history is not appropriate. (author)
Directory of Open Access Journals (Sweden)
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.
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.
An Improved Method for Solving Multiobjective Integer Linear Fractional Programming Problem
Directory of Open Access Journals (Sweden)
Meriem Ait Mehdi
2014-01-01
Full Text Available We describe an improvement of Chergui and Moulaï’s method (2008 that generates the whole efficient set of a multiobjective integer linear fractional program based on the branch and cut concept. The general step of this method consists in optimizing (maximizing without loss of generality one of the fractional objective functions over a subset of the original continuous feasible set; then if necessary, a branching process is carried out until obtaining an integer feasible solution. At this stage, an efficient cut is built from the criteria’s growth directions in order to discard a part of the feasible domain containing only nonefficient solutions. Our contribution concerns firstly the optimization process where a linear program that we define later will be solved at each step rather than a fractional linear program. Secondly, local ideal and nadir points will be used as bounds to prune some branches leading to nonefficient solutions. The computational experiments show that the new method outperforms the old one in all the treated instances.
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
International Nuclear Information System (INIS)
Sergienko, I.V.; Golodnikov, A.N.
1984-01-01
This article applies the methods of decompositions, which are used to solve continuous linear problems, to integer and partially integer problems. The fall-vector method is used to solve the obtained coordinate problems. An algorithm of the fall-vector is described. The Kornai-Liptak decomposition principle is used to reduce the integer linear programming problem to integer linear programming problems of a smaller dimension and to a discrete coordinate problem with simple constraints
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.
A note on probabilistic models over strings: the linear algebra approach.
Bouchard-Côté, Alexandre
2013-12-01
Probabilistic models over strings have played a key role in developing methods that take into consideration indels as phylogenetically informative events. There is an extensive literature on using automata and transducers on phylogenies to do inference on these probabilistic models, in which an important theoretical question is the complexity of computing the normalization of a class of string-valued graphical models. This question has been investigated using tools from combinatorics, dynamic programming, and graph theory, and has practical applications in Bayesian phylogenetics. In this work, we revisit this theoretical question from a different point of view, based on linear algebra. The main contribution is a set of results based on this linear algebra view that facilitate the analysis and design of inference algorithms on string-valued graphical models. As an illustration, we use this method to give a new elementary proof of a known result on the complexity of inference on the "TKF91" model, a well-known probabilistic model over strings. Compared to previous work, our proving method is easier to extend to other models, since it relies on a novel weak condition, triangular transducers, which is easy to establish in practice. The linear algebra view provides a concise way of describing transducer algorithms and their compositions, opens the possibility of transferring fast linear algebra libraries (for example, based on GPUs), as well as low rank matrix approximation methods, to string-valued inference problems.
Energy Technology Data Exchange (ETDEWEB)
Ellis, J H; McBean, E A; Farquhar, G J
1985-01-01
A Linear Programming model is presented for development of acid rain abatement strategies in eastern North America. For a system comprised of 235 large controllable point sources and 83 uncontrolled area sources, it determines the least-cost method of reducing SO/sub 2/ emissions to satisfy maximum wet sulfur deposition limits at 20 sensitive receptor locations. In this paper, the purely deterministic model is extended to a probabilistic form by incorporating the effects of meteorologic variability on the long-range pollutant transport processes. These processes are represented by source-receptor-specific transfer coefficients. Experiments for quantifying the spatial variability of transfer coefficients showed their distributions to be approximately lognormal with logarithmic standard deviations consistently about unity. Three methods of incorporating second-moment random variable uncertainty into the deterministic LP framework are described: Two-Stage Programming Under Uncertainty, Chance-Constrained Programming and Stochastic Linear Programming. A composite CCP-SLP model is developed which embodies the two-dimensional characteristics of transfer coefficient uncertainty. Two probabilistic formulations are described involving complete colinearity and complete noncolinearity for the transfer coefficient covariance-correlation structure. The completely colinear and noncolinear formulations are considered extreme bounds in a meteorologic sense and yield abatement strategies of largely didactic value. Such strategies can be characterized as having excessive costs and undesirable deposition results in the completely colinear case and absence of a clearly defined system risk level (other than expected-value) in the noncolinear formulation.
State space model extraction of thermohydraulic systems – Part I: A linear graph approach
International Nuclear Information System (INIS)
Uren, K.R.; Schoor, G. van
2013-01-01
Thermohydraulic simulation codes are increasingly making use of graphical design interfaces. The user can quickly and easily design a thermohydraulic system by placing symbols on the screen resembling system components. These components can then be connected to form a system representation. Such system models may then be used to obtain detailed simulations of the physical system. Usually this kind of simulation models are too complex and not ideal for control system design. Therefore, a need exists for automated techniques to extract lumped parameter models useful for control system design. The goal of this first paper, in a two part series, is to propose a method that utilises a graphical representation of a thermohydraulic system, and a lumped parameter modelling approach, to extract state space models. In this methodology each physical domain of the thermohydraulic system is represented by a linear graph. These linear graphs capture the interaction between all components within and across energy domains – hydraulic, thermal and mechanical. These linear graphs are analysed using a graph-theoretic approach to derive reduced order state space models. These models capture the dominant dynamics of the thermohydraulic system and are ideal for control system design purposes. The proposed state space model extraction method is demonstrated by considering a U-tube system. A non-linear state space model is extracted representing both the hydraulic and thermal domain dynamics of the system. The simulated state space model is compared with a Flownex ® model of the U-tube. Flownex ® is a validated systems thermal-fluid simulation software package. - Highlights: • A state space model extraction methodology based on graph-theoretic concepts. • An energy-based approach to consider multi-domain systems in a common framework. • Allow extraction of transparent (white-box) state space models automatically. • Reduced order models containing only independent state
DEFF Research Database (Denmark)
Andreasen, Martin Møller; Christensen, Bent Jesper
This paper suggests a new and easy approach to estimate linear and non-linear dynamic term structure models with latent factors. We impose no distributional assumptions on the factors and they may therefore be non-Gaussian. The novelty of our approach is to use many observables (yields or bonds p...
Quantitative Approach to Failure Mode and Effect Analysis for Linear Accelerator Quality Assurance
Energy Technology Data Exchange (ETDEWEB)
O' Daniel, Jennifer C., E-mail: jennifer.odaniel@duke.edu; Yin, Fang-Fang
2017-05-01
Purpose: To determine clinic-specific linear accelerator quality assurance (QA) TG-142 test frequencies, to maximize physicist time efficiency and patient treatment quality. Methods and Materials: A novel quantitative approach to failure mode and effect analysis is proposed. Nine linear accelerator-years of QA records provided data on failure occurrence rates. The severity of test failure was modeled by introducing corresponding errors into head and neck intensity modulated radiation therapy treatment plans. The relative risk of daily linear accelerator QA was calculated as a function of frequency of test performance. Results: Although the failure severity was greatest for daily imaging QA (imaging vs treatment isocenter and imaging positioning/repositioning), the failure occurrence rate was greatest for output and laser testing. The composite ranking results suggest that performing output and lasers tests daily, imaging versus treatment isocenter and imaging positioning/repositioning tests weekly, and optical distance indicator and jaws versus light field tests biweekly would be acceptable for non-stereotactic radiosurgery/stereotactic body radiation therapy linear accelerators. Conclusions: Failure mode and effect analysis is a useful tool to determine the relative importance of QA tests from TG-142. Because there are practical time limitations on how many QA tests can be performed, this analysis highlights which tests are the most important and suggests the frequency of testing based on each test's risk priority number.
Valid statistical approaches for analyzing sholl data: Mixed effects versus simple linear models.
Wilson, Machelle D; Sethi, Sunjay; Lein, Pamela J; Keil, Kimberly P
2017-03-01
The Sholl technique is widely used to quantify dendritic morphology. Data from such studies, which typically sample multiple neurons per animal, are often analyzed using simple linear models. However, simple linear models fail to account for intra-class correlation that occurs with clustered data, which can lead to faulty inferences. Mixed effects models account for intra-class correlation that occurs with clustered data; thus, these models more accurately estimate the standard deviation of the parameter estimate, which produces more accurate p-values. While mixed models are not new, their use in neuroscience has lagged behind their use in other disciplines. A review of the published literature illustrates common mistakes in analyses of Sholl data. Analysis of Sholl data collected from Golgi-stained pyramidal neurons in the hippocampus of male and female mice using both simple linear and mixed effects models demonstrates that the p-values and standard deviations obtained using the simple linear models are biased downwards and lead to erroneous rejection of the null hypothesis in some analyses. The mixed effects approach more accurately models the true variability in the data set, which leads to correct inference. Mixed effects models avoid faulty inference in Sholl analysis of data sampled from multiple neurons per animal by accounting for intra-class correlation. Given the widespread practice in neuroscience of obtaining multiple measurements per subject, there is a critical need to apply mixed effects models more widely. Copyright © 2017 Elsevier B.V. All rights reserved.
