A Mixed Integer Programming Poultry Feed Ration Optimisation Problem Using the Bat Algorithm

Directory of Open Access Journals (Sweden)

Godfrey Chagwiza

2016-01-01

Full Text Available In this paper, a feed ration problem is presented as a mixed integer programming problem. An attempt to find the optimal quantities of Moringa oleifera inclusion into the poultry feed ration was done and the problem was solved using the Bat algorithm and the Cplex solver. The study used findings of previous research to investigate the effects of Moringa oleifera inclusion in poultry feed ration. The results show that the farmer is likely to gain US$0.89 more if Moringa oleifera is included in the feed ration. Results also show superiority of the Bat algorithm in terms of execution time and number of iterations required to find the optimum solution as compared with the results obtained by the Cplex solver. Results revealed that there is a significant economic benefit of Moringa oleifera inclusion into the poultry feed ration.

Polynomial selection in number field sieve for integer factorization

Directory of Open Access Journals (Sweden)

Gireesh Pandey

2016-09-01

Full Text Available The general number field sieve (GNFS is the fastest algorithm for factoring large composite integers which is made up by two prime numbers. Polynomial selection is an important step of GNFS. The asymptotic runtime depends on choice of good polynomial pairs. In this paper, we present polynomial selection algorithm that will be modelled with size and root properties. The correlations between polynomial coefficient and number of relations have been explored with experimental findings.

A wavelet-based ECG delineation algorithm for 32-bit integer online processing.

Science.gov (United States)

Di Marco, Luigi Y; Chiari, Lorenzo

2011-04-03

Since the first well-known electrocardiogram (ECG) delineator based on Wavelet Transform (WT) presented by Li et al. in 1995, a significant research effort has been devoted to the exploitation of this promising method. Its ability to reliably delineate the major waveform components (mono- or bi-phasic P wave, QRS, and mono- or bi-phasic T wave) would make it a suitable candidate for efficient online processing of ambulatory ECG signals. Unfortunately, previous implementations of this method adopt non-linear operators such as root mean square (RMS) or floating point algebra, which are computationally demanding. This paper presents a 32-bit integer, linear algebra advanced approach to online QRS detection and P-QRS-T waves delineation of a single lead ECG signal, based on WT. The QRS detector performance was validated on the MIT-BIH Arrhythmia Database (sensitivity Se = 99.77%, positive predictive value P+ = 99.86%, on 109010 annotated beats) and on the European ST-T Database (Se = 99.81%, P+ = 99.56%, on 788050 annotated beats). The ECG delineator was validated on the QT Database, showing a mean error between manual and automatic annotation below 1.5 samples for all fiducial points: P-onset, P-peak, P-offset, QRS-onset, QRS-offset, T-peak, T-offset, and a mean standard deviation comparable to other established methods. The proposed algorithm exhibits reliable QRS detection as well as accurate ECG delineation, in spite of a simple structure built on integer linear algebra.

Computer Corner: Spreadsheets, Power Series, Generating Functions, and Integers.

Science.gov (United States)

Snow, Donald R.

1989-01-01

Implements a table algorithm on a spreadsheet program and obtains functions for several number sequences such as the Fibonacci and Catalan numbers. Considers other applications of the table algorithm to integers represented in various number bases. (YP)

PageRank of integers

International Nuclear Information System (INIS)

Frahm, K M; Shepelyansky, D L; Chepelianskii, A D

2012-01-01

We up a directed network tracing links from a given integer to its divisors and analyze the properties of the Google matrix of this network. The PageRank vector of this matrix is computed numerically and it is shown that its probability is approximately inversely proportional to the PageRank index thus being similar to the Zipf law and the dependence established for the World Wide Web. The spectrum of the Google matrix of integers is characterized by a large gap and a relatively small number of nonzero eigenvalues. A simple semi-analytical expression for the PageRank of integers is derived that allows us to find this vector for matrices of billion size. This network provides a new PageRank order of integers. (paper)

A Generalized National Planning Approach for Admission Capacity in Higher Education: A Nonlinear Integer Goal Programming Model with a Novel Differential Evolution Algorithm.

Science.gov (United States)

El-Qulity, Said Ali; Mohamed, Ali Wagdy

2016-01-01

This paper proposes a nonlinear integer goal programming model (NIGPM) for solving the general problem of admission capacity planning in a country as a whole. The work aims to satisfy most of the required key objectives of a country related to the enrollment problem for higher education. The system general outlines are developed along with the solution methodology for application to the time horizon in a given plan. The up-to-date data for Saudi Arabia is used as a case study and a novel evolutionary algorithm based on modified differential evolution (DE) algorithm is used to solve the complexity of the NIGPM generated for different goal priorities. The experimental results presented in this paper show their effectiveness in solving the admission capacity for higher education in terms of final solution quality and robustness.

Genetic Algorithm for Mixed Integer Nonlinear Bilevel Programming and Applications in Product Family Design

Directory of Open Access Journals (Sweden)

Chenlu Miao

2016-01-01

Full Text Available Many leader-follower relationships exist in product family design engineering problems. We use bilevel programming (BLP to reflect the leader-follower relationship and describe such problems. Product family design problems have unique characteristics; thus, mixed integer nonlinear BLP (MINLBLP, which has both continuous and discrete variables and multiple independent lower-level problems, is widely used in product family optimization. However, BLP is difficult in theory and is an NP-hard problem. Consequently, using traditional methods to solve such problems is difficult. Genetic algorithms (GAs have great value in solving BLP problems, and many studies have designed GAs to solve BLP problems; however, such GAs are typically designed for special cases that do not involve MINLBLP with one or multiple followers. Therefore, we propose a bilevel GA to solve these particular MINLBLP problems, which are widely used in product family problems. We give numerical examples to demonstrate the effectiveness of the proposed algorithm. In addition, a reducer family case study is examined to demonstrate practical applications of the proposed BLGA.

50 Years of Integer Programming 1958-2008 From the Early Years to the State-of-the-Art

CERN Document Server

Jünger, Michael; Naddef, Denis

2010-01-01

In 1958, Ralph E. Gomory transformed the field of integer programming when he published a paper that described a cutting-plane algorithm for pure integer programs and announced that the method could be refined to give a finite algorithm for integer programming. In 2008, to commemorate the anniversary of this seminal paper, a special workshop celebrating fifty years of integer programming was held in Aussois, France, as part of the 12th Combinatorial Optimization Workshop. It contains reprints of key historical articles and written versions of survey lectures on six of the hottest topics in the

New Approaches for Very Large-Scale Integer Programming

Science.gov (United States)

2016-06-24

DISTRIBUTION/ AVAILABILITY STATEMENT Approved for Public Release 13. SUPPLEMENTARY NOTES 14. ABSTRACT The focus of this project is new computational... heuristics for integer programs in order to rapidly improve dual bounds. 2. Choosing good branching variables in branch-and-bound algorithms for MIP. 3...programming, algorithms, parallel processing, machine learning, heuristics 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT UU 18. NUMBER OF

A quantum architecture for multiplying signed integers

International Nuclear Information System (INIS)

Alvarez-Sanchez, J J; Alvarez-Bravo, J V; Nieto, L M

2008-01-01

A new quantum architecture for multiplying signed integers is presented based on Booth's algorithm, which is well known in classical computation. It is shown how a quantum binary chain might be encoded by its flank changes, giving the final product in 2's-complement representation.

Presolving and regularization in mixed-integer second-order cone optimization

DEFF Research Database (Denmark)

Friberg, Henrik Alsing

Mixed-integer second-order cone optimization is a powerful mathematical framework capable of representing both logical conditions and nonlinear relationships in mathematical models of industrial optimization problems. What is more, solution methods are already part of many major commercial solvers...... both continuous and mixed-integer conic optimization in general, is discovered and treated. This part of the thesis continues the studies of facial reduction preceding the work of Borwein and Wolkowicz [17] in 1981, when the first algorithmic cure for these kinds of reliability issues were formulated....... An important distinction to make between continuous and mixed-integer optimization, however, is that the reliability issues occurring in mixed-integer optimization cannot be blamed on the practitioner’s formulation of the problem. Specifically, as shown, the causes for these issues may well lie within...

Quantum Integers

International Nuclear Information System (INIS)

Khrennikov, Andrei; Klein, Moshe; Mor, Tal

2010-01-01

In number theory, a partition of a positive integer n is a way of writing n as a sum of positive integers. The number of partitions of n is given by the partition function p(n). Inspired by quantum information processing, we extend the concept of partitions in number theory as follows: for an integer n, we treat each partition as a basis state of a quantum system representing that number n, so that the Hilbert-space that corresponds to that integer n is of dimension p(n); the 'classical integer' n can thus be generalized into a (pure) quantum state ||ψ(n) > which is a superposition of the partitions of n, in the same way that a quantum bit (qubit) is a generalization of a classical bit. More generally, ρ(n) is a density matrix in that same Hilbert-space (a probability distribution over pure states). Inspired by the notion of quantum numbers in quantum theory (such as in Bohr's model of the atom), we then try to go beyond the partitions, by defining (via recursion) the notion of 'sub-partitions' in number theory. Combining the two notions mentioned above, sub-partitions and quantum integers, we finally provide an alternative definition of the quantum integers [the pure-state |ψ'(n)> and the mixed-state ρ'(n),] this time using the sub-partitions as the basis states instead of the partitions, for describing the quantum number that corresponds to the integer n.

Multi-task feature selection in microarray data by binary integer programming.

Science.gov (United States)

Lan, Liang; Vucetic, Slobodan

2013-12-20

A major challenge in microarray classification is that the number of features is typically orders of magnitude larger than the number of examples. In this paper, we propose a novel feature filter algorithm to select the feature subset with maximal discriminative power and minimal redundancy by solving a quadratic objective function with binary integer constraints. To improve the computational efficiency, the binary integer constraints are relaxed and a low-rank approximation to the quadratic term is applied. The proposed feature selection algorithm was extended to solve multi-task microarray classification problems. We compared the single-task version of the proposed feature selection algorithm with 9 existing feature selection methods on 4 benchmark microarray data sets. The empirical results show that the proposed method achieved the most accurate predictions overall. We also evaluated the multi-task version of the proposed algorithm on 8 multi-task microarray datasets. The multi-task feature selection algorithm resulted in significantly higher accuracy than when using the single-task feature selection methods.

Performance Analysis for Cooperative Communication System with QC-LDPC Codes Constructed with Integer Sequences

Directory of Open Access Journals (Sweden)

Yan Zhang

2015-01-01

Full Text Available This paper presents four different integer sequences to construct quasi-cyclic low-density parity-check (QC-LDPC codes with mathematical theory. The paper introduces the procedure of the coding principle and coding. Four different integer sequences constructing QC-LDPC code are compared with LDPC codes by using PEG algorithm, array codes, and the Mackey codes, respectively. Then, the integer sequence QC-LDPC codes are used in coded cooperative communication. Simulation results show that the integer sequence constructed QC-LDPC codes are effective, and overall performance is better than that of other types of LDPC codes in the coded cooperative communication. The performance of Dayan integer sequence constructed QC-LDPC is the most excellent performance.

A Branch and Bound Algorithm for a Class of Biobjective Mixed Integer Programs

DEFF Research Database (Denmark)

Stidsen, Thomas Riis; Andersen, Kim Allan; Dammann, Bernd

2014-01-01

there is the complicating factor that some of the variables are required to be integral. The resulting class of problems is named multiobjective mixed integer programming (MOMIP) problems. Solving these kinds of optimization problems exactly requires a method that can generate the whole set of nondominated points (the...... Pareto-optimal front). In this paper, we first give a survey of the newly developed branch and bound methods for solving MOMIP problems. After that, we propose a new branch and bound method for solving a subclass of MOMIP problems, where only two objectives are allowed, the integer variables are binary......, and one of the two objectives has only integer variables. The proposed method is able to find the full set of nondominated points. It is tested on a large number of problem instances, from six different classes of MOMIP problems. The results reveal that the developed biobjective branch and bound method...

Hierarchical Hidden Markov Models for Multivariate Integer-Valued Time-Series

DEFF Research Database (Denmark)

Catania, Leopoldo; Di Mari, Roberto

2018-01-01

We propose a new flexible dynamic model for multivariate nonnegative integer-valued time-series. Observations are assumed to depend on the realization of two additional unobserved integer-valued stochastic variables which control for the time-and cross-dependence of the data. An Expectation......-Maximization algorithm for maximum likelihood estimation of the model's parameters is derived. We provide conditional and unconditional (cross)-moments implied by the model, as well as the limiting distribution of the series. A Monte Carlo experiment investigates the finite sample properties of our estimation...

On the Delone property of (−β-integers

Directory of Open Access Journals (Sweden)

Wolfgang Steiner

2011-08-01

Full Text Available The (−β-integers are natural generalisations of the β-integers, and thus of the integers, for negative real bases. They can be described by infinite words which are fixed points of anti-morphisms. We show that they are not necessarily uniformly discrete and relatively dense in the real numbers.

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

International Nuclear Information System (INIS)

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

1984-01-01

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

Sharp probability estimates for Shor's order-finding algorithm

OpenAIRE

Bourdon, P. S.; Williams, H. T.

2006-01-01

Let N be a (large positive integer, let b > 1 be an integer relatively prime to N, and let r be the order of b modulo N. Finally, let QC be a quantum computer whose input register has the size specified in Shor's original description of his order-finding algorithm. We prove that when Shor's algorithm is implemented on QC, then the probability P of obtaining a (nontrivial) divisor of r exceeds 0.7 whenever N exceeds 2^{11}-1 and r exceeds 39, and we establish that 0.7736 is an asymptotic lower...

FAST INTEGER AMBIGUITY RESOLUTION IN GPS KINEMATIC POSITIONING USING LEFT NULL SPACE AND MULTI-TIME (INVERSE PAIRED CHOLESKY DECORRELATION

Directory of Open Access Journals (Sweden)

Rong Duan

Full Text Available Aiming at the problems that huge amount of computation in ambiguity resolution with multiple epochs and high-order matrix inversion occurred in the GPS kinematic relative positioning, a modified algorithm for fast integer ambiguity resolution is proposed. Firstly, Singular Value Decomposition (SVD is applied to construct the left null space matrix in order to eliminate the baselines components, which is able to separate ambiguity parameters from the position parameters efficiently. Kalman filter is applied only to estimate the ambiguity parameters so that the real-time ambiguity float solution is obtained. Then, sorting and multi-time (inverse paired Cholesky decomposition are adopted for decorrelation of ambiguity. After diagonal elements preprocessing and diagonal elements sorting according to the results of Cholesky decomposition, the efficiency of decomposition and decorrelation is improved. Lastly, the integer search algorithm implemented in LAMBDA method is used for searching the integer ambiguity. To verify the validity and efficacy of the proposed algorithm, static and kinematic tests are carried out. Experimental results show that this algorithm has good performance of decorrelation and precision of float solution, with computation speed also increased effectively. The final positioning accuracy result with static baseline error less than 1 cm and kinematic error less than 2 cm, which indicates that it can be used for fast kinematic positioning of high precision carrier.

A formalization of the Berlekamp-Zassenhaus factorization algorithm

NARCIS (Netherlands)

Divasón, Jose; Joosten, Sebastiaan; Thiemann, René; Yamada, Akihisa

2017-01-01

We formalize the Berlekamp–Zassenhaus algorithm for factoring square-free integer polynomials in Isabelle/HOL. We further adapt an existing formalization of Yun’s square-free factorization algorithm to integer polynomials, and thus provide an efficient and certified factorization algorithm for

Mixed integer evolution strategies for parameter optimization.

Science.gov (United States)

Li, Rui; Emmerich, Michael T M; Eggermont, Jeroen; Bäck, Thomas; Schütz, M; Dijkstra, J; Reiber, J H C

2013-01-01

Evolution strategies (ESs) are powerful probabilistic search and optimization algorithms gleaned from biological evolution theory. They have been successfully applied to a wide range of real world applications. The modern ESs are mainly designed for solving continuous parameter optimization problems. Their ability to adapt the parameters of the multivariate normal distribution used for mutation during the optimization run makes them well suited for this domain. In this article we describe and study mixed integer evolution strategies (MIES), which are natural extensions of ES for mixed integer optimization problems. MIES can deal with parameter vectors consisting not only of continuous variables but also with nominal discrete and integer variables. Following the design principles of the canonical evolution strategies, they use specialized mutation operators tailored for the aforementioned mixed parameter classes. For each type of variable, the choice of mutation operators is governed by a natural metric for this variable type, maximal entropy, and symmetry considerations. All distributions used for mutation can be controlled in their shape by means of scaling parameters, allowing self-adaptation to be implemented. After introducing and motivating the conceptual design of the MIES, we study the optimality of the self-adaptation of step sizes and mutation rates on a generalized (weighted) sphere model. Moreover, we prove global convergence of the MIES on a very general class of problems. The remainder of the article is devoted to performance studies on artificial landscapes (barrier functions and mixed integer NK landscapes), and a case study in the optimization of medical image analysis systems. In addition, we show that with proper constraint handling techniques, MIES can also be applied to classical mixed integer nonlinear programming problems.

Logic integer programming models for signaling networks.

Science.gov (United States)

Haus, Utz-Uwe; Niermann, Kathrin; Truemper, Klaus; Weismantel, Robert

2009-05-01

We propose a static and a dynamic approach to model biological signaling networks, and show how each can be used to answer relevant biological questions. For this, we use the two different mathematical tools of Propositional Logic and Integer Programming. The power of discrete mathematics for handling qualitative as well as quantitative data has so far not been exploited in molecular biology, which is mostly driven by experimental research, relying on first-order or statistical models. The arising logic statements and integer programs are analyzed and can be solved with standard software. For a restricted class of problems the logic models reduce to a polynomial-time solvable satisfiability algorithm. Additionally, a more dynamic model enables enumeration of possible time resolutions in poly-logarithmic time. Computational experiments are included.

Quadratic Sieve integer factorization using Hadoop

OpenAIRE

Ghebregiorgish, Semere Tsehaye

2012-01-01

Master's thesis in Computer Science Integer factorization problem is one of the most important parts in the world of cryptography. The security of the widely-used public-key cryptographic algorithm, RSA [1], and the Blum Blum Shub cryptographic pseudorandom number generator [2] heavily depend on the presumed difficulty of factoring a number to its prime constituents. As the size of the number to be factored gets larger, the difficulty of the problem increases enormously. Thi...

Using Integer Clocks to Verify the Timing-Sync Sensor Network Protocol

Science.gov (United States)

Huang, Xiaowan; Singh, Anu; Smolka, Scott A.

2010-01-01

We use the UPPAAL model checker for Timed Automata to verify the Timing-Sync time-synchronization protocol for sensor networks (TPSN). The TPSN protocol seeks to provide network-wide synchronization of the distributed clocks in a sensor network. Clock-synchronization algorithms for sensor networks such as TPSN must be able to perform arithmetic on clock values to calculate clock drift and network propagation delays. They must be able to read the value of a local clock and assign it to another local clock. Such operations are not directly supported by the theory of Timed Automata. To overcome this formal-modeling obstacle, we augment the UPPAAL specification language with the integer clock derived type. Integer clocks, which are essentially integer variables that are periodically incremented by a global pulse generator, greatly facilitate the encoding of the operations required to synchronize clocks as in the TPSN protocol. With this integer-clock-based model of TPSN in hand, we use UPPAAL to verify that the protocol achieves network-wide time synchronization and is devoid of deadlock. We also use the UPPAAL Tracer tool to illustrate how integer clocks can be used to capture clock drift and resynchronization during protocol execution

Integer anatomy

Energy Technology Data Exchange (ETDEWEB)

Doolittle, R. [ONR, Arlington, VA (United States)

1994-11-15

The title integer anatomy is intended to convey the idea of a systematic method for displaying the prime decomposition of the integers. Just as the biological study of anatomy does not teach us all things about behavior of species neither would we expect to learn everything about the number theory from a study of its anatomy. But, some number-theoretic theorems are illustrated by inspection of integer anatomy, which tend to validate the underlying structure and the form as developed and displayed in this treatise. The first statement to be made in this development is: the way structure of the natural numbers is displayed depends upon the allowed operations.

Positive integer solutions of certain diophantine equations

Indian Academy of Sciences (India)

BIJAN KUMAR PATEL

2018-03-19

Mar 19, 2018 ... integer solutions. They also found all the positive integer solutions of the given equations in terms of Fibonacci and Lucas numbers. Another interesting number sequence which is closely related to the sequence of. Fibonacci numbers is the sequence of balancing numbers. In 1999, Behera et al. [1] intro-.

Expansion around half-integer values, binomial sums, and inverse binomial sums

International Nuclear Information System (INIS)

Weinzierl, Stefan

2004-01-01

I consider the expansion of transcendental functions in a small parameter around rational numbers. This includes in particular the expansion around half-integer values. I present algorithms which are suitable for an implementation within a symbolic computer algebra system. The method is an extension of the technique of nested sums. The algorithms allow in addition the evaluation of binomial sums, inverse binomial sums and generalizations thereof

VLSI Architectures for the Multiplication of Integers Modulo a Fermat Number

Science.gov (United States)

Chang, J. J.; Truong, T. K.; Reed, I. S.; Hsu, I. S.

1984-01-01

Multiplication is central in the implementation of Fermat number transforms and other residue number algorithms. There is need for a good multiplication algorithm that can be realized easily on a very large scale integration (VLSI) chip. The Leibowitz multiplier is modified to realize multiplication in the ring of integers modulo a Fermat number. This new algorithm requires only a sequence of cyclic shifts and additions. The designs developed for this new multiplier are regular, simple, expandable, and, therefore, suitable for VLSI implementation.

S-parts of terms of integer linear recurrence sequences

NARCIS (Netherlands)

Bugeaud, Y.; Evertse, J.H.

2017-01-01

Let S = {q1 , . . . , qs } be a finite, non-empty set of distinct prime numbers. For a non-zero integer m, write m = q1^ r1 . . . qs^rs M, where r1 , . . . , rs  are non-negative integers and M is an integer relatively prime to q1 . . . qs. We define the S-part [m]_S of m by [m]_S := q1^r1 . . .

Binary GCD like Algorithms for Some Complex Quadratic Rings

DEFF Research Database (Denmark)

Agarwal, Saurabh; Frandsen, Gudmund Skovbjerg

2004-01-01

On the lines of the binary gcd algorithm for rational integers, algorithms for computing the gcd are presented for the ring of integers in where . Thus a binary gcd like algorithm is presented for a unique factorization domain which is not Euclidean (case d=-19). Together with the earlier known b...

Calculating the Mean Amplitude of Glycemic Excursions from Continuous Glucose Data Using an Open-Code Programmable Algorithm Based on the Integer Nonlinear Method.

Science.gov (United States)

Yu, Xuefei; Lin, Liangzhuo; Shen, Jie; Chen, Zhi; Jian, Jun; Li, Bin; Xin, Sherman Xuegang

2018-01-01

The mean amplitude of glycemic excursions (MAGE) is an essential index for glycemic variability assessment, which is treated as a key reference for blood glucose controlling at clinic. However, the traditional "ruler and pencil" manual method for the calculation of MAGE is time-consuming and prone to error due to the huge data size, making the development of robust computer-aided program an urgent requirement. Although several software products are available instead of manual calculation, poor agreement among them is reported. Therefore, more studies are required in this field. In this paper, we developed a mathematical algorithm based on integer nonlinear programming. Following the proposed mathematical method, an open-code computer program named MAGECAA v1.0 was developed and validated. The results of the statistical analysis indicated that the developed program was robust compared to the manual method. The agreement among the developed program and currently available popular software is satisfied, indicating that the worry about the disagreement among different software products is not necessary. The open-code programmable algorithm is an extra resource for those peers who are interested in the related study on methodology in the future.