Quantitative Approach to Failure Mode and Effect Analysis for Linear Accelerator Quality Assurance.
O'Daniel, Jennifer C; Yin, Fang-Fang
2017-05-01
To determine clinic-specific linear accelerator quality assurance (QA) TG-142 test frequencies, to maximize physicist time efficiency and patient treatment quality. A novel quantitative approach to failure mode and effect analysis is proposed. Nine linear accelerator-years of QA records provided data on failure occurrence rates. The severity of test failure was modeled by introducing corresponding errors into head and neck intensity modulated radiation therapy treatment plans. The relative risk of daily linear accelerator QA was calculated as a function of frequency of test performance. Although the failure severity was greatest for daily imaging QA (imaging vs treatment isocenter and imaging positioning/repositioning), the failure occurrence rate was greatest for output and laser testing. The composite ranking results suggest that performing output and lasers tests daily, imaging versus treatment isocenter and imaging positioning/repositioning tests weekly, and optical distance indicator and jaws versus light field tests biweekly would be acceptable for non-stereotactic radiosurgery/stereotactic body radiation therapy linear accelerators. Failure mode and effect analysis is a useful tool to determine the relative importance of QA tests from TG-142. Because there are practical time limitations on how many QA tests can be performed, this analysis highlights which tests are the most important and suggests the frequency of testing based on each test's risk priority number. Copyright © 2017 Elsevier Inc. All rights reserved.
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.
Energy Technology Data Exchange (ETDEWEB)
Domingos, Roberto P.; Schirru, Roberto; Martinez, Aquilino S. [Universidade Federal, Rio de Janeiro, RJ (Brazil). Coordenacao dos Programas de Pos-graduacao de Engenharia
1997-12-01
This work presents a Genetic Programming paradigm and a nuclear application. A field of Artificial Intelligence, based on the concepts of Species Evolution and Natural Selection, can be understood as a self-programming process where the computer is the main agent responsible for the discovery of a program able to solve a given problem. In the present case, the problem was to find a mathematical expression in symbolic form, able to express the existent relation between equivalent ratio of a fuel cell, the enrichment of fuel elements and the multiplication factor. Such expression would avoid repeatedly reactor physics codes execution for core optimization. The results were compared with those obtained by different techniques such as Neural Networks and Linear Multiple Regression. Genetic Programming has shown to present a performance as good as, and under some features superior to Neural Network and Linear Multiple Regression. (author). 10 refs., 8 figs., 1 tabs.
International Nuclear Information System (INIS)
Piacentino, A.; Cardona, F.
2008-01-01
The optimization of synthesis, design and operation in trigeneration systems for building applications is a quite complex task, due to the high number of decision variables, the presence of irregular heat, cooling and electric load profiles and the variable electricity price. Consequently, computer-aided techniques are usually adopted to achieve the optimal solution, based either on iterative techniques, linear or non-linear programming or evolutionary search. Large efforts have been made in improving algorithm efficiency, which have resulted in an increasingly rapid convergence to the optimal solution and in reduced calculation time; robust algorithm have also been formulated, assuming stochastic behaviour for energy loads and prices. This paper is based on the assumption that margins for improvements in the optimization of trigeneration systems still exist, which require an in-depth understanding of plant's energetic behaviour. Robustness in the optimization of trigeneration systems has more to do with a 'correct and comprehensive' than with an 'efficient' modelling, being larger efforts required to energy specialists rather than to experts in efficient algorithms. With reference to a mixed integer linear programming model implemented in MatLab for a trigeneration system including a pressurized (medium temperature) heat storage, the relevant contribute of thermoeconomics and energo-environmental analysis in the phase of mathematical modelling and code testing are shown
A kinetic approach to some quasi-linear laws of macroeconomics
Gligor, M.; Ignat, M.
2002-11-01
Some previous works have presented the data on wealth and income distributions in developed countries and have found that the great majority of population is described by an exponential distribution, which results in idea that the kinetic approach could be adequate to describe this empirical evidence. The aim of our paper is to extend this framework by developing a systematic kinetic approach of the socio-economic systems and to explain how linear laws, modelling correlations between macroeconomic variables, may arise in this context. Firstly we construct the Boltzmann kinetic equation for an idealised system composed by many individuals (workers, officers, business men, etc.), each of them getting a certain income and spending money for their needs. To each individual a certain time variable amount of money is associated this meaning him/her phase space coordinate. In this way the exponential distribution of money in a closed economy is explicitly found. The extension of this result, including states near the equilibrium, give us the possibility to take into account the regular increase of the total amount of money, according to the modern economic theories. The Kubo-Green-Onsager linear response theory leads us to a set of linear equations between some macroeconomic variables. Finally, the validity of such laws is discussed in relation with the time reversal symmetry and is tested empirically using some macroeconomic time series.
Quantitative Assessment of Arrhythmia Using Non-linear Approach: A Non-invasive Prognostic Tool
Chakraborty, Monisha; Ghosh, Dipak
2018-04-01
Accurate prognostic tool to identify severity of Arrhythmia is yet to be investigated, owing to the complexity of the ECG signal. In this paper, we have shown that quantitative assessment of Arrhythmia is possible using non-linear technique based on "Hurst Rescaled Range Analysis". Although the concept of applying "non-linearity" for studying various cardiac dysfunctions is not entirely new, the novel objective of this paper is to identify the severity of the disease, monitoring of different medicine and their dose, and also to assess the efficiency of different medicine. The approach presented in this work is simple which in turn will help doctors in efficient disease management. In this work, Arrhythmia ECG time series are collected from MIT-BIH database. Normal ECG time series are acquired using POLYPARA system. Both time series are analyzed in thelight of non-linear approach following the method "Rescaled Range Analysis". The quantitative parameter, "Fractal Dimension" (D) is obtained from both types of time series. The major finding is that Arrhythmia ECG poses lower values of D as compared to normal. Further, this information can be used to access the severity of Arrhythmia quantitatively, which is a new direction of prognosis as well as adequate software may be developed for the use of medical practice.
A versatile program for the calculation of linear accelerator room shielding.
Hassan, Zeinab El-Taher; Farag, Nehad M; Elshemey, Wael M
2018-03-22
This work aims at designing a computer program to calculate the necessary amount of shielding for a given or proposed linear accelerator room design in radiotherapy. The program (Shield Calculation in Radiotherapy, SCR) has been developed using Microsoft Visual Basic. It applies the treatment room shielding calculations of NCRP report no. 151 to calculate proper shielding thicknesses for a given linear accelerator treatment room design. The program is composed of six main user-friendly interfaces. The first enables the user to upload their choice of treatment room design and to measure the distances required for shielding calculations. The second interface enables the user to calculate the primary barrier thickness in case of three-dimensional conventional radiotherapy (3D-CRT), intensity modulated radiotherapy (IMRT) and total body irradiation (TBI). The third interface calculates the required secondary barrier thickness due to both scattered and leakage radiation. The fourth and fifth interfaces provide a means to calculate the photon dose equivalent for low and high energy radiation, respectively, in door and maze areas. The sixth interface enables the user to calculate the skyshine radiation for photons and neutrons. The SCR program has been successfully validated, precisely reproducing all of the calculated examples presented in NCRP report no. 151 in a simple and fast manner. Moreover, it easily performed the same calculations for a test design that was also calculated manually, and produced the same results. The program includes a new and important feature that is the ability to calculate required treatment room thickness in case of IMRT and TBI. It is characterised by simplicity, precision, data saving, printing and retrieval, in addition to providing a means for uploading and testing any proposed treatment room shielding design. The SCR program provides comprehensive, simple, fast and accurate room shielding calculations in radiotherapy.