An Integer Programming Formulation of the Minimum Common String Partition Problem.

Directory of Open Access Journals (Sweden)

S M Ferdous

Full Text Available We consider the problem of finding a minimum common string partition (MCSP of two strings, which is an NP-hard problem. The MCSP problem is closely related to genome comparison and rearrangement, an important field in Computational Biology. In this paper, we map the MCSP problem into a graph applying a prior technique and using this graph, we develop an Integer Linear Programming (ILP formulation for the problem. We implement the ILP formulation and compare the results with the state-of-the-art algorithms from the literature. The experimental results are found to be promising.

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

Science.gov (United States)

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

2018-01-01

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

Mixed-Integer Conic Linear Programming: Challenges and Perspectives

Science.gov (United States)

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

Integer programming theory, applications, and computations

CERN Document Server

Taha, Hamdy A

1975-01-01

Integer Programming: Theory, Applications, and Computations provides information pertinent to the theory, applications, and computations of integer programming. This book presents the computational advantages of the various techniques of integer programming.Organized into eight chapters, this book begins with an overview of the general categorization of integer applications and explains the three fundamental techniques of integer programming. This text then explores the concept of implicit enumeration, which is general in a sense that it is applicable to any well-defined binary program. Other

Hard equality constrained integer knapsacks

NARCIS (Netherlands)

Aardal, K.I.; Lenstra, A.K.; Cook, W.J.; Schulz, A.S.

2002-01-01

We consider the following integer feasibility problem: "Given positive integer numbers a 0, a 1,..., a n, with gcd(a 1,..., a n) = 1 and a = (a 1,..., a n), does there exist a nonnegative integer vector x satisfying ax = a 0?" Some instances of this type have been found to be extremely hard to solve

LOW COMPLEXITY HYBRID LOSSY TO LOSSLESS IMAGE CODER WITH COMBINED ORTHOGONAL POLYNOMIALS TRANSFORM AND INTEGER WAVELET TRANSFORM

Directory of Open Access Journals (Sweden)

R. Krishnamoorthy

2012-05-01

Full Text Available In this paper, a new lossy to lossless image coding scheme combined with Orthogonal Polynomials Transform and Integer Wavelet Transform is proposed. The Lifting Scheme based Integer Wavelet Transform (LS-IWT is first applied on the image in order to reduce the blocking artifact and memory demand. The Embedded Zero tree Wavelet (EZW subband coding algorithm is used in this proposed work for progressive image coding which achieves efficient bit rate reduction. The computational complexity of lower subband coding of EZW algorithm is reduced in this proposed work with a new integer based Orthogonal Polynomials transform coding. The normalization and mapping are done on the subband of the image for exploiting the subjective redundancy and the zero tree structure is obtained for EZW coding and so the computation complexity is greatly reduced in this proposed work. The experimental results of the proposed technique also show that the efficient bit rate reduction is achieved for both lossy and lossless compression when compared with existing techniques.

On factoring RSA modulus using random-restart hill-climbing algorithm and Pollard’s rho algorithm

Science.gov (United States)

Budiman, M. A.; Rachmawati, D.

2017-12-01

The security of the widely-used RSA public key cryptography algorithm depends on the difficulty of factoring a big integer into two large prime numbers. For many years, the integer factorization problem has been intensively and extensively studied in the field of number theory. As a result, a lot of deterministic algorithms such as Euler’s algorithm, Kraitchik’s, and variants of Pollard’s algorithms have been researched comprehensively. Our study takes a rather uncommon approach: rather than making use of intensive number theories, we attempt to factorize RSA modulus n by using random-restart hill-climbing algorithm, which belongs the class of metaheuristic algorithms. The factorization time of RSA moduli with different lengths is recorded and compared with the factorization time of Pollard’s rho algorithm, which is a deterministic algorithm. Our experimental results indicates that while random-restart hill-climbing algorithm is an acceptable candidate to factorize smaller RSA moduli, the factorization speed is much slower than that of Pollard’s rho algorithm.

Determining on-fault earthquake magnitude distributions from integer programming

Science.gov (United States)

Geist, Eric L.; Parsons, Thomas E.

2018-01-01

Earthquake magnitude distributions among faults within a fault system are determined from regional seismicity and fault slip rates using binary integer programming. A synthetic earthquake catalog (i.e., list of randomly sampled magnitudes) that spans millennia is first formed, assuming that regional seismicity follows a Gutenberg-Richter relation. Each earthquake in the synthetic catalog can occur on any fault and at any location. The objective is to minimize misfits in the target slip rate for each fault, where slip for each earthquake is scaled from its magnitude. The decision vector consists of binary variables indicating which locations are optimal among all possibilities. Uncertainty estimates in fault slip rates provide explicit upper and lower bounding constraints to the problem. An implicit constraint is that an earthquake can only be located on a fault if it is long enough to contain that earthquake. A general mixed-integer programming solver, consisting of a number of different algorithms, is used to determine the optimal decision vector. A case study is presented for the State of California, where a 4 kyr synthetic earthquake catalog is created and faults with slip ≥3 mm/yr are considered, resulting in >106  variables. The optimal magnitude distributions for each of the faults in the system span a rich diversity of shapes, ranging from characteristic to power-law distributions. 

A verified LLL algorithm

NARCIS (Netherlands)

Divasón, Jose; Joosten, Sebastiaan; Thiemann, René; Yamada, Akihisa

2018-01-01

The Lenstra-Lenstra-Lovász basis reduction algorithm, also known as LLL algorithm, is an algorithm to find a basis with short, nearly orthogonal vectors of an integer lattice. Thereby, it can also be seen as an approximation to solve the shortest vector problem (SVP), which is an NP-hard problem,

Parallel integer sorting with medium and fine-scale parallelism

Science.gov (United States)

Dagum, Leonardo

1993-01-01

Two new parallel integer sorting algorithms, queue-sort and barrel-sort, are presented and analyzed in detail. These algorithms do not have optimal parallel complexity, yet they show very good performance in practice. Queue-sort designed for fine-scale parallel architectures which allow the queueing of multiple messages to the same destination. Barrel-sort is designed for medium-scale parallel architectures with a high message passing overhead. The performance results from the implementation of queue-sort on a Connection Machine CM-2 and barrel-sort on a 128 processor iPSC/860 are given. The two implementations are found to be comparable in performance but not as good as a fully vectorized bucket sort on the Cray YMP.

An improved exploratory search technique for pure integer linear programming problems

Science.gov (United States)

Fogle, F. R.

1990-01-01

The development is documented of a heuristic method for the solution of pure integer linear programming problems. The procedure draws its methodology from the ideas of Hooke and Jeeves type 1 and 2 exploratory searches, greedy procedures, and neighborhood searches. It uses an efficient rounding method to obtain its first feasible integer point from the optimal continuous solution obtained via the simplex method. Since this method is based entirely on simple addition or subtraction of one to each variable of a point in n-space and the subsequent comparison of candidate solutions to a given set of constraints, it facilitates significant complexity improvements over existing techniques. It also obtains the same optimal solution found by the branch-and-bound technique in 44 of 45 small to moderate size test problems. Two example problems are worked in detail to show the inner workings of the method. Furthermore, using an established weighted scheme for comparing computational effort involved in an algorithm, a comparison of this algorithm is made to the more established and rigorous branch-and-bound method. A computer implementation of the procedure, in PC compatible Pascal, is also presented and discussed.

Integer batch scheduling problems for a single-machine with simultaneous effect of learning and forgetting to minimize total actual flow time

Directory of Open Access Journals (Sweden)

Rinto Yusriski

2015-09-01

Full Text Available This research discusses an integer batch scheduling problems for a single-machine with position-dependent batch processing time due to the simultaneous effect of learning and forgetting. The decision variables are the number of batches, batch sizes, and the sequence of the resulting batches. The objective is to minimize total actual flow time, defined as total interval time between the arrival times of parts in all respective batches and their common due date. There are two proposed algorithms to solve the problems. The first is developed by using the Integer Composition method, and it produces an optimal solution. Since the problems can be solved by the first algorithm in a worst-case time complexity O(n2n-1, this research proposes the second algorithm. It is a heuristic algorithm based on the Lagrange Relaxation method. Numerical experiments show that the heuristic algorithm gives outstanding results.

Slip and Slide Method of Factoring Trinomials with Integer Coefficients over the Integers

Science.gov (United States)

Donnell, William A.

2012-01-01

In intermediate and college algebra courses there are a number of methods for factoring quadratic trinomials with integer coefficients over the integers. Some of these methods have been given names, such as trial and error, reversing FOIL, AC method, middle term splitting method and slip and slide method. The purpose of this article is to discuss…

Frozen density embedding with non-integer subsystems' particle numbers.

Science.gov (United States)

Fabiano, Eduardo; Laricchia, Savio; Della Sala, Fabio

2014-03-21

We extend the frozen density embedding theory to non-integer subsystems' particles numbers. Different features of this formulation are discussed, with special concern for approximate embedding calculations. In particular, we highlight the relation between the non-integer particle-number partition scheme and the resulting embedding errors. Finally, we provide a discussion of the implications of the present theory for the derivative discontinuity issue and the calculation of chemical reactivity descriptors.

Multiple Object Tracking Using the Shortest Path Faster Association Algorithm

Directory of Open Access Journals (Sweden)

Zhenghao Xi

2014-01-01

Full Text Available To solve the persistently multiple object tracking in cluttered environments, this paper presents a novel tracking association approach based on the shortest path faster algorithm. First, the multiple object tracking is formulated as an integer programming problem of the flow network. Then we relax the integer programming to a standard linear programming problem. Therefore, the global optimum can be quickly obtained using the shortest path faster algorithm. The proposed method avoids the difficulties of integer programming, and it has a lower worst-case complexity than competing methods but better robustness and tracking accuracy in complex environments. Simulation results show that the proposed algorithm takes less time than other state-of-the-art methods and can operate in real time.

A parallel line sieve for the GNFS Algorithm

OpenAIRE

Sameh Daoud; Ibrahim Gad

2014-01-01

RSA is one of the most important public key cryptosystems for information security. The security of RSA depends on Integer factorization problem, it relies on the difficulty of factoring large integers. Much research has gone into problem of factoring a large number. Due to advances in factoring algorithms and advances in computing hardware the size of the number that can be factorized increases exponentially year by year. The General Number Field Sieve algorithm (GNFS) is currently the best ...

Network Model for The Problem of Integer Balancing of a Fourdimensional Matrix

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A. V. Smirnov

2016-01-01

Full Text Available The problem of integer balancing of a four-dimensional matrix is studied. The elements of the inner part (all four indices are greater than zero of the given real matrix are summed in each direction and each two- and three-dimensional section of the matrix; the total sum is also found. These sums are placed into the elements where one or more indices are equal to zero (according to the summing directions. The problem is to find an integer matrix of the same structure, which can be produced from the initial one by replacing the elements with the largest previous or the smallest following integer. At the same time, the element with four zero indices should be produced with standard rules of rounding - off. In the article the problem of finding the maximum multiple flow in the network of any natural multiplicity   is also studied. There are arcs of three types: ordinary arcs, multiple arcs and multi-arcs. Each multiple and multi-arc is a union of   linked arcs, which are adjusted with each other. The network constructing rules are described. The definitions of a divisible network and some associated subjects are stated. There are defined the basic principles for reducing the integer balancing problem of an  -dimensional matrix (  to the problem of finding the maximum flow in a divisible multiple network of multiplicity  . There are stated the rules for reducing the four-dimensional balancing problem to the maximum flow problem in the network of multiplicity 5. The algorithm of finding the maximum flow, which meets the solvability conditions for the integer balancing problem, is formulated for such a network.

A statistical mechanical approach to restricted integer partition functions

Science.gov (United States)

Zhou, Chi-Chun; Dai, Wu-Sheng

2018-05-01

The main aim of this paper is twofold: (1) suggesting a statistical mechanical approach to the calculation of the generating function of restricted integer partition functions which count the number of partitions—a way of writing an integer as a sum of other integers under certain restrictions. In this approach, the generating function of restricted integer partition functions is constructed from the canonical partition functions of various quantum gases. (2) Introducing a new type of restricted integer partition functions corresponding to general statistics which is a generalization of Gentile statistics in statistical mechanics; many kinds of restricted integer partition functions are special cases of this restricted integer partition function. Moreover, with statistical mechanics as a bridge, we reveal a mathematical fact: the generating function of restricted integer partition function is just the symmetric function which is a class of functions being invariant under the action of permutation groups. Using this approach, we provide some expressions of restricted integer partition functions as examples.

Fixed-point image orthorectification algorithms for reduced computational cost

Science.gov (United States)

French, Joseph Clinton

Imaging systems have been applied to many new applications in recent years. With the advent of low-cost, low-power focal planes and more powerful, lower cost computers, remote sensing applications have become more wide spread. Many of these applications require some form of geolocation, especially when relative distances are desired. However, when greater global positional accuracy is needed, orthorectification becomes necessary. Orthorectification is the process of projecting an image onto a Digital Elevation Map (DEM), which removes terrain distortions and corrects the perspective distortion by changing the viewing angle to be perpendicular to the projection plane. Orthorectification is used in disaster tracking, landscape management, wildlife monitoring and many other applications. However, orthorectification is a computationally expensive process due to floating point operations and divisions in the algorithm. To reduce the computational cost of on-board processing, two novel algorithm modifications are proposed. One modification is projection utilizing fixed-point arithmetic. Fixed point arithmetic removes the floating point operations and reduces the processing time by operating only on integers. The second modification is replacement of the division inherent in projection with a multiplication of the inverse. The inverse must operate iteratively. Therefore, the inverse is replaced with a linear approximation. As a result of these modifications, the processing time of projection is reduced by a factor of 1.3x with an average pixel position error of 0.2% of a pixel size for 128-bit integer processing and over 4x with an average pixel position error of less than 13% of a pixel size for a 64-bit integer processing. A secondary inverse function approximation is also developed that replaces the linear approximation with a quadratic. The quadratic approximation produces a more accurate approximation of the inverse, allowing for an integer multiplication calculation

Ramsey theory on the integers

CERN Document Server

Landman, Bruce M

2014-01-01

Ramsey theory is the study of the structure of mathematical objects that is preserved under partitions. In its full generality, Ramsey theory is quite powerful, but can quickly become complicated. By limiting the focus of this book to Ramsey theory applied to the set of integers, the authors have produced a gentle, but meaningful, introduction to an important and enticing branch of modern mathematics. Ramsey Theory on the Integers offers students a glimpse into the world of mathematical research and the opportunity for them to begin pondering unsolved problems. For this new edition, several sections have been added and others have been significantly updated. Among the newly introduced topics are: rainbow Ramsey theory, an "inequality" version of Schur's theorem, monochromatic solutions of recurrence relations, Ramsey results involving both sums and products, monochromatic sets avoiding certain differences, Ramsey properties for polynomial progressions, generalizations of the Erdős-Ginzberg-Ziv theorem, and t...

A new algorithm for the integration of exponential and logarithmic functions

Science.gov (United States)

Rothstein, M.

1977-01-01

An algorithm for symbolic integration of functions built up from the rational functions by repeatedly applying either the exponential or logarithm functions is discussed. This algorithm does not require polynomial factorization nor partial fraction decomposition and requires solutions of linear systems with only a small number of unknowns. It is proven that if this algorithm is applied to rational functions over the integers, a computing time bound for the algorithm can be obtained which is a polynomial in a bound on the integer length of the coefficients, and in the degrees of the numerator and denominator of the rational function involved.

A novel progressively swarmed mixed integer genetic algorithm for ...

African Journals Online (AJOL)

MIGA) which inherits the advantages of binary and real coded Genetic Algorithm approach. The proposed algorithm is applied for the conventional generation cost minimization Optimal Power Flow (OPF) problem and for the Security ...

Integer-valued trawl processes

DEFF Research Database (Denmark)

Barndorff-Nielsen, Ole E.; Lunde, Asger; Shephard, Neil

2014-01-01

the probabilistic properties of such processes in detail and, in addition, study volatility modulation and multivariate extensions within the new modelling framework. Moreover, we describe how the parameters of a trawl process can be estimated and obtain promising estimation results in our simulation study. Finally......This paper introduces a new continuous-time framework for modelling serially correlated count and integer-valued data. The key component in our new model is the class of integer-valued trawl processes, which are serially correlated, stationary, infinitely divisible processes. We analyse...

Integer and combinatorial optimization

CERN Document Server

Nemhauser, George L

1999-01-01

Rave reviews for INTEGER AND COMBINATORIAL OPTIMIZATION ""This book provides an excellent introduction and survey of traditional fields of combinatorial optimization . . . It is indeed one of the best and most complete texts on combinatorial optimization . . . available. [And] with more than 700 entries, [it] has quite an exhaustive reference list.""-Optima ""A unifying approach to optimization problems is to formulate them like linear programming problems, while restricting some or all of the variables to the integers. This book is an encyclopedic resource for such f

Genetic Algorithm for Mixed Integer Nonlinear Bilevel Programming and Applications in Product Family Design

OpenAIRE

Chenlu Miao; Gang Du; Yi Xia; Danping Wang

2016-01-01

Many leader-follower relationships exist in product family design engineering problems. We use bilevel programming (BLP) to reflect the leader-follower relationship and describe such problems. Product family design problems have unique characteristics; thus, mixed integer nonlinear BLP (MINLBLP), which has both continuous and discrete variables and multiple independent lower-level problems, is widely used in product family optimization. However, BLP is difficult in theory and is an NP-hard pr...

Analysis misconception of integers in microteaching activities

Science.gov (United States)

Setyawati, R. D.; Indiati, I.

2018-05-01

This study view to analyse student misconceptions on integers in microteaching activities. This research used qualitative research design. An integers test contained questions from eight main areas of integers. The Integers material test includes (a) converting the image into fractions, (b) examples of positive numbers including rational numbers, (c) operations in fractions, (d) sorting fractions from the largest to the smallest, and vice versa; e) equate denominator, (f) concept of ratio mark, (g) definition of fraction, and (h) difference between fractions and parts. The results indicated an integers concepts: (1) the students have not been able to define concepts well based on the classification of facts in organized part; (2) The correlational concept: students have not been able to combine interrelated events in the form of general principles; and (3) theoretical concepts: students have not been able to use concepts that facilitate in learning the facts or events in an organized system.

Harmonic oscillator states with integer and non-integer orbital angular momentum

International Nuclear Information System (INIS)

Land, Martin

2011-01-01

We study the quantum mechanical harmonic oscillator in two and three dimensions, with particular attention to the solutions as basis states for representing their respective symmetry groups — O(2), O(1,1), O(3), and O(2,1). The goal of this study is to establish a correspondence between Hilbert space descriptions found by solving the Schrodinger equation in polar coordinates, and Fock space descriptions constructed by expressing the symmetry operators in terms of creation/annihilation operators. We obtain wavefunctions characterized by a principal quantum number, the group Casimir eigenvalue, and one group generator whose eigenvalue is m + s, for integer m and real constant parameter s. For the three groups that contain O(2), the solutions split into two inequivalent representations, one associated with s = 0, from which we recover the familiar description of the oscillator as a product of one-dimensional solutions, and the other with s > 0 (in three dimensions, solutions are found for s = 0 and s = 1/2) whose solutions are non-separable in Cartesian coordinates, and are hence overlooked by the standard Fock space approach. The O(1,1) solutions are singlet states, restricted to zero eigenvalue of the symmetry operator, which represents the boost, not angular momentum. For O(2), a single set of creation and annihilation operators forms a ladder representation for the allowed oscillator states for any s, and the degeneracy of energy states is always finite. However, in three dimensions, the integer and half-integer eigenstates are qualitatively different: the former can be expressed as finite dimensional irreducible tensors under O(3) or O(2,1) while the latter exhibit infinite degeneracy. Creation operators that produce the allowed integer states by acting on the non-degenerate ground state are constructed as irreducible tensor products of the fundamental vector representation. However, the half-integer eigenstates are infinite-dimensional, as expected for the non

Quasi-greedy systems of integer translates

DEFF Research Database (Denmark)

Nielsen, Morten; Sikic, Hrvoje

We consider quasi-greedy systems of integer translates in a finitely generated shift invariant subspace of L2(Rd), that is systems for which the thresholding approximation procedure is well behaved. We prove that every quasi-greedy system of integer translates is also a Riesz basis for its closed...

Quasi-greedy systems of integer translates

DEFF Research Database (Denmark)

Nielsen, Morten; Sikic, Hrvoje

2008-01-01

We consider quasi-greedy systems of integer translates in a finitely generated shift-invariant subspace of L2(Rd), that is systems for which the thresholding approximation procedure is well behaved. We prove that every quasi-greedy system of integer translates is also a Riesz basis for its closed...

Final Report---Optimization Under Nonconvexity and Uncertainty: Algorithms and Software

Energy Technology Data Exchange (ETDEWEB)

Jeff Linderoth

2011-11-06

the goal of this work was to develop new algorithmic techniques for solving large-scale numerical optimization problems, focusing on problems classes that have proven to be among the most challenging for practitioners: those involving uncertainty and those involving nonconvexity. This research advanced the state-of-the-art in solving mixed integer linear programs containing symmetry, mixed integer nonlinear programs, and stochastic optimization problems. The focus of the work done in the continuation was on Mixed Integer Nonlinear Programs (MINLP)s and Mixed Integer Linear Programs (MILP)s, especially those containing a great deal of symmetry.

Non-integer viscoelastic constitutive law to model soft biological tissues to in-vivo indentation.

Science.gov (United States)

Demirci, Nagehan; Tönük, Ergin

2014-01-01

During the last decades, derivatives and integrals of non-integer orders are being more commonly used for the description of constitutive behavior of various viscoelastic materials including soft biological tissues. Compared to integer order constitutive relations, non-integer order viscoelastic material models of soft biological tissues are capable of capturing a wider range of viscoelastic behavior obtained from experiments. Although integer order models may yield comparably accurate results, non-integer order material models have less number of parameters to be identified in addition to description of an intermediate material that can monotonically and continuously be adjusted in between an ideal elastic solid and an ideal viscous fluid. In this work, starting with some preliminaries on non-integer (fractional) calculus, the "spring-pot", (intermediate mechanical element between a solid and a fluid), non-integer order three element (Zener) solid model, finally a user-defined large strain non-integer order viscoelastic constitutive model was constructed to be used in finite element simulations. Using the constitutive equation developed, by utilizing inverse finite element method and in vivo indentation experiments, soft tissue material identification was performed. The results indicate that material coefficients obtained from relaxation experiments, when optimized with creep experimental data could simulate relaxation, creep and cyclic loading and unloading experiments accurately. Non-integer calculus viscoelastic constitutive models, having physical interpretation and modeling experimental data accurately is a good alternative to classical phenomenological viscoelastic constitutive equations.

Is there a computable upper bound for the height of a solution of a Diophantine equation with a unique solution in positive integers?