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.
Rinkevicius, Zilvinas; Li, Xin; Sandberg, Jaime A R; Mikkelsen, Kurt V; Ågren, Hans
2014-03-11
We introduce a density functional theory/molecular mechanical approach for computation of linear response properties of molecules in heterogeneous environments, such as metal surfaces or nanoparticles embedded in solvents. The heterogeneous embedding environment, consisting from metallic and nonmetallic parts, is described by combined force fields, where conventional force fields are used for the nonmetallic part and capacitance-polarization-based force fields are used for the metallic part. The presented approach enables studies of properties and spectra of systems embedded in or placed at arbitrary shaped metallic surfaces, clusters, or nanoparticles. The capability and performance of the proposed approach is illustrated by sample calculations of optical absorption spectra of thymidine absorbed on gold surfaces in an aqueous environment, where we study how different organizations of the gold surface and how the combined, nonadditive effect of the two environments is reflected in the optical absorption spectrum.
Linear-algebraic approach to electron-molecule collisions: General formulation
International Nuclear Information System (INIS)
Collins, L.A.; Schneider, B.I.
1981-01-01
We present a linear-algebraic approach to electron-molecule collisions based on an integral equations form with either logarithmic or asymptotic boundary conditions. The introduction of exchange effects does not alter the basic form or order of the linear-algebraic equations for a local potential. In addition to the standard procedure of directly evaluating the exchange integrals by numerical quadrature, we also incorporate exchange effects through a separable-potential approximation. Efficient schemes are developed for reducing the number of points and channels that must be included. The method is applied at the static-exchange level to a number of molecular systems including H 2 , N 2 , LiH, and CO 2
Tissue characterization using electrical impedance spectroscopy data: a linear algebra approach.
Laufer, Shlomi; Solomon, Stephen B; Rubinsky, Boris
2012-06-01
In this study, we use a new linear algebra manipulation on electrical impedance spectroscopy measurements to provide real-time information regarding the nature of the tissue surrounding the needle in minimal invasive procedures. Using a Comsol Multiphysics three-dimensional model, a phantom based on ex vivo animal tissue and in vivo animal data, we demonstrate how tissue inhomogeneity can be characterized without any previous knowledge of the electrical properties of the different tissues, except that they should not be linearly dependent on a certain frequency range. This method may have applications in needle biopsies, radiation seeds, or minimally invasive surgery and can reduce the number of computer tomography or magnetic resonance imaging images. We conclude by demonstrating how this mathematical approach can be useful in other applications.
Tissue characterization using electrical impedance spectroscopy data: a linear algebra approach
International Nuclear Information System (INIS)
Laufer, Shlomi; Solomon, Stephen B; Rubinsky, Boris
2012-01-01
In this study, we use a new linear algebra manipulation on electrical impedance spectroscopy measurements to provide real-time information regarding the nature of the tissue surrounding the needle in minimal invasive procedures. Using a Comsol Multiphysics three-dimensional model, a phantom based on ex vivo animal tissue and in vivo animal data, we demonstrate how tissue inhomogeneity can be characterized without any previous knowledge of the electrical properties of the different tissues, except that they should not be linearly dependent on a certain frequency range. This method may have applications in needle biopsies, radiation seeds, or minimally invasive surgery and can reduce the number of computer tomography or magnetic resonance imaging images. We conclude by demonstrating how this mathematical approach can be useful in other applications. (paper)
The Bayes linear approach to inference and decision-making for a reliability programme
International Nuclear Information System (INIS)
Goldstein, Michael; Bedford, Tim
2007-01-01
In reliability modelling it is conventional to build sophisticated models of the probabilistic behaviour of the component lifetimes in a system in order to deduce information about the probabilistic behaviour of the system lifetime. Decision modelling of the reliability programme requires a priori, therefore, an even more sophisticated set of models in order to capture the evidence the decision maker believes may be obtained from different types of data acquisition. Bayes linear analysis is a methodology that uses expectation rather than probability as the fundamental expression of uncertainty. By working only with expected values, a simpler level of modelling is needed as compared to full probability models. In this paper we shall consider the Bayes linear approach to the estimation of a mean time to failure MTTF of a component. The model built will take account of the variance in our estimate of the MTTF, based on a variety of sources of information
Robust control of uncertain dynamic systems a linear state space approach
Yedavalli, Rama K
2014-01-01
This textbook aims to provide a clear understanding of the various tools of analysis and design for robust stability and performance of uncertain dynamic systems. In model-based control design and analysis, mathematical models can never completely represent the “real world” system that is being modeled, and thus it is imperative to incorporate and accommodate a level of uncertainty into the models. This book directly addresses these issues from a deterministic uncertainty viewpoint and focuses on the interval parameter characterization of uncertain systems. Various tools of analysis and design are presented in a consolidated manner. This volume fills a current gap in published works by explicitly addressing the subject of control of dynamic systems from linear state space framework, namely using a time-domain, matrix-theory based approach. This book also: Presents and formulates the robustness problem in a linear state space model framework Illustrates various systems level methodologies with examples and...
Linear models in matrix form a hands-on approach for the behavioral sciences
Brown, Jonathon D
2014-01-01
This textbook is an approachable introduction to statistical analysis using matrix algebra. Prior knowledge of matrix algebra is not necessary. Advanced topics are easy to follow through analyses that were performed on an open-source spreadsheet using a few built-in functions. These topics include ordinary linear regression, as well as maximum likelihood estimation, matrix decompositions, nonparametric smoothers and penalized cubic splines. Each data set (1) contains a limited number of observations to encourage readers to do the calculations themselves, and (2) tells a coherent story based on statistical significance and confidence intervals. In this way, students will learn how the numbers were generated and how they can be used to make cogent arguments about everyday matters. This textbook is designed for use in upper level undergraduate courses or first year graduate courses. The first chapter introduces students to linear equations, then covers matrix algebra, focusing on three essential operations: sum ...
Solutions to estimation problems for scalar hamilton-jacobi equations using linear programming
Claudel, Christian G.; Chamoin, Timothee; Bayen, Alexandre M.
2014-01-01
This brief presents new convex formulations for solving estimation problems in systems modeled by scalar Hamilton-Jacobi (HJ) equations. Using a semi-analytic formula, we show that the constraints resulting from a HJ equation are convex, and can be written as a set of linear inequalities. We use this fact to pose various (and seemingly unrelated) estimation problems related to traffic flow-engineering as a set of linear programs. In particular, we solve data assimilation and data reconciliation problems for estimating the state of a system when the model and measurement constraints are incompatible. We also solve traffic estimation problems, such as travel time estimation or density estimation. For all these problems, a numerical implementation is performed using experimental data from the Mobile Century experiment. In the context of reproducible research, the code and data used to compute the results presented in this brief have been posted online and are accessible to regenerate the results. © 2013 IEEE.
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.
A primal-dual exterior point algorithm for linear programming problems
Directory of Open Access Journals (Sweden)
Samaras Nikolaos
2009-01-01
Full Text Available The aim of this paper is to present a new simplex type algorithm for the Linear Programming Problem. The Primal - Dual method is a Simplex - type pivoting algorithm that generates two paths in order to converge to the optimal solution. The first path is primal feasible while the second one is dual feasible for the original problem. Specifically, we use a three-phase-implementation. The first two phases construct the required primal and dual feasible solutions, using the Primal Simplex algorithm. Finally, in the third phase the Primal - Dual algorithm is applied. Moreover, a computational study has been carried out, using randomly generated sparse optimal linear problems, to compare its computational efficiency with the Primal Simplex algorithm and also with MATLAB's Interior Point Method implementation. The algorithm appears to be very promising since it clearly shows its superiority to the Primal Simplex algorithm as well as its robustness over the IPM algorithm.
Linear differential equations to solve nonlinear mechanical problems: A novel approach
Nair, C. Radhakrishnan
2004-01-01
Often a non-linear mechanical problem is formulated as a non-linear differential equation. A new method is introduced to find out new solutions of non-linear differential equations if one of the solutions of a given non-linear differential equation is known. Using the known solution of the non-linear differential equation, linear differential equations are set up. The solutions of these linear differential equations are found using standard techniques. Then the solutions of the linear differe...
Designing a graph-based approach to landscape ecological assessment of linear infrastructures
Energy Technology Data Exchange (ETDEWEB)
Girardet, Xavier, E-mail: xavier.girardet@univ-fcomte.fr; Foltête, Jean-Christophe, E-mail: jean-christophe.foltete@univ-fcomte.fr; Clauzel, Céline, E-mail: celine.clauzel@univ-fcomte.fr
2013-09-15
The development of major linear infrastructures contributes to landscape fragmentation and impacts natural habitats and biodiversity in various ways. To anticipate and minimize such impacts, landscape planning needs to be capable of effective strategic environmental assessment (SEA) and of supporting environmental impact assessment (EIA) decisions. To this end, species distribution models (SDMs) are an effective way of making predictive maps of the presence of a given species. In this paper, we propose to combine SDMs and graph-based representation of landscape networks to integrate the potential long-distance effect of infrastructures on species distribution. A diachronic approach, comparing distribution before and after the linear infrastructure is constructed, leads to the design of a species distribution assessment (SDA), taking into account population isolation. The SDA makes it possible (1) to estimate the local variation in probability of presence and (2) to characterize the impact of the infrastructure in terms of global variation in presence and of distance of disturbance. The method is illustrated by assessing the impact of the construction of a high-speed railway line on the distribution of several virtual species in Franche-Comté (France). The study shows the capacity of the SDA to characterize the impact of a linear infrastructure either as a research concern or as a spatial planning challenge. SDAs could be helpful in deciding among several scenarios for linear infrastructure routes or for the location of mitigation measures. -- Highlights: • Graph connectivity metrics were integrated into a species distribution model. • SDM was performed before and after the implementation of linear infrastructure. • The local variation of presence provides spatial indicators of the impact.
Designing a graph-based approach to landscape ecological assessment of linear infrastructures
International Nuclear Information System (INIS)
Girardet, Xavier; Foltête, Jean-Christophe; Clauzel, Céline
2013-01-01
The development of major linear infrastructures contributes to landscape fragmentation and impacts natural habitats and biodiversity in various ways. To anticipate and minimize such impacts, landscape planning needs to be capable of effective strategic environmental assessment (SEA) and of supporting environmental impact assessment (EIA) decisions. To this end, species distribution models (SDMs) are an effective way of making predictive maps of the presence of a given species. In this paper, we propose to combine SDMs and graph-based representation of landscape networks to integrate the potential long-distance effect of infrastructures on species distribution. A diachronic approach, comparing distribution before and after the linear infrastructure is constructed, leads to the design of a species distribution assessment (SDA), taking into account population isolation. The SDA makes it possible (1) to estimate the local variation in probability of presence and (2) to characterize the impact of the infrastructure in terms of global variation in presence and of distance of disturbance. The method is illustrated by assessing the impact of the construction of a high-speed railway line on the distribution of several virtual species in Franche-Comté (France). The study shows the capacity of the SDA to characterize the impact of a linear infrastructure either as a research concern or as a spatial planning challenge. SDAs could be helpful in deciding among several scenarios for linear infrastructure routes or for the location of mitigation measures. -- Highlights: • Graph connectivity metrics were integrated into a species distribution model. • SDM was performed before and after the implementation of linear infrastructure. • The local variation of presence provides spatial indicators of the impact
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.
International Nuclear Information System (INIS)
Assmann, R.; Adolphsen, C.; Bane, K.; Raubenheimer, T.O.; Siemann, R.; Thompson, K.
1996-09-01
Linear accelerators are the central components of the proposed next generation of linear colliders. They need to provide acceleration of up to 750 GeV per beam while maintaining very small normalized emittances. Standard simulation programs, mainly developed for storage rings, do not meet the specific requirements for high energy linear accelerators. The authors present a new program LIAR (LInear Accelerator Research code) that includes wakefield effects, a 4D coupled beam description, specific optimization algorithms and other advanced features. Its modular structure allows to use and to extend it easily for different purposes. They present examples of simulations for SLC and NLC
Modified linear predictive coding approach for moving target tracking by Doppler radar
Ding, Yipeng; Lin, Xiaoyi; Sun, Ke-Hui; Xu, Xue-Mei; Liu, Xi-Yao
2016-07-01
Doppler radar is a cost-effective tool for moving target tracking, which can support a large range of civilian and military applications. A modified linear predictive coding (LPC) approach is proposed to increase the target localization accuracy of the Doppler radar. Based on the time-frequency analysis of the received echo, the proposed approach first real-time estimates the noise statistical parameters and constructs an adaptive filter to intelligently suppress the noise interference. Then, a linear predictive model is applied to extend the available data, which can help improve the resolution of the target localization result. Compared with the traditional LPC method, which empirically decides the extension data length, the proposed approach develops an error array to evaluate the prediction accuracy and thus, adjust the optimum extension data length intelligently. Finally, the prediction error array is superimposed with the predictor output to correct the prediction error. A series of experiments are conducted to illustrate the validity and performance of the proposed techniques.
Modeling the distribution of ciliate protozoa in the reticulo-rumen using linear programming.
Hook, S E; Dijkstra, J; Wright, A-D G; McBride, B W; France, J
2012-01-01
The flow of ciliate protozoa from the reticulo-rumen is significantly less than expected given the total density of rumen protozoa present. To maintain their numbers in the reticulo-rumen, protozoa can be selectively retained through association with feed particles and the rumen wall. Few mathematical models have been designed to model rumen protozoa in both the free-living and attached phases, and the data used in the models were acquired using classical techniques. It has therefore become necessary to provide an updated model that more accurately represents these microorganisms and incorporates the recent literature on distribution, sequestration, and generation times. This paper represents a novel approach to synthesizing experimental data on rumen microorganisms in a quantitative and structured manner. The development of a linear programming model of rumen protozoa in an approximate steady state will be described and applied to data from healthy ruminants consuming commonly fed diets. In the model, protozoa associated with the liquid phase and protozoa attached to particulate matter or sequestered against the rumen wall are distinguished. Growth, passage, death, and transfer of protozoa between both pools are represented. The results from the model application using the contrasting diets of increased forage content versus increased starch content indicate that the majority of rumen protozoa, 63 to 90%, are found in the attached phase, either attached to feed particles or sequestered on the rumen wall. A slightly greater proportion of protozoa are found in the attached phase in animals fed a hay diet compared with a starch diet. This suggests that experimental protocols that only sample protozoa from the rumen fluid could be significantly underestimating the size of the protozoal population of the rumen. Further data are required on the distribution of ciliate protozoa in the rumen of healthy animals to improve model development, but the model described herein
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
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.
Fabre, Anne-Claire; Cornette, Raphäel; Huyghe, Katleen; Andrade, Denis V; Herrel, Anthony
2014-09-01
Differences between the sexes may arise because of differences in reproductive strategy, with females investing more in traits related to reproductive output and males investing more in traits related to resource holding capacity and territory defence. Sexual dimorphism is widespread in lizards and in many species males and females also differ in head shape. Males typically have bigger heads than females resulting in intersexual differences in bite force. Whereas most studies documenting differences in head dimensions between sexes use linear dimensions, the use of geometric morphometrics has been advocated as more appropriate to characterize such differences. This method may allow the characterization of local shape differences that may have functional consequences, and provides unbiased indicators of shape. Here, we explore whether the two approaches provide similar results in an analyses of head shape in Tupinambis merianae. The Argentine black and white tegu differs dramatically in body size, head size, and bite force between the sexes. However, whether the intersexual differences in bite force are simply the result of differences in head size or whether more subtle modifications (e.g., in muscle insertion areas) are involved remains currently unknown. Based on the crania and mandibles of 19 lizards with known bite force, we show intersexual differences in the shape of the cranium and mandible using both linear and geometric morphometric approaches. Although both types of analyses showed generally similar results for the mandible, this was not the case for the cranium. Geometric morphometric approaches provided better insights into the underlying functional relationships between the cranium and the jaw musculature, as illustrated by shape differences in muscle insertion areas not detected using linear morphometric data. © 2014 Wiley Periodicals, Inc.
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.
Reactor Network Synthesis Using Coupled Genetic Algorithm with the Quasi-linear Programming Method
Soltani, H.; Shafiei, S.; Edraki, J.