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Tyszka Apoloniusz

2017-03-01

Full Text Available Let Bn = {xi · xj = xk : i, j, k ∈ {1, . . . , n}} ∪ {xi + 1 = xk : i, k ∈ {1, . . . , n}} denote the system of equations in the variables x1, . . . , xn. For a positive integer n, let _(n denote the smallest positive integer b such that for each system of equations S ⊆ Bn with a unique solution in positive integers x1, . . . , xn, this solution belongs to [1, b]n. Let g(1 = 1, and let g(n + 1 = 22g(n for every positive integer n. We conjecture that ξ (n 6 g(2n for every positive integer n. We prove: (1 the function ξ : N \\ {0} → N \\ {0} is computable in the limit; (2 if a function f : N \\ {0} → N \\ {0} has a single-fold Diophantine representation, then there exists a positive integer m such that f (n m; (3 the conjecture implies that there exists an algorithm which takes as input a Diophantine equation D(x1, . . . , xp = 0 and returns a positive integer d with the following property: for every positive integers a1, . . . , ap, if the tuple (a1, . . . , ap solely solves the equation D(x1, . . . , xp = 0 in positive integers, then a1, . . . , ap 6 d; (4 the conjecture implies that if a set M ⊆ N has a single-fold Diophantine representation, then M is computable; (5 for every integer n > 9, the inequality ξ (n < (22n−5 − 12n−5 + 1 implies that 22n−5 + 1 is composite.

THE PHENOMENON OF HALF-INTEGER SPIN, QUATERNIONS, AND PAULI MATRICES

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FERNANDO R. GONZÁLEZ DÍAZ

2017-01-01

Full Text Available In this paper the phenomenon of half-integer spin exemplification Paul AM Dirac made with a pair of scissors, an elastic cord and chair play. Four examples in which the same phenomenon appears and the algebraic structure of quaternions is related to one of the examples are described. Mathematical proof of the phenomenon using known topological and algebraic results are explained. The basic results of algebraic structures are described quaternions H , and an intrinsic relationship with the phenomenon half-integer spin and the Pauli matrices is established.

A hybrid Jaya algorithm for reliability-redundancy allocation problems

Science.gov (United States)

Ghavidel, Sahand; Azizivahed, Ali; Li, Li

2018-04-01

This article proposes an efficient improved hybrid Jaya algorithm based on time-varying acceleration coefficients (TVACs) and the learning phase introduced in teaching-learning-based optimization (TLBO), named the LJaya-TVAC algorithm, for solving various types of nonlinear mixed-integer reliability-redundancy allocation problems (RRAPs) and standard real-parameter test functions. RRAPs include series, series-parallel, complex (bridge) and overspeed protection systems. The search power of the proposed LJaya-TVAC algorithm for finding the optimal solutions is first tested on the standard real-parameter unimodal and multi-modal functions with dimensions of 30-100, and then tested on various types of nonlinear mixed-integer RRAPs. The results are compared with the original Jaya algorithm and the best results reported in the recent literature. The optimal results obtained with the proposed LJaya-TVAC algorithm provide evidence for its better and acceptable optimization performance compared to the original Jaya algorithm and other reported optimal results.

Module detection in complex networks using integer optimisation

Directory of Open Access Journals (Sweden)

Tsoka Sophia

2010-11-01

Full Text Available Abstract Background The detection of modules or community structure is widely used to reveal the underlying properties of complex networks in biology, as well as physical and social sciences. Since the adoption of modularity as a measure of network topological properties, several methodologies for the discovery of community structure based on modularity maximisation have been developed. However, satisfactory partitions of large graphs with modest computational resources are particularly challenging due to the NP-hard nature of the related optimisation problem. Furthermore, it has been suggested that optimising the modularity metric can reach a resolution limit whereby the algorithm fails to detect smaller communities than a specific size in large networks. Results We present a novel solution approach to identify community structure in large complex networks and address resolution limitations in module detection. The proposed algorithm employs modularity to express network community structure and it is based on mixed integer optimisation models. The solution procedure is extended through an iterative procedure to diminish effects that tend to agglomerate smaller modules (resolution limitations. Conclusions A comprehensive comparative analysis of methodologies for module detection based on modularity maximisation shows that our approach outperforms previously reported methods. Furthermore, in contrast to previous reports, we propose a strategy to handle resolution limitations in modularity maximisation. Overall, we illustrate ways to improve existing methodologies for community structure identification so as to increase its efficiency and applicability.

Ramsey theory on the integers

CERN Document Server

Landman, Bruce M

2003-01-01

Ramsey theory is the study of the structure of mathematical objects that is preserved under partitions. In its full generality, Ramsey theory is quite powerful, but can quickly become complicated. By limiting the focus of this book to Ramsey theory applied to the set of integers, the authors have produced a gentle, but meaningful, introduction to an important and enticing branch of modern mathematics. Ramsey Theory on the Integers offers students something quite rare for a book at this level: a glimpse into the world of mathematical research and the opportunity to begin pondering unsolved problems themselves. In addition to being the first truly accessible book on Ramsey theory, this innovative book also provides the first cohesive study of Ramsey theory on the integers. It contains perhaps the most substantial account of solved and unsolved problems in this blossoming subarea of Ramsey theory. The result is a breakthrough book that will engage students, teachers, and researchers alike.

Fractal electrodynamics via non-integer dimensional space approach

Science.gov (United States)

Tarasov, Vasily E.

2015-09-01

Using the recently suggested vector calculus for non-integer dimensional space, we consider electrodynamics problems in isotropic case. This calculus allows us to describe fractal media in the framework of continuum models with non-integer dimensional space. We consider electric and magnetic fields of fractal media with charges and currents in the framework of continuum models with non-integer dimensional spaces. An application of the fractal Gauss's law, the fractal Ampere's circuital law, the fractal Poisson equation for electric potential, and equation for fractal stream of charges are suggested. Lorentz invariance and speed of light in fractal electrodynamics are discussed. An expression for effective refractive index of non-integer dimensional space is suggested.

A hardware-oriented concurrent TZ search algorithm for High-Efficiency Video Coding

Science.gov (United States)

Doan, Nghia; Kim, Tae Sung; Rhee, Chae Eun; Lee, Hyuk-Jae

2017-12-01

High-Efficiency Video Coding (HEVC) is the latest video coding standard, in which the compression performance is double that of its predecessor, the H.264/AVC standard, while the video quality remains unchanged. In HEVC, the test zone (TZ) search algorithm is widely used for integer motion estimation because it effectively searches the good-quality motion vector with a relatively small amount of computation. However, the complex computation structure of the TZ search algorithm makes it difficult to implement it in the hardware. This paper proposes a new integer motion estimation algorithm which is designed for hardware execution by modifying the conventional TZ search to allow parallel motion estimations of all prediction unit (PU) partitions. The algorithm consists of the three phases of zonal, raster, and refinement searches. At the beginning of each phase, the algorithm obtains the search points required by the original TZ search for all PU partitions in a coding unit (CU). Then, all redundant search points are removed prior to the estimation of the motion costs, and the best search points are then selected for all PUs. Compared to the conventional TZ search algorithm, experimental results show that the proposed algorithm significantly decreases the Bjøntegaard Delta bitrate (BD-BR) by 0.84%, and it also reduces the computational complexity by 54.54%.

Improved multivariate polynomial factoring algorithm

International Nuclear Information System (INIS)

Wang, P.S.

1978-01-01

A new algorithm for factoring multivariate polynomials over the integers based on an algorithm by Wang and Rothschild is described. The new algorithm has improved strategies for dealing with the known problems of the original algorithm, namely, the leading coefficient problem, the bad-zero problem and the occurrence of extraneous factors. It has an algorithm for correctly predetermining leading coefficients of the factors. A new and efficient p-adic algorithm named EEZ is described. Bascially it is a linearly convergent variable-by-variable parallel construction. The improved algorithm is generally faster and requires less store then the original algorithm. Machine examples with comparative timing are included

Preconditioning 2D Integer Data for Fast Convex Hull Computations.

Science.gov (United States)

Cadenas, José Oswaldo; Megson, Graham M; Luengo Hendriks, Cris L

2016-01-01

In order to accelerate computing the convex hull on a set of n points, a heuristic procedure is often applied to reduce the number of points to a set of s points, s ≤ n, which also contains the same hull. We present an algorithm to precondition 2D data with integer coordinates bounded by a box of size p × q before building a 2D convex hull, with three distinct advantages. First, we prove that under the condition min(p, q) ≤ n the algorithm executes in time within O(n); second, no explicit sorting of data is required; and third, the reduced set of s points forms a simple polygonal chain and thus can be directly pipelined into an O(n) time convex hull algorithm. This paper empirically evaluates and quantifies the speed up gained by preconditioning a set of points by a method based on the proposed algorithm before using common convex hull algorithms to build the final hull. A speedup factor of at least four is consistently found from experiments on various datasets when the condition min(p, q) ≤ n holds; the smaller the ratio min(p, q)/n is in the dataset, the greater the speedup factor achieved.

Bilevel programming problems theory, algorithms and applications to energy networks

CERN Document Server

Dempe, Stephan; Pérez-Valdés, Gerardo A; Kalashnykova, Nataliya; Kalashnikova, Nataliya

2015-01-01

This book describes recent theoretical findings relevant to bilevel programming in general, and in mixed-integer bilevel programming in particular. It describes recent applications in energy problems, such as the stochastic bilevel optimization approaches used in the natural gas industry. New algorithms for solving linear and mixed-integer bilevel programming problems are presented and explained.

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

Energy Technology Data Exchange (ETDEWEB)

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

2017-03-27

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

Linear and integer programming made easy

CERN Document Server

Hu, T C

2016-01-01

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

Diversity and non-integer differentiation for system dynamics

CERN Document Server

Oustaloup, Alain

2014-01-01

Based on a structured approach to diversity, notably inspired by various forms of diversity of natural origins, Diversity and Non-integer Derivation Applied to System Dynamics provides a study framework to the introduction of the non-integer derivative as a modeling tool. Modeling tools that highlight unsuspected dynamical performances (notably damping performances) in an ""integer"" approach of mechanics and automation are also included. Written to enable a two-tier reading, this is an essential resource for scientists, researchers, and industrial engineers interested in this subject area. Ta

An n -material thresholding method for improving integerness of solutions in topology optimization

International Nuclear Information System (INIS)

Watts, Seth; Engineering); Tortorelli, Daniel A.; Engineering)

2016-01-01

It is common in solving topology optimization problems to replace an integer-valued characteristic function design field with the material volume fraction field, a real-valued approximation of the design field that permits "fictitious" mixtures of materials during intermediate iterations in the optimization process. This is reasonable so long as one can interpolate properties for such materials and so long as the final design is integer valued. For this purpose, we present a method for smoothly thresholding the volume fractions of an arbitrary number of material phases which specify the design. This method is trivial for two-material design problems, for example, the canonical topology design problem of specifying the presence or absence of a single material within a domain, but it becomes more complex when three or more materials are used, as often occurs in material design problems. We take advantage of the similarity in properties between the volume fractions and the barycentric coordinates on a simplex to derive a thresholding, method which is applicable to an arbitrary number of materials. As we show in a sensitivity analysis, this method has smooth derivatives, allowing it to be used in gradient-based optimization algorithms. Finally, we present results, which show synergistic effects when used with Solid Isotropic Material with Penalty and Rational Approximation of Material Properties material interpolation functions, popular methods of ensuring integerness of solutions.

Superposition of two optical vortices with opposite integer or non-integer orbital angular momentum

Directory of Open Access Journals (Sweden)

Carlos Fernando Díaz Meza

2016-01-01

Full Text Available This work develops a brief proposal to achieve the superposition of two opposite vortex beams, both with integer or non-integer mean value of the orbital angular momentum. The first part is about the generation of this kind of spatial light distributions through a modified Brown and Lohmann’s hologram. The inclusion of a simple mathematical expression into the pixelated grid’s transmittance function, based in Fourier domain properties, shifts the diffraction orders counterclockwise and clockwise to the same point and allows the addition of different modes. The strategy is theoretically and experimentally validated for the case of two opposite rotation helical wavefronts.

Metamorphic Testing Integer Overflow Faults of Mission Critical Program: A Case Study

Directory of Open Access Journals (Sweden)

Zhanwei Hui

2013-01-01

Full Text Available For mission critical programs, integer overflow is one of the most dangerous faults. Different testing methods provide several effective ways to detect the defect. However, it is hard to validate the testing outputs, because the oracle of testing is not always available or too expensive to get, unless the program throws an exception obviously. In the present study, the authors conduct a case study, where the authors apply a metamorphic testing (MT method to detect the integer overflow defect and alleviate the oracle problem in testing critical program of Traffic Collision Avoidance System (TCAS. Experimental results show that, in revealing typical integer mutations, compared with traditional safety property testing method, MT with a novel symbolic metamorphic relation is more effective than the traditional method in some cases.

Neomysis integer: a review

OpenAIRE

Fockedey, N.

2005-01-01

The present chapter aims to be a literature review on the brackish water mysid Neomysis integer, with focus on its feeding ecology, life history aspects, behaviour, physiology, biochemical composition, bioenergetics and ecotoxico10gy. All records on the species, available from literature, are listed as an appendix. The review aims to identify the state-of-the-art and the gaps in our knowledge on the species. Abundant information is available on the distribution patterns of Neomysis integer in...

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

Science.gov (United States)

Lyubetsky, Vassily; Gershgorin, Roman; Gorbunov, Konstantin

2017-12-06

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

Binary Positive Semidefinite Matrices and Associated Integer Polytopes

DEFF Research Database (Denmark)

Letchford, Adam N.; Sørensen, Michael Malmros

2012-01-01

We consider the positive semidefinite (psd) matrices with binary entries, along with the corresponding integer polytopes. We begin by establishing some basic properties of these matrices and polytopes. Then, we show that several families of integer polytopes in the literature-the cut, boolean qua...

Neutrosophic Integer Programming Problem

Directory of Open Access Journals (Sweden)

Mai Mohamed

2017-02-01

Full Text Available In this paper, we introduce the integer programming in neutrosophic environment, by considering coffecients of problem as a triangulare neutrosophic numbers. The degrees of acceptance, indeterminacy and rejection of objectives are simultaneously considered.

Quantum recurrence and integer ratios in neutron resonances

Energy Technology Data Exchange (ETDEWEB)

Ohkubo, Makio

1998-03-01

Quantum recurrence of the compound nucleus in neutron resonance reactions are described for normal modes which are excited on the compound nucleus simultaneously. In the structure of the recurrence time, integer relations among dominant level spacings are derived. The `base modes` are assumed as stable combinations of the normal modes, preferably excited in many nuclei. (author)

Garbage-free reversible constant multipliers for arbitrary integers

DEFF Research Database (Denmark)

Mogensen, Torben Ægidius

2013-01-01

We present a method for constructing reversible circuitry for multiplying integers by arbitrary integer constants. The method is based on Mealy machines and gives circuits whose size are (in the worst case) linear in the size of the constant. This makes the method unsuitable for large constants...

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 ...

Experimental realization of Shor's quantum factoring algorithm using nuclear magnetic resonance.

Science.gov (United States)

Vandersypen, L M; Steffen, M; Breyta, G; Yannoni, C S; Sherwood, M H; Chuang, I L

The number of steps any classical computer requires in order to find the prime factors of an l-digit integer N increases exponentially with l, at least using algorithms known at present. Factoring large integers is therefore conjectured to be intractable classically, an observation underlying the security of widely used cryptographic codes. Quantum computers, however, could factor integers in only polynomial time, using Shor's quantum factoring algorithm. Although important for the study of quantum computers, experimental demonstration of this algorithm has proved elusive. Here we report an implementation of the simplest instance of Shor's algorithm: factorization of N = 15 (whose prime factors are 3 and 5). We use seven spin-1/2 nuclei in a molecule as quantum bits, which can be manipulated with room temperature liquid-state nuclear magnetic resonance techniques. This method of using nuclei to store quantum information is in principle scalable to systems containing many quantum bits, but such scalability is not implied by the present work. The significance of our work lies in the demonstration of experimental and theoretical techniques for precise control and modelling of complex quantum computers. In particular, we present a simple, parameter-free but predictive model of decoherence effects in our system.

Integers annual volume 2013

CERN Document Server

Landman, Bruce

2014-01-01

""Integers"" is a refereed online journal devoted to research in the area of combinatorial number theory. It publishes original research articles in combinatorics and number theory. This work presents all papers of the 2013 volume in book form.

Bi-objective integer programming for RNA secondary structure prediction with pseudoknots.

Science.gov (United States)

Legendre, Audrey; Angel, Eric; Tahi, Fariza

2018-01-15

RNA structure prediction is an important field in bioinformatics, and numerous methods and tools have been proposed. Pseudoknots are specific motifs of RNA secondary structures that are difficult to predict. Almost all existing methods are based on a single model and return one solution, often missing the real structure. An alternative approach would be to combine different models and return a (small) set of solutions, maximizing its quality and diversity in order to increase the probability that it contains the real structure. We propose here an original method for predicting RNA secondary structures with pseudoknots, based on integer programming. We developed a generic bi-objective integer programming algorithm allowing to return optimal and sub-optimal solutions optimizing simultaneously two models. This algorithm was then applied to the combination of two known models of RNA secondary structure prediction, namely MEA and MFE. The resulting tool, called BiokoP, is compared with the other methods in the literature. The results show that the best solution (structure with the highest F 1 -score) is, in most cases, given by BiokoP. Moreover, the results of BiokoP are homogeneous, regardless of the pseudoknot type or the presence or not of pseudoknots. Indeed, the F 1 -scores are always higher than 70% for any number of solutions returned. The results obtained by BiokoP show that combining the MEA and the MFE models, as well as returning several optimal and several sub-optimal solutions, allow to improve the prediction of secondary structures. One perspective of our work is to combine better mono-criterion models, in particular to combine a model based on the comparative approach with the MEA and the MFE models. This leads to develop in the future a new multi-objective algorithm to combine more than two models. BiokoP is available on the EvryRNA platform: https://EvryRNA.ibisc.univ-evry.fr .

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

Science.gov (United States)

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

2017-08-01

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

Spreading Sequences Generated Using Asymmetrical Integer-Number Maps

Directory of Open Access Journals (Sweden)

V. Sebesta

2007-09-01

Full Text Available Chaotic sequences produced by piecewise linear maps can be transformed to binary sequences. The binary sequences are optimal for the asynchronous DS/CDMA systems in case of certain shapes of the maps. This paper is devoted to the one-to-one integer-number maps derived from the suitable asymmetrical piecewise linear maps. Such maps give periodic integer-number sequences, which can be transformed to the binary sequences. The binary sequences produced via proposed modified integer-number maps are perfectly balanced and embody good autocorrelation and crosscorrelation properties. The number of different binary sequences is sizable. The sequences are suitable as spreading sequences in DS/CDMA systems.

Integer-valued time series

NARCIS (Netherlands)

van den Akker, R.

2007-01-01

This thesis adresses statistical problems in econometrics. The first part contributes statistical methodology for nonnegative integer-valued time series. The second part of this thesis discusses semiparametric estimation in copula models and develops semiparametric lower bounds for a large class of

Integer programming techniques for educational timetabling

DEFF Research Database (Denmark)

Fonseca, George H.G.; Santos, Haroldo G.; Carrano, Eduardo G.

2017-01-01

in recent studies in the field. This work presents new cuts and reformulations for the existing integer programming model for XHSTT. The proposed cuts improved hugely the linear relaxation of the formulation, leading to an average gap reduction of 32%. Applied to XHSTT-2014 instance set, the alternative...... formulation provided four new best known lower bounds and, used in a matheuristic framework, improved eleven best known solutions. The computational experiments also show that the resulting integer programming models from the proposed formulation are more effectively solved for most of the instances....

A New GCD Algorithm for Quadratic Number Rings with Unique Factorization

DEFF Research Database (Denmark)

Agarwal, Saurabh; Frandsen, Gudmund Skovbjerg

2006-01-01

We present an algorithm to compute a greatest common divisor of two integers in a quadratic number ring that is a unique factorization domain. The algorithm uses bit operations in a ring of discriminant Δ. This appears to be the first gcd algorithm of complexity o(n 2) for any fixed non-Euclidean...

Anisotropic fractal media by vector calculus in non-integer dimensional space

Energy Technology Data Exchange (ETDEWEB)

Tarasov, Vasily E., E-mail: tarasov@theory.sinp.msu.ru [Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow 119991 (Russian Federation)

2014-08-15

A review of different approaches to describe anisotropic fractal media is proposed. In this paper, differentiation and integration non-integer dimensional and multi-fractional spaces are considered as tools to describe anisotropic fractal materials and media. We suggest a generalization of vector calculus for non-integer dimensional space by using a product measure method. The product of fractional and non-integer dimensional spaces allows us to take into account the anisotropy of the fractal media in the framework of continuum models. The integration over non-integer-dimensional spaces is considered. In this paper differential operators of first and second orders for fractional space and non-integer dimensional space are suggested. The differential operators are defined as inverse operations to integration in spaces with non-integer dimensions. Non-integer dimensional space that is product of spaces with different dimensions allows us to give continuum models for anisotropic type of the media. The Poisson's equation for fractal medium, the Euler-Bernoulli fractal beam, and the Timoshenko beam equations for fractal material are considered as examples of application of suggested generalization of vector calculus for anisotropic fractal materials and media.

Anisotropic fractal media by vector calculus in non-integer dimensional space

Science.gov (United States)

Tarasov, Vasily E.

2014-08-01

A review of different approaches to describe anisotropic fractal media is proposed. In this paper, differentiation and integration non-integer dimensional and multi-fractional spaces are considered as tools to describe anisotropic fractal materials and media. We suggest a generalization of vector calculus for non-integer dimensional space by using a product measure method. The product of fractional and non-integer dimensional spaces allows us to take into account the anisotropy of the fractal media in the framework of continuum models. The integration over non-integer-dimensional spaces is considered. In this paper differential operators of first and second orders for fractional space and non-integer dimensional space are suggested. The differential operators are defined as inverse operations to integration in spaces with non-integer dimensions. Non-integer dimensional space that is product of spaces with different dimensions allows us to give continuum models for anisotropic type of the media. The Poisson's equation for fractal medium, the Euler-Bernoulli fractal beam, and the Timoshenko beam equations for fractal material are considered as examples of application of suggested generalization of vector calculus for anisotropic fractal materials and media.

Anisotropic fractal media by vector calculus in non-integer dimensional space

International Nuclear Information System (INIS)

Tarasov, Vasily E.

2014-01-01

A review of different approaches to describe anisotropic fractal media is proposed. In this paper, differentiation and integration non-integer dimensional and multi-fractional spaces are considered as tools to describe anisotropic fractal materials and media. We suggest a generalization of vector calculus for non-integer dimensional space by using a product measure method. The product of fractional and non-integer dimensional spaces allows us to take into account the anisotropy of the fractal media in the framework of continuum models. The integration over non-integer-dimensional spaces is considered. In this paper differential operators of first and second orders for fractional space and non-integer dimensional space are suggested. The differential operators are defined as inverse operations to integration in spaces with non-integer dimensions. Non-integer dimensional space that is product of spaces with different dimensions allows us to give continuum models for anisotropic type of the media. The Poisson's equation for fractal medium, the Euler-Bernoulli fractal beam, and the Timoshenko beam equations for fractal material are considered as examples of application of suggested generalization of vector calculus for anisotropic fractal materials and media

Winding numbers in homotopy theory from integers to reals

International Nuclear Information System (INIS)

Mekhfi, M.

1993-07-01

In Homotopy Theory (HT) we define paths on a given topological space. Closed paths prove to be construction elements of a group (the fundamental group) Π 1 and carry charges, the winding numbers. The charges are integers as they indicate how many times closed paths encircle a given hole (or set of holes). Open paths as they are defined in (HT) do not possess any groups structure and as such they are less useful in topology. In the present paper we enlarge the concept of a path in such a way that both types of paths do possess a group structure. In this broad sense we have two fundamental groups the Π i = Z group and the SO(2) group of rotations but the latter has the global property that there is no periodicity in the rotation angle. There is also two charge operators W and W λ whose eigenvalues are either integers or reals depending respectively on the paths being closed or open. Also the SO(2) group and the real charge operator W λ are not independently defined but directly related respectively to the Π i group and to the integer charge operator W. Thus well defined links can be established between seemingly different groups and charges. (author). 3 refs, 1 fig

Heuristic Methods of Integer Programming and Its Applications in Economics

Directory of Open Access Journals (Sweden)

Dominika Crnjac Milić

2010-12-01

Full Text Available A short overview of the results related to integer programming is described in the introductory part of this paper. Furthermore, there is a list of literature related to this field. The main part of the paper analyses the Heuristic method which yields a very fast result without the use of significant mathematical tools.