2016-01-01
This research is an attempt to develop a new procedure for the synthesis of reactor networks (RNs) using a genetic algorithm (GA) coupled with the quasi-linear programming (LP) method. The GA is used to produce structural configuration, whereas continuous variables are handled using a quasi-LP formulation for finding the best objective function. Quasi-LP consists of LP together with a search loop to find the best reactor conversions (xi), as well as split and recycle ratios (yi). Quasi-LP rep...
Quadratic-linear pattern in cancer fractional radiotherapy. Equations for a computering program
International Nuclear Information System (INIS)
Burgos, D.; Bullejos, J.; Garcia Puche, J.L.; Pedraza, V.
1990-01-01
Knowledge of equivalence between different tratment schemes with the same iso-effect is the essential thing in clinical cancer radiotherapy. For this purpose it is very useful the group of ideas derived from quadratic-linear pattern (Q-L) proposed in order to analyze cell survival curve to radiation. Iso-effect definition caused by several irradiation rules is done by extrapolated tolerance dose (ETD). Because equations for ETD are complex, a computering program have been carried out. In this paper, iso-effect equations for well defined therapeutic situations and flow diagram proposed for resolution, have been studied. (Author)
International Nuclear Information System (INIS)
Sun Wei; Huang, Guo H.; Lv Ying; Li Gongchen
2012-01-01
Highlights: ► Inexact piecewise-linearization-based fuzzy flexible programming is proposed. ► It’s the first application to waste management under multiple complexities. ► It tackles nonlinear economies-of-scale effects in interval-parameter constraints. ► It estimates costs more accurately than the linear-regression-based model. ► Uncertainties are decreased and more satisfactory interval solutions are obtained. - Abstract: To tackle nonlinear economies-of-scale (EOS) effects in interval-parameter constraints for a representative waste management problem, an inexact piecewise-linearization-based fuzzy flexible programming (IPFP) model is developed. In IPFP, interval parameters for waste amounts and transportation/operation costs can be quantified; aspiration levels for net system costs, as well as tolerance intervals for both capacities of waste treatment facilities and waste generation rates can be reflected; and the nonlinear EOS effects transformed from objective function to constraints can be approximated. An interactive algorithm is proposed for solving the IPFP model, which in nature is an interval-parameter mixed-integer quadratically constrained programming model. To demonstrate the IPFP’s advantages, two alternative models are developed to compare their performances. One is a conventional linear-regression-based inexact fuzzy programming model (IPFP2) and the other is an IPFP model with all right-hand-sides of fussy constraints being the corresponding interval numbers (IPFP3). The comparison results between IPFP and IPFP2 indicate that the optimized waste amounts would have the similar patterns in both models. However, when dealing with EOS effects in constraints, the IPFP2 may underestimate the net system costs while the IPFP can estimate the costs more accurately. The comparison results between IPFP and IPFP3 indicate that their solutions would be significantly different. The decreased system uncertainties in IPFP’s solutions demonstrate
Directory of Open Access Journals (Sweden)
Darunee Hunwisai
2017-01-01
Full Text Available In this work, we considered two-person zero-sum games with fuzzy payoffs and matrix games with payoffs of trapezoidal intuitionistic fuzzy numbers (TrIFNs. The concepts of TrIFNs and their arithmetic operations were used. The cut-set based method for matrix game with payoffs of TrIFNs was also considered. Compute the interval-type value of any alfa-constrategies by simplex method for linear programming. The proposed method is illustrated with a numerical example.
International Nuclear Information System (INIS)
Kato, K.; Ihara, S.
1993-01-01
Hydrogen is expected to be an important energy carrier, especially in the frame of global warming problem solution. The purpose of this study is to examine the condition of market penetration of hydrogen technologies in reducing CO 2 emissions. A multi-time-period linear programming model (MARKAL, Market Allocation)) is used to explore technology options and cost for meeting the energy demands while reducing CO 2 emissions from energy systems. The results show that hydrogen technologies become economical when CO 2 emissions are stringently constrained. 9 figs., 2 refs
The evaluation of multi-element personal dosemeters using the linear programming method
International Nuclear Information System (INIS)
Kragh, P.; Ambrosi, P.; Boehm, J.; Hilgers, G.
1996-01-01
Multi-element dosemeters are frequently used in individual monitoring. Each element can be regarded as an individual dosemeter with its own individual dose measurement value. In general, the individual dose values of one dosemeter vary according to the exposure conditions, i. e. the energy and angle of incidence of the radiation. The (final) dose measurement value of the personal dosemeter is calculated from the individual dose values by means of an evaluation algorithm. The best possible dose value, i.e. that of the smallest systematic (type B) uncertainty if the exposure conditions are changed in the dosemeter's rated range of use, is obtained by the method of linear programming. (author)
Energy Technology Data Exchange (ETDEWEB)
Dufour, F., E-mail: dufour@math.u-bordeaux1.fr [Institut de Mathématiques de Bordeaux, INRIA Bordeaux Sud Ouest, Team: CQFD, and IMB (France); Prieto-Rumeau, T., E-mail: tprieto@ccia.uned.es [UNED, Department of Statistics and Operations Research (Spain)
2016-08-15
We consider a discrete-time constrained discounted Markov decision process (MDP) with Borel state and action spaces, compact action sets, and lower semi-continuous cost functions. We introduce a set of hypotheses related to a positive weight function which allow us to consider cost functions that might not be bounded below by a constant, and which imply the solvability of the linear programming formulation of the constrained MDP. In particular, we establish the existence of a constrained optimal stationary policy. Our results are illustrated with an application to a fishery management problem.
International Nuclear Information System (INIS)
Collins, L.A.; Schneider, B.I.
1984-01-01
The linear algebraic, separable potential approach is applied to the electronic excitation of atoms and molecules by electron impact. By representing the exchange and off-diagonal direct terms on a basis, the standard set of coupled inelastic equations is reduced to a set of elastic inhomogeneous equations. The procedure greatly simplifies the formulation by allowing a large portion of the problem to be handled by standard bound-state techniques and by greatly reducing the order of the scattering equations that must be solved. Application is made to the excitation of atomic hydrogen in the three-state close-coupling (1s, 2s, 2p) approximation. (author)
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.
An MDE Approach for Modular Program Analyses
Yildiz, Bugra Mehmet; Bockisch, Christoph; Aksit, Mehmet; Rensink, Arend
Program analyses are an important tool to check if a system fulfills its specification. A typical implementation strategy for program analyses is to use an imperative, general-purpose language like Java, and access the program to be analyzed through libraries that offer an API for reading, writing
Cognitive agent programming : A semantic approach
Riemsdijk, M.B. van
2006-01-01
In this thesis we are concerned with the design and investigation of dedicated programming languages for programming agents. We focus in particular on programming languages for rational agents, i.e., flexibly behaving computing entities that are able to make "good" decisions about what to do. An
Eid, Chaker; Millham, Richard
2012-01-01
In this paper, we discuss the visual programming approach to teaching introductory programming courses and then compare this approach with that of procedural programming. The involved cognitive levels of students, as beginning students are introduced to different types of programming concepts, are correlated to the learning processes of…
Mixed H∞ and passive control for linear switched systems via hybrid control approach
Zheng, Qunxian; Ling, Youzhu; Wei, Lisheng; Zhang, Hongbin
2018-03-01
This paper investigates the mixed H∞ and passive control problem for linear switched systems based on a hybrid control strategy. To solve this problem, first, a new performance index is proposed. This performance index can be viewed as the mixed weighted H∞ and passivity performance. Then, the hybrid controllers are used to stabilise the switched systems. The hybrid controllers consist of dynamic output-feedback controllers for every subsystem and state updating controllers at the switching instant. The design of state updating controllers not only depends on the pre-switching subsystem and the post-switching subsystem, but also depends on the measurable output signal. The hybrid controllers proposed in this paper can include some existing ones as special cases. Combine the multiple Lyapunov functions approach with the average dwell time technique, new sufficient conditions are obtained. Under the new conditions, the closed-loop linear switched systems are globally uniformly asymptotically stable with a mixed H∞ and passivity performance index. Moreover, the desired hybrid controllers can be constructed by solving a set of linear matrix inequalities. Finally, a numerical example and a practical example are given.
DEFF Research Database (Denmark)
Parlesak, A.; Tetens, Inge; Dejgård Jensen, Jørgen
2016-01-01
programming. The FBs were defined using five different constraints: cultural acceptability (CA), or dietary guidelines (DG), or nutrient recommendations (N), or cultural acceptability and nutrient recommendations (CAN), or dietary guidelines and nutrient recommendations (DGN). The variety and number of foods...... in each of the resulting five baskets was increased through limiting the relative share of individual foods. The one-day version of N contained only 12 foods at the minimum cost of DKK 27 (€ 3.6). The CA, DG, and DGN were about twice of this and the CAN cost ~DKK 81 (€ 10.8). The baskets with the greater...... variety of foods contained from 70 (CAN) to 134 (DGN) foods and cost between DKK 60 (€ 8.1, N) and DKK 125 (€ 16.8, DGN). Ensuring that the food baskets cover both dietary guidelines and nutrient recommendations doubled the cost while cultural acceptability (CAN) tripled it. Use of linear programming...
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.
Stochastic Fractional Programming Approach to a Mean and Variance Model of a Transportation Problem
Directory of Open Access Journals (Sweden)
V. Charles
2011-01-01
Full Text Available In this paper, we propose a stochastic programming model, which considers a ratio of two nonlinear functions and probabilistic constraints. In the former, only expected model has been proposed without caring variability in the model. On the other hand, in the variance model, the variability played a vital role without concerning its counterpart, namely, the expected model. Further, the expected model optimizes the ratio of two linear cost functions where as variance model optimize the ratio of two non-linear functions, that is, the stochastic nature in the denominator and numerator and considering expectation and variability as well leads to a non-linear fractional program. In this paper, a transportation model with stochastic fractional programming (SFP problem approach is proposed, which strikes the balance between previous models available in the literature.
Directory of Open Access Journals (Sweden)
Nurdan Cetin
2014-01-01
Full Text Available We consider a multiobjective linear fractional transportation problem (MLFTP with several fractional criteria, such as, the maximization of the transport profitability like profit/cost or profit/time, and its two properties are source and destination. Our aim is to introduce MLFTP which has not been studied in literature before and to provide a fuzzy approach which obtain a compromise Pareto-optimal solution for this problem. To do this, first, we present a theorem which shows that MLFTP is always solvable. And then, reducing MLFTP to the Zimmermann’s “min” operator model which is the max-min problem, we construct Generalized Dinkelbach’s Algorithm for solving the obtained problem. Furthermore, we provide an illustrative numerical example to explain this fuzzy approach.
Marzban, Hamid Reza
2018-05-01
In this paper, we are concerned with the parameter identification of linear time-invariant systems containing multiple delays. The approach is based upon a hybrid of block-pulse functions and Legendre's polynomials. The convergence of the proposed procedure is established and an upper error bound with respect to the L2-norm associated with the hybrid functions is derived. The problem under consideration is first transformed into a system of algebraic equations. The least squares technique is then employed for identification of the desired parameters. Several multi-delay systems of varying complexity are investigated to evaluate the performance and capability of the proposed approximation method. It is shown that the proposed approach is also applicable to a class of nonlinear multi-delay systems. It is demonstrated that the suggested procedure provides accurate results for the desired parameters.
A mathematical programming approach for sequential clustering of dynamic networks
Silva, Jonathan C.; Bennett, Laura; Papageorgiou, Lazaros G.; Tsoka, Sophia
2016-02-01
A common analysis performed on dynamic networks is community structure detection, a challenging problem that aims to track the temporal evolution of network modules. An emerging area in this field is evolutionary clustering, where the community structure of a network snapshot is identified by taking into account both its current state as well as previous time points. Based on this concept, we have developed a mixed integer non-linear programming (MINLP) model, SeqMod, that sequentially clusters each snapshot of a dynamic network. The modularity metric is used to determine the quality of community structure of the current snapshot and the historical cost is accounted for by optimising the number of node pairs co-clustered at the previous time point that remain so in the current snapshot partition. Our method is tested on social networks of interactions among high school students, college students and members of the Brazilian Congress. We show that, for an adequate parameter setting, our algorithm detects the classes that these students belong more accurately than partitioning each time step individually or by partitioning the aggregated snapshots. Our method also detects drastic discontinuities in interaction patterns across network snapshots. Finally, we present comparative results with similar community detection methods for time-dependent networks from the literature. Overall, we illustrate the applicability of mathematical programming as a flexible, adaptable and systematic approach for these community detection problems. Contribution to the Topical Issue "Temporal Network Theory and Applications", edited by Petter Holme.
Averaging and Linear Programming in Some Singularly Perturbed Problems of Optimal Control
Energy Technology Data Exchange (ETDEWEB)
Gaitsgory, Vladimir, E-mail: vladimir.gaitsgory@mq.edu.au [Macquarie University, Department of Mathematics (Australia); Rossomakhine, Sergey, E-mail: serguei.rossomakhine@flinders.edu.au [Flinders University, Flinders Mathematical Sciences Laboratory, School of Computer Science, Engineering and Mathematics (Australia)
2015-04-15
The paper aims at the development of an apparatus for analysis and construction of near optimal solutions of singularly perturbed (SP) optimal controls problems (that is, problems of optimal control of SP systems) considered on the infinite time horizon. We mostly focus on problems with time discounting criteria but a possibility of the extension of results to periodic optimization problems is discussed as well. Our consideration is based on earlier results on averaging of SP control systems and on linear programming formulations of optimal control problems. The idea that we exploit is to first asymptotically approximate a given problem of optimal control of the SP system by a certain averaged optimal control problem, then reformulate this averaged problem as an infinite-dimensional linear programming (LP) problem, and then approximate the latter by semi-infinite LP problems. We show that the optimal solution of these semi-infinite LP problems and their duals (that can be found with the help of a modification of an available LP software) allow one to construct near optimal controls of the SP system. We demonstrate the construction with two numerical examples.
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.
International Nuclear Information System (INIS)
Shimizu, Yoshiaki
1988-01-01
Due to the simplicity and effectiveness, linear program has been popular in the actual optimization in various fields. In the previous study, the uncertainty involved in the model at the different stage of optimization was dealt with by post-optimizing analysis. But it often becomes insufficient to make a decision how to deal with an uncertain system especially suffering large parameter deviation. Recently in the field of processing systems, it is desired to obtain a flexible solution which can present the counterplan to a deviating system from a practical viewpoint. The scope of this preliminary note presents how to apply a methodology development to obtain the flexible solution of a linear program. For this purpose, a simple example associated with nuclear reactor decommissioning is shown. The problem to maximize a system performance given as an objective function under the constraint of the static behavior of the system is considered, and the flexible solution is determined. In Japan, the decommissioning of commercial nuclear power plants will being in near future, and the study using the retired research reactor JPDR is in progress. The planning of decontamination and the reuse of wastes is taken as the example. (Kako, I.)
Li, Yanning; Canepa, Edward S.; Claudel, Christian G.
2013-01-01
This article presents a new robust control framework for transportation problems in which the state is modeled by a first order scalar conservation law. Using an equivalent formulation based on a Hamilton-Jacobi equation, we pose the problem of controlling the state of the system on a network link, using boundary flow control, as a Linear Program. Unlike many previously investigated transportation control schemes, this method yields a globally optimal solution and is capable of handling shocks (i.e. discontinuities in the state of the system). We also demonstrate that the same framework can handle robust control problems, in which the uncontrollable components of the initial and boundary conditions are encoded in intervals on the right hand side of inequalities in the linear program. The lower bound of the interval which defines the smallest feasible solution set is used to solve the robust LP (or MILP if the objective function depends on boolean variables). Since this framework leverages the intrinsic properties of the Hamilton-Jacobi equation used to model the state of the system, it is extremely fast. Several examples are given to demonstrate the performance of the robust control solution and the trade-off between the robustness and the optimality. © 2013 IEEE.
International Nuclear Information System (INIS)
Shimizu, Yoshiaki
1991-01-01
In recent complicated nuclear systems, there are increasing demands for developing highly advanced procedures for various problems-solvings. Among them keen interests have been paid on man-machine communications to improve both safety and economy factors. Many optimization methods have been good enough to elaborate on these points. In this preliminary note, we will concern with application of linear programming (LP) for this purpose. First we will present a new superior version of the generalized PAPA method (GEPAPA) to solve LP problems. We will then examine its effectiveness when applied to derive dynamic matrix control (DMC) as the LP solution. The approach is to aim at the above goal through a quality control of process that will appear in the system. (author)
Electric generating capacity planning: A nonlinear programming approach
Energy Technology Data Exchange (ETDEWEB)
Yakin, M.Z.; McFarland, J.W.