COMPUTING VERTICES OF INTEGER PARTITION POLYTOPES

Directory of Open Access Journals (Sweden)

A. S. Vroublevski

2015-01-01

Full Text Available The paper describes a method of generating vertices of the polytopes of integer partitions that was used by the authors to calculate all vertices and support vertices of the partition polytopes for all n ≤ 105 and all knapsack partitions of n ≤ 165. The method avoids generating all partitions of n. The vertices are determined with the help of sufficient and necessary conditions; in the hard cases, the well-known program Polymake is used. Some computational aspects are exposed in more detail. These are the algorithm for checking the criterion that characterizes partitions that are convex combinations of two other partitions; the way of using two combinatorial operations that transform the known vertices to the new ones; and employing the Polymake to recognize a limited number (for small n of partitions that need three or more other partitions for being convexly expressed. We discuss the computational results on the numbers of vertices and support vertices of the partition polytopes and some appealing problems these results give rise to.

Spinor Field Realizations of the half-integer $W_{2,s}$ Strings

OpenAIRE

Wei, Shao-Wen; Liu, Yu-Xiao; Zhang, Li-Jie; Ren, Ji-Rong

2008-01-01

The grading Becchi-Rouet-Stora-Tyutin (BRST) method gives a way to construct the integer $W_{2,s}$ strings, where the BRST charge is written as $Q_B=Q_0+Q_1$. Using this method, we reconstruct the nilpotent BRST charges $Q_{0}$ for the integer $W_{2,s}$ strings and the half-integer $W_{2,s}$ strings. Then we construct the exact grading BRST charge with spinor fields and give the new realizations of the half-integer $W_{2,s}$ strings for the cases of $s=3/2$, 5/2, and 7/2.

Right Propositional Neighborhood Logic over Natural Numbers with Integer Constraints for Interval Lengths

DEFF Research Database (Denmark)

Bresolin, Davide; Goranko, Valentin; Montanari, Angelo

2009-01-01

Interval temporal logics are based on interval structures over linearly (or partially) ordered domains, where time intervals, rather than time instants, are the primitive ontological entities. In this paper we introduce and study Right Propositional Neighborhood Logic over natural numbers...... with integer constraints for interval lengths, which is a propositional interval temporal logic featuring a modality for the 'right neighborhood' relation between intervals and explicit integer constraints for interval lengths. We prove that it has the bounded model property with respect to ultimately periodic...

Some operational tools for solving fractional and higher integer order differential equations: A survey on their mutual relations

Science.gov (United States)

Kiryakova, Virginia S.

2012-11-01

The Laplace Transform (LT) serves as a basis of the Operational Calculus (OC), widely explored by engineers and applied scientists in solving mathematical models for their practical needs. This transform is closely related to the exponential and trigonometric functions (exp, cos, sin) and to the classical differentiation and integration operators, reducing them to simple algebraic operations. Thus, the classical LT and the OC give useful tool to handle differential equations and systems with constant coefficients. Several generalizations of the LT have been introduced to allow solving, in a similar way, of differential equations with variable coefficients and of higher integer orders, as well as of fractional (arbitrary non-integer) orders. Note that fractional order mathematical models are recently widely used to describe better various systems and phenomena of the real world. This paper surveys briefly some of our results on classes of such integral transforms, that can be obtained from the LT by means of "transmutations" which are operators of the generalized fractional calculus (GFC). On the list of these Laplace-type integral transforms, we consider the Borel-Dzrbashjan, Meijer, Krätzel, Obrechkoff, generalized Obrechkoff (multi-index Borel-Dzrbashjan) transforms, etc. All of them are G- and H-integral transforms of convolutional type, having as kernels Meijer's G- or Fox's H-functions. Besides, some special functions (also being G- and H-functions), among them - the generalized Bessel-type and Mittag-Leffler (M-L) type functions, are generating Gel'fond-Leontiev (G-L) operators of generalized differentiation and integration, which happen to be also operators of GFC. Our integral transforms have operational properties analogous to those of the LT - they do algebrize the G-L generalized integrations and differentiations, and thus can serve for solving wide classes of differential equations with variable coefficients of arbitrary, including non-integer order

Integer Linear Programming for Constrained Multi-Aspect Committee Review Assignment

Science.gov (United States)

Karimzadehgan, Maryam; Zhai, ChengXiang

2011-01-01

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

Solution Algorithm for a New Bi-Level Discrete Network Design Problem

Directory of Open Access Journals (Sweden)

Qun Chen

2013-12-01

Full Text Available A new discrete network design problem (DNDP was pro-posed in this paper, where the variables can be a series of integers rather than just 0-1. The new DNDP can determine both capacity improvement grades of reconstruction roads and locations and capacity grades of newly added roads, and thus complies with the practical projects where road capacity can only be some discrete levels corresponding to the number of lanes of roads. This paper designed a solution algorithm combining branch-and-bound with Hooke-Jeeves algorithm, where feasible integer solutions are recorded in searching the process of Hooke-Jeeves algorithm, lend -ing itself to determine the upper bound of the upper-level problem. The thresholds for branch cutting and ending were set for earlier convergence. Numerical examples are given to demonstrate the efficiency of the proposed algorithm.

Discrete cosine and sine transforms general properties, fast algorithms and integer approximations

CERN Document Server

Britanak, Vladimir; Rao, K R; Rao, K R

2006-01-01

The Discrete Cosine Transform (DCT) is used in many applications by the scientific, engineering and research communities and in data compression in particular. Fast algorithms and applications of the DCT Type II (DCT-II) have become the heart of many established international image/video coding standards. Since then other forms of the DCT and Discrete Sine Transform (DST) have been investigated in detail. This new edition presents the complete set of DCT and DST discrete trigonometric transforms, including their definitions, general mathematical properties, and relations to the optimal Karhune

Vertical partitioning of relational OLTP databases using integer programming

DEFF Research Database (Denmark)

Amossen, Rasmus Resen

2010-01-01

A way to optimize performance of relational row store databases is to reduce the row widths by vertically partition- ing tables into table fractions in order to minimize the number of irrelevant columns/attributes read by each transaction. This pa- per considers vertical partitioning algorithms...... for relational row- store OLTP databases with an H-store-like architecture, meaning that we would like to maximize the number of single-sited transactions. We present a model for the vertical partitioning problem that, given a schema together with a vertical partitioning and a workload, estimates the costs...... applied to the TPC-C benchmark and the heuristic is shown to obtain solutions with costs close to the ones found using the quadratic program....

Optimal and Suboptimal Finger Selection Algorithms for MMSE Rake Receivers in Impulse Radio Ultra-Wideband Systems

Directory of Open Access Journals (Sweden)

Chiang Mung

2006-01-01

Full Text Available The problem of choosing the optimal multipath components to be employed at a minimum mean square error (MMSE selective Rake receiver is considered for an impulse radio ultra-wideband system. First, the optimal finger selection problem is formulated as an integer programming problem with a nonconvex objective function. Then, the objective function is approximated by a convex function and the integer programming problem is solved by means of constraint relaxation techniques. The proposed algorithms are suboptimal due to the approximate objective function and the constraint relaxation steps. However, they perform better than the conventional finger selection algorithm, which is suboptimal since it ignores the correlation between multipath components, and they can get quite close to the optimal scheme that cannot be implemented in practice due to its complexity. In addition to the convex relaxation techniques, a genetic-algorithm- (GA- based approach is proposed, which does not need any approximations or integer relaxations. This iterative algorithm is based on the direct evaluation of the objective function, and can achieve near-optimal performance with a reasonable number of iterations. Simulation results are presented to compare the performance of the proposed finger selection algorithms with that of the conventional and the optimal schemes.

Hybrid Projected Gradient-Evolutionary Search Algorithm for Mixed Integer Nonlinear Optimization Problems

National Research Council Canada - National Science Library

Homaifar, Abdollah; Esterline, Albert; Kimiaghalam, Bahram

2005-01-01

The Hybrid Projected Gradient-Evolutionary Search Algorithm (HPGES) algorithm uses a specially designed evolutionary-based global search strategy to efficiently create candidate solutions in the solution space...

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

Science.gov (United States)

Fogle, F. R.

1994-01-01

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

Rewrite systems for integer arithmetic

NARCIS (Netherlands)

H.R. Walters (Pum); H. Zantema (Hans)

1995-01-01

textabstractWe present three term rewrite systems for integer arithmetic with addition, multiplication, and, in two cases, subtraction. All systems are ground confluent and terminating; termination is proved by semantic labelling and recursive path order. The first system represents numbers by

Paradeisos: A perfect hashing algorithm for many-body eigenvalue problems

Science.gov (United States)

Jia, C. J.; Wang, Y.; Mendl, C. B.; Moritz, B.; Devereaux, T. P.

2018-03-01

We describe an essentially perfect hashing algorithm for calculating the position of an element in an ordered list, appropriate for the construction and manipulation of many-body Hamiltonian, sparse matrices. Each element of the list corresponds to an integer value whose binary representation reflects the occupation of single-particle basis states for each element in the many-body Hilbert space. The algorithm replaces conventional methods, such as binary search, for locating the elements of the ordered list, eliminating the need to store the integer representation for each element, without increasing the computational complexity. Combined with the "checkerboard" decomposition of the Hamiltonian matrix for distribution over parallel computing environments, this leads to a substantial savings in aggregate memory. While the algorithm can be applied broadly to many-body, correlated problems, we demonstrate its utility in reducing total memory consumption for a series of fermionic single-band Hubbard model calculations on small clusters with progressively larger Hilbert space dimension.

On the convex hull of the simple integer recourse objective function

NARCIS (Netherlands)

Klein Haneveld, Willem K.; Stougie, L.; van der Vlerk, Maarten H.

1995-01-01

We consider the objective function of a simple integer recourse problem with fixed technology matrix. Using properties of the expected value function, we prove a relation between the convex hull of this function and the expected value function of a continuous simple recourse program. We present an

An Algorithm to Solve the Equal-Sum-Product Problem

OpenAIRE

Nyblom, M. A.; Evans, C. D.

2013-01-01

A recursive algorithm is constructed which finds all solutions to a class of Diophantine equations connected to the problem of determining ordered n-tuples of positive integers satisfying the property that their sum is equal to their product. An examination of the use of Binary Search Trees in implementing the algorithm into a working program is given. In addition an application of the algorithm for searching possible extra exceptional values of the equal-sum-product problem is explored after...

Advances in mixed-integer programming methods for chemical production scheduling.

Science.gov (United States)

Velez, Sara; Maravelias, Christos T

2014-01-01

The goal of this paper is to critically review advances in the area of chemical production scheduling over the past three decades and then present two recently proposed solution methods that have led to dramatic computational enhancements. First, we present a general framework and problem classification and discuss modeling and solution methods with an emphasis on mixed-integer programming (MIP) techniques. Second, we present two solution methods: (a) a constraint propagation algorithm that allows us to compute parameters that are then used to tighten MIP scheduling models and (b) a reformulation that introduces new variables, thus leading to effective branching. We also present computational results and an example illustrating how these methods are implemented, as well as the resulting enhancements. We close with a discussion of open research challenges and future research directions.