1987-02-01
This paper presents a nonlinear programming approach for long-range generating capacity expansion planning in electrical power systems. The objective in the model is the minimization of total cost consisting of investment cost plus generation cost for a multi-year planning horizon. Reliability constraints are imposed by using standard and practical reserve margin requirements. State equations representing the dynamic aspect of the problem are included. The electricity demand (load) and plant availabilities are treated as random variables, and the method of cumulants is used to calculate the expected energy generated by each plant in each year of the planning horizon. The resulting model has a (highly) nonlinear objective function and linear constraints. The planning model is solved over the multiyear planning horizon instead of decomposing it into one-year period problems. This approach helps the utility decision maker to carry out extensive sensitivity analysis easily. A case study example is provided using EPRI test data. Relationships among the reserve margin, total cost and surplus energy generating capacity over the planning horizon are explored by analyzing the model.
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…
Towards Automated Binding Affinity Prediction Using an Iterative Linear Interaction Energy Approach
Directory of Open Access Journals (Sweden)
C. Ruben Vosmeer
2014-01-01
Full Text Available Binding affinity prediction of potential drugs to target and off-target proteins is an essential asset in drug development. These predictions require the calculation of binding free energies. In such calculations, it is a major challenge to properly account for both the dynamic nature of the protein and the possible variety of ligand-binding orientations, while keeping computational costs tractable. Recently, an iterative Linear Interaction Energy (LIE approach was introduced, in which results from multiple simulations of a protein-ligand complex are combined into a single binding free energy using a Boltzmann weighting-based scheme. This method was shown to reach experimental accuracy for flexible proteins while retaining the computational efficiency of the general LIE approach. Here, we show that the iterative LIE approach can be used to predict binding affinities in an automated way. A workflow was designed using preselected protein conformations, automated ligand docking and clustering, and a (semi-automated molecular dynamics simulation setup. We show that using this workflow, binding affinities of aryloxypropanolamines to the malleable Cytochrome P450 2D6 enzyme can be predicted without a priori knowledge of dominant protein-ligand conformations. In addition, we provide an outlook for an approach to assess the quality of the LIE predictions, based on simulation outcomes only.
A Novel Approach for Collaborative Pair Programming
Goel, Sanjay; Kathuria, Vanshi
2010-01-01
The majority of an engineer's time in the software industry is spent working with other programmers. Agile methods of software development like eXtreme Programming strongly rely upon practices like daily meetings and pair programming. Hence, the need to learn the skill of working collaboratively is of primary importance for software developers.…
International Nuclear Information System (INIS)
Fernandes, Marco A.R.; Fernandes, David M.; Florentino, Helenice O.
2010-01-01
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)
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.
DEFF Research Database (Denmark)
Sokoler, Leo Emil; Frison, Gianluca; Skajaa, Anders
2015-01-01
We develop an efficient homogeneous and self-dual interior-point method (IPM) for the linear programs arising in economic model predictive control of constrained linear systems with linear objective functions. The algorithm is based on a Riccati iteration procedure, which is adapted to the linear...... system of equations solved in homogeneous and self-dual IPMs. Fast convergence is further achieved using a warm-start strategy. We implement the algorithm in MATLAB and C. Its performance is tested using a conceptual power management case study. Closed loop simulations show that 1) the proposed algorithm...
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.
Performance improvement of shunt active power filter based on non-linear least-square approach
DEFF Research Database (Denmark)
Terriche, Yacine
2018-01-01
Nowadays, the shunt active power filters (SAPFs) have become a popular solution for power quality issues. A crucial issue in controlling the SAPFs which is highly correlated with their accuracy, flexibility and dynamic behavior, is generating the reference compensating current (RCC). The synchron......Nowadays, the shunt active power filters (SAPFs) have become a popular solution for power quality issues. A crucial issue in controlling the SAPFs which is highly correlated with their accuracy, flexibility and dynamic behavior, is generating the reference compensating current (RCC......). The synchronous reference frame (SRF) approach is widely used for generating the RCC due to its simplicity and computation efficiency. However, the SRF approach needs precise information of the voltage phase which becomes a challenge under adverse grid conditions. A typical solution to answer this need....... This paper proposes an improved open loop strategy which is unconditionally stable and flexible. The proposed method which is based on non-linear least square (NLS) approach can extract the fundamental voltage and estimates its phase within only half cycle, even in the presence of odd harmonics and dc offset...
DEFF Research Database (Denmark)
Kiani, Alishir; Chwalibog, André; Nielsen, Mette O
2007-01-01
Late gestation energy expenditure (EE(gest)) originates from energy expenditure (EE) of development of conceptus (EE(conceptus)) and EE of homeorhetic adaptation of metabolism (EE(homeorhetic)). Even though EE(gest) is relatively easy to quantify, its partitioning is problematic. In the present...... study metabolizable energy (ME) intake ranges for twin-bearing ewes were 220-440, 350- 700, 350-900 kJ per metabolic body weight (W0.75) at week seven, five, two pre-partum respectively. Indirect calorimetry and a linear regression approach were used to quantify EE(gest) and then partition to EE......(conceptus) and EE(homeorhetic). Energy expenditure of basal metabolism of the non-gravid tissues (EE(bmng)), derived from the intercept of the linear regression equation of retained energy [kJ/W0.75] and ME intake [kJ/W(0.75)], was 298 [kJ/ W0.75]. Values of the intercepts of the regression equations at week seven...
Macroscopic QED in linearly responding media and a Lorentz-Force approach to dispersion forces
Energy Technology Data Exchange (ETDEWEB)
Raabe, Christian
2008-07-08
In this thesis, a very general quantization scheme for the macroscopic electromagnetic field in arbitrary linearly responding media is presented. It offers a unified approach to QED in such media. Applying the quantization scheme, a theory of the dispersion forces on the basis of the Lorentz force is developed. By regarding the dispersion force as the (ground-state or thermal-state) expectation value of the Lorentz force that acts on appropriately defined charge and current densities, Casimir, Casimir-Polder, and van der Waals forces are united in a very natural way that makes transparent their common physical basis. Application of the theory to planar structures yields generalizations of well-known Lifschitz and Casimir-type formulas. (orig.)
Molenaar, Dylan; Tuerlinckx, Francis; van der Maas, Han L J
2015-05-01
We show how the hierarchical model for responses and response times as developed by van der Linden (2007), Fox, Klein Entink, and van der Linden (2007), Klein Entink, Fox, and van der Linden (2009), and Glas and van der Linden (2010) can be simplified to a generalized linear factor model with only the mild restriction that there is no hierarchical model at the item side. This result is valuable as it enables all well-developed modelling tools and extensions that come with these methods. We show that the restriction we impose on the hierarchical model does not influence parameter recovery under realistic circumstances. In addition, we present two illustrative real data analyses to demonstrate the practical benefits of our approach. © 2014 The British Psychological Society.
International Nuclear Information System (INIS)
Balasubramaniam, P.; Kalpana, M.; Rakkiyappan, R.