Integer Flows and Circuit Covers of Graphs and Signed Graphs

Science.gov (United States)

Cheng, Jian

The work in Chapter 2 is motivated by Tutte and Jaeger's pioneering work on converting modulo flows into integer-valued flows for ordinary graphs. For a signed graphs (G, sigma), we first prove that for each k ∈ {2, 3}, if (G, sigma) is (k - 1)-edge-connected and contains an even number of negative edges when k = 2, then every modulo k-flow of (G, sigma) can be converted into an integer-valued ( k + 1)-ow with a larger or the same support. We also prove that if (G, sigma) is odd-(2p+1)-edge-connected, then (G, sigma) admits a modulo circular (2 + 1/ p)-flows if and only if it admits an integer-valued circular (2 + 1/p)-flows, which improves all previous result by Xu and Zhang (DM2005), Schubert and Steffen (EJC2015), and Zhu (JCTB2015). Shortest circuit cover conjecture is one of the major open problems in graph theory. It states that every bridgeless graph G contains a set of circuits F such that each edge is contained in at least one member of F and the length of F is at most 7/5∥E(G)∥. This concept was recently generalized to signed graphs by Macajova et al. (JGT2015). In Chapter 3, we improve their upper bound from 11∥E( G)∥ to 14/3 ∥E(G)∥, and if G is 2-edgeconnected and has even negativeness, then it can be further reduced to 11/3 ∥E(G)∥. Tutte's 3-flow conjecture has been studied by many graph theorists in the last several decades. As a new approach to this conjecture, DeVos and Thomassen considered the vectors as ow values and found that there is a close relation between vector S1-flows and integer 3-NZFs. Motivated by their observation, in Chapter 4, we prove that if a graph G admits a vector S1-flow with rank at most two, then G admits an integer 3-NZF. The concept of even factors is highly related to the famous Four Color Theorem. We conclude this dissertation in Chapter 5 with an improvement of a recent result by Chen and Fan (JCTB2016) on the upperbound of even factors. We show that if a graph G contains an even factor, then it

Rewrite systems for integer arithmetic

NARCIS (Netherlands)

Walters, H.R.; Zantema, H.

1994-01-01

We present three term rewrite systems for integer arithmetic with addition, multiplication, and, in two cases, subtraction. All systems are ground con uent and terminating; termination is proved by semantic labelling and recursive path order. The first system represents numbers by successor and

A few Smarandache Integer Sequences

OpenAIRE

Ibstedt, Henry

2010-01-01

This paper deals with the analysis of a few Smarandache Integer Sequences which first appeared in Properties or the Numbers, F. Smarandache, University or Craiova Archives, 1975. The first four sequences are recurrence generated sequences while the last three are concatenation sequences.

A novel Random Walk algorithm with Compulsive Evolution for heat exchanger network synthesis

International Nuclear Information System (INIS)

Xiao, Yuan; Cui, Guomin

2017-01-01

Highlights: • A novel Random Walk Algorithm with Compulsive Evolution is proposed for HENS. • A simple and feasible evolution strategy is presented in RWCE algorithm. • The integer and continuous variables of HEN are optimized simultaneously in RWCE. • RWCE is demonstrated a relatively strong global search ability in HEN optimization. - Abstract: The heat exchanger network (HEN) synthesis can be characterized as highly combinatorial, nonlinear and nonconvex, contributing to unmanageable computational time and a challenge in identifying the global optimal network design. Stochastic methods are robust and show a powerful global optimizing ability. Based on the common characteristic of different stochastic methods, namely randomness, a novel Random Walk algorithm with Compulsive Evolution (RWCE) is proposed to achieve the best possible total annual cost of heat exchanger network with the relatively simple and feasible evolution strategy. A population of heat exchanger networks is first randomly initialized. Next, the heat load of heat exchanger for each individual is randomly expanded or contracted in order to optimize both the integer and continuous variables simultaneously and to obtain the lowest total annual cost. Besides, when individuals approach to local optima, there is a certain probability for them to compulsively accept the imperfect networks in order to keep the population diversity and ability of global optimization. The presented method is then applied to heat exchanger network synthesis cases from the literature to compare the best results published. RWCE consistently has a lower computed total annual cost compared to previously published results.

Chemotherapy appointment scheduling under uncertainty using mean-risk stochastic integer programming.

Science.gov (United States)

Alvarado, Michelle; Ntaimo, Lewis

2018-03-01

Oncology clinics are often burdened with scheduling large volumes of cancer patients for chemotherapy treatments under limited resources such as the number of nurses and chairs. These cancer patients require a series of appointments over several weeks or months and the timing of these appointments is critical to the treatment's effectiveness. Additionally, the appointment duration, the acuity levels of each appointment, and the availability of clinic nurses are uncertain. The timing constraints, stochastic parameters, rising treatment costs, and increased demand of outpatient oncology clinic services motivate the need for efficient appointment schedules and clinic operations. In this paper, we develop three mean-risk stochastic integer programming (SIP) models, referred to as SIP-CHEMO, for the problem of scheduling individual chemotherapy patient appointments and resources. These mean-risk models are presented and an algorithm is devised to improve computational speed. Computational results were conducted using a simulation model and results indicate that the risk-averse SIP-CHEMO model with the expected excess mean-risk measure can decrease patient waiting times and nurse overtime when compared to deterministic scheduling algorithms by 42 % and 27 %, respectively.

A time series model: First-order integer-valued autoregressive (INAR(1))

Science.gov (United States)

Simarmata, D. M.; Novkaniza, F.; Widyaningsih, Y.

2017-07-01

Nonnegative integer-valued time series arises in many applications. A time series model: first-order Integer-valued AutoRegressive (INAR(1)) is constructed by binomial thinning operator to model nonnegative integer-valued time series. INAR (1) depends on one period from the process before. The parameter of the model can be estimated by Conditional Least Squares (CLS). Specification of INAR(1) is following the specification of (AR(1)). Forecasting in INAR(1) uses median or Bayesian forecasting methodology. Median forecasting methodology obtains integer s, which is cumulative density function (CDF) until s, is more than or equal to 0.5. Bayesian forecasting methodology forecasts h-step-ahead of generating the parameter of the model and parameter of innovation term using Adaptive Rejection Metropolis Sampling within Gibbs sampling (ARMS), then finding the least integer s, where CDF until s is more than or equal to u . u is a value taken from the Uniform(0,1) distribution. INAR(1) is applied on pneumonia case in Penjaringan, Jakarta Utara, January 2008 until April 2016 monthly.

Integers without large prime factors in short intervals: Conditional ...

Indian Academy of Sciences (India)

α > 0 the interval (X, X +. √. X(log X)1/2+o(1)] contains an integer having no prime factor exceeding Xα for all X sufficiently large. Keywords. Smooth numbers; Riemann zeta function. 1. Introduction. Suppose P (n) denotes the largest prime factor of an integer n > 1 and let us declare. P(1) = 1. Given a positive real number y, ...

Parallel Integer Factorization Using Quadratic Forms

National Research Council Canada - National Science Library

McMath, Stephen S

2005-01-01

Factorization is important for both practical and theoretical reasons. In secure digital communication, security of the commonly used RSA public key cryptosystem depends on the difficulty of factoring large integers...

Optimal Diet Planning for Eczema Patient Using Integer Programming

Science.gov (United States)

Zhen Sheng, Low; Sufahani, Suliadi

2018-04-01

Human diet planning is conducted by choosing appropriate food items that fulfill the nutritional requirements into the diet formulation. This paper discusses the application of integer programming to build the mathematical model of diet planning for eczema patients. The model developed is used to solve the diet problem of eczema patients from young age group. The integer programming is a scientific approach to select suitable food items, which seeks to minimize the costs, under conditions of meeting desired nutrient quantities, avoiding food allergens and getting certain foods into the diet that brings relief to the eczema conditions. This paper illustrates that the integer programming approach able to produce the optimal and feasible solution to deal with the diet problem of eczema patient.

Algorithmic Relative Complexity

Directory of Open Access Journals (Sweden)

Daniele Cerra

2011-04-01

Full Text Available Information content and compression are tightly related concepts that can be addressed through both classical and algorithmic information theories, on the basis of Shannon entropy and Kolmogorov complexity, respectively. The definition of several entities in Kolmogorov’s framework relies upon ideas from classical information theory, and these two approaches share many common traits. In this work, we expand the relations between these two frameworks by introducing algorithmic cross-complexity and relative complexity, counterparts of the cross-entropy and relative entropy (or Kullback-Leibler divergence found in Shannon’s framework. We define the cross-complexity of an object x with respect to another object y as the amount of computational resources needed to specify x in terms of y, and the complexity of x related to y as the compression power which is lost when adopting such a description for x, compared to the shortest representation of x. Properties of analogous quantities in classical information theory hold for these new concepts. As these notions are incomputable, a suitable approximation based upon data compression is derived to enable the application to real data, yielding a divergence measure applicable to any pair of strings. Example applications are outlined, involving authorship attribution and satellite image classification, as well as a comparison to similar established techniques.

Learning oncogenetic networks by reducing to mixed integer linear programming.

Science.gov (United States)

Shahrabi Farahani, Hossein; Lagergren, Jens

2013-01-01

Cancer can be a result of accumulation of different types of genetic mutations such as copy number aberrations. The data from tumors are cross-sectional and do not contain the temporal order of the genetic events. Finding the order in which the genetic events have occurred and progression pathways are of vital importance in understanding the disease. In order to model cancer progression, we propose Progression Networks, a special case of Bayesian networks, that are tailored to model disease progression. Progression networks have similarities with Conjunctive Bayesian Networks (CBNs) [1],a variation of Bayesian networks also proposed for modeling disease progression. We also describe a learning algorithm for learning Bayesian networks in general and progression networks in particular. We reduce the hard problem of learning the Bayesian and progression networks to Mixed Integer Linear Programming (MILP). MILP is a Non-deterministic Polynomial-time complete (NP-complete) problem for which very good heuristics exists. We tested our algorithm on synthetic and real cytogenetic data from renal cell carcinoma. We also compared our learned progression networks with the networks proposed in earlier publications. The software is available on the website https://bitbucket.org/farahani/diprog.

Synthesis of Greedy Algorithms Using Dominance Relations

Science.gov (United States)

Nedunuri, Srinivas; Smith, Douglas R.; Cook, William R.

2010-01-01

Greedy algorithms exploit problem structure and constraints to achieve linear-time performance. Yet there is still no completely satisfactory way of constructing greedy algorithms. For example, the Greedy Algorithm of Edmonds depends upon translating a problem into an algebraic structure called a matroid, but the existence of such a translation can be as hard to determine as the existence of a greedy algorithm itself. An alternative characterization of greedy algorithms is in terms of dominance relations, a well-known algorithmic technique used to prune search spaces. We demonstrate a process by which dominance relations can be methodically derived for a number of greedy algorithms, including activity selection, and prefix-free codes. By incorporating our approach into an existing framework for algorithm synthesis, we demonstrate that it could be the basis for an effective engineering method for greedy algorithms. We also compare our approach with other characterizations of greedy algorithms.

Fast parallel molecular algorithms for DNA-based computation: factoring integers.

Science.gov (United States)

Chang, Weng-Long; Guo, Minyi; Ho, Michael Shan-Hui

2005-06-01

The RSA public-key cryptosystem is an algorithm that converts input data to an unrecognizable encryption and converts the unrecognizable data back into its original decryption form. The security of the RSA public-key cryptosystem is based on the difficulty of factoring the product of two large prime numbers. This paper demonstrates to factor the product of two large prime numbers, and is a breakthrough in basic biological operations using a molecular computer. In order to achieve this, we propose three DNA-based algorithms for parallel subtractor, parallel comparator, and parallel modular arithmetic that formally verify our designed molecular solutions for factoring the product of two large prime numbers. Furthermore, this work indicates that the cryptosystems using public-key are perhaps insecure and also presents clear evidence of the ability of molecular computing to perform complicated mathematical operations.

Stochastic programming with integer recourse

NARCIS (Netherlands)

van der Vlerk, Maarten Hendrikus

1995-01-01

In this thesis we consider two-stage stochastic linear programming models with integer recourse. Such models are at the intersection of two different branches of mathematical programming. On the one hand some of the model parameters are random, which places the problem in the field of stochastic

Optimization in engineering models and algorithms