2012-01-01
Fuzzy cellular neural networks (FCNNs) are special kinds of cellular neural networks (CNNs). Each cell in an FCNN contains fuzzy operating abilities. The entire network is governed by cellular computing laws. The design of FCNNs is based on fuzzy local rules. In this paper, a linear matrix inequality (LMI) approach for synchronization control of FCNNs with mixed delays is investigated. Mixed delays include discrete time-varying delays and unbounded distributed delays. A dynamic control scheme is proposed to achieve the synchronization between a drive network and a response network. By constructing the Lyapunov—Krasovskii functional which contains a triple-integral term and the free-weighting matrices method an improved delay-dependent stability criterion is derived in terms of LMIs. The controller can be easily obtained by solving the derived LMIs. A numerical example and its simulations are presented to illustrate the effectiveness of the proposed method. (interdisciplinary physics and related areas of science and technology)
Dib, Julián R.; Wagenknecht, Martin; Farías, María E.; Meinhardt, Friedhelm
2015-01-01
The term plasmid was originally coined for circular, extrachromosomal genetic elements. Today, plasmids are widely recognized not only as important factors facilitating genome restructuring but also as vehicles for the dissemination of beneficial characters within bacterial communities. Plasmid diversity has been uncovered by means of culture-dependent or -independent approaches, such as endogenous or exogenous plasmid isolation as well as PCR-based detection or transposon-aided capture, respectively. High-throughput-sequencing made possible to cover total plasmid populations in a given environment, i.e., the plasmidome, and allowed to address the quality and significance of self-replicating genetic elements. Since such efforts were and still are rather restricted to circular molecules, here we put equal emphasis on the linear plasmids which—despite their frequent occurrence in a large number of bacteria—are largely neglected in prevalent plasmidome conceptions. PMID:26074886
Quantum dynamics of a vibronically coupled linear chain using a surrogate Hamiltonian approach
Energy Technology Data Exchange (ETDEWEB)
Lee, Myeong H., E-mail: myeong.lee@warwick.ac.uk; Troisi, Alessandro [Department of Chemistry and Centre for Scientific Computing, University of Warwick, Coventry CV4 7AL (United Kingdom)
2016-06-07
Vibronic coupling between the electronic and vibrational degrees of freedom has been reported to play an important role in charge and exciton transport in organic photovoltaic materials, molecular aggregates, and light-harvesting complexes. Explicitly accounting for effective vibrational modes rather than treating them as a thermal environment has been shown to be crucial to describe the effect of vibronic coupling. We present a methodology to study dissipative quantum dynamics of vibronically coupled systems based on a surrogate Hamiltonian approach, which is in principle not limited by Markov approximation or weak system-bath interaction, using a vibronic basis. We apply vibronic surrogate Hamiltonian method to a linear chain system and discuss how different types of relaxation process, intramolecular vibrational relaxation and intermolecular vibronic relaxation, influence population dynamics of dissipative vibronic systems.
Macroscopic QED in linearly responding media and a Lorentz-Force approach to dispersion forces
International Nuclear Information System (INIS)
Raabe, Christian
2008-01-01
In this thesis, a very general quantization scheme for the macroscopic electromagnetic field in arbitrary linearly responding media is presented. It offers a unified approach to QED in such media. Applying the quantization scheme, a theory of the dispersion forces on the basis of the Lorentz force is developed. By regarding the dispersion force as the (ground-state or thermal-state) expectation value of the Lorentz force that acts on appropriately defined charge and current densities, Casimir, Casimir-Polder, and van der Waals forces are united in a very natural way that makes transparent their common physical basis. Application of the theory to planar structures yields generalizations of well-known Lifschitz and Casimir-type formulas. (orig.)
International Nuclear Information System (INIS)
De Donato, O.; Parisi, M.A.
1977-01-01
When loads increase proportionally beyond the elastic limit in the presence of elastic-plastic piecewise-linear constitutive laws, the problem of finding the whole evolution of the plastic strain and displacements of structures was recently shown to be amenable to a parametric linear complementary problem (PLCP) in which the parameter is represented by the load factor, the matrix is symmetric positive definite or at least semi-definite (for perfect plasticity) and the variables with a direct mechanical meaning are the plastic multipliers. With reference to plane trusses and frames with elastic-plastic linear work-hardening material behaviour numerical solutions were also fairly efficiently obtained using a recent mathematical programming algorithm (due to R.W. Cottle) which is able to provide the whole deformation history of the structure and, at the same time to rule out local unloadings along the given proportional loading process by means of 'a priori' checks carried out before each pivotal step of the procedure. Hence it becomes possible to use the holonomic (reversible, path-independent) constitutive laws in finite terms and to benefit by all the relevant numerical and computational advantages despite the non-holonomic nature of plastic behaviour. In the present paper the method of solution is re-examined in view to overcome an important drawback of the algorithm deriving from the size of PLCP fully populated matrix when structural problems with large number of variables are considered and, consequently, the updating, the storing or, generally, the handling of the current tableau may become prohibitive. (Auth.)
Linear programming optimization of nuclear energy strategy with sodium-cooled fast reactors
International Nuclear Information System (INIS)
Lee, Je Whan; Jeong, Yong Hoon; Chang, Yoon Il; Chang, Soon Heung
2011-01-01
Nuclear power has become an essential part of electricity generation to meet the continuous growth of electricity demand. A Sodium-cooled Fast Reactor (SFR) was developed to extend uranium resource utilization under a growing nuclear energy scenario while concomitantly providing a nuclear waste management solution. Key questions in this scenario are when to introduce SFRs and how many reactors should be introduced. In this study, a methodology using Linear Programming is employed in order to quantify an optimized growth pattern of a nuclear energy system comprising light water reactors and SFRs. The optimization involves tradeoffs between SFR capital cost premiums and the total system U3O8 price premiums. Optimum nuclear growth patterns for several scenarios are presented, as well as sensitivity analyses of important input parameters
A linear goal programming model for urban energy-economy-environment interaction
Energy Technology Data Exchange (ETDEWEB)
Kambo, N.S.; Handa, B.R. (Indian Inst. of Tech., New Delhi (India). Dept. of Mathematics); Bose, R.K. (Tata Energy Research Inst., New Delhi (India))
1991-01-01
This paper provides a comprehensive and systematic analysis of energy and pollution problems interconnected with the economic structure, by using a multi-objective sectoral end-use model for addressing regional energy policy issues. The multi-objective model proposed for the study is a 'linear goal programming (LGP)' technique of analysing a 'reference energy system (RES)' in a framework within which alternative policies and technical strategies may be evaluated. The model so developed has further been tested for the city of Delhi (India) for the period 1985 - 86, and a scenario analysis has been carried out by assuming different policy options. (orig./BWJ).
Approximating high-dimensional dynamics by barycentric coordinates with linear programming
Energy Technology Data Exchange (ETDEWEB)
Hirata, Yoshito, E-mail: yoshito@sat.t.u-tokyo.ac.jp; Aihara, Kazuyuki; Suzuki, Hideyuki [Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505 (Japan); Department of Mathematical Informatics, The University of Tokyo, Bunkyo-ku, Tokyo 113-8656 (Japan); CREST, JST, 4-1-8 Honcho, Kawaguchi, Saitama 332-0012 (Japan); Shiro, Masanori [Department of Mathematical Informatics, The University of Tokyo, Bunkyo-ku, Tokyo 113-8656 (Japan); Mathematical Neuroinformatics Group, Advanced Industrial Science and Technology, Tsukuba, Ibaraki 305-8568 (Japan); Takahashi, Nozomu; Mas, Paloma [Center for Research in Agricultural Genomics (CRAG), Consorci CSIC-IRTA-UAB-UB, Barcelona 08193 (Spain)
2015-01-15
The increasing development of novel methods and techniques facilitates the measurement of high-dimensional time series but challenges our ability for accurate modeling and predictions. The use of a general mathematical model requires the inclusion of many parameters, which are difficult to be fitted for relatively short high-dimensional time series observed. Here, we propose a novel method to accurately model a high-dimensional time series. Our method extends the barycentric coordinates to high-dimensional phase space by employing linear programming, and allowing the approximation errors explicitly. The extension helps to produce free-running time-series predictions that preserve typical topological, dynamical, and/or geometric characteristics of the underlying attractors more accurately than the radial basis function model that is widely used. The method can be broadly applied, from helping to improve weather forecasting, to creating electronic instruments that sound more natural, and to comprehensively understanding complex biological data.
Highlights of the SLD Physics Program at the SLAC Linear Collider
International Nuclear Information System (INIS)
Willocq, Stephane
2001-01-01
Starting in 1989, and continuing through the 1990s, high-energy physics witnessed a flowering of precision measurements in general and tests of the standard model in particular, led by e + e - collider experiments operating at the Z 0 resonance. Key contributions to this work came from the SLD collaboration at the SLAC Linear Collider. By exploiting the unique capabilities of this pioneering accelerator and the SLD detector, including a polarized electron beam, exceptionally small beam dimensions, and a CCD pixel vertex detector, SLD produced a broad array of electroweak, heavy-flavor, and QCD measurements. Many of these results are one of a kind or represent the world's standard in precision. This article reviews the highlights of the SLD physics program, with an eye toward associated advances in experimental technique, and the contribution of these measurements to our dramatically improved present understanding of the standard model and its possible extensions
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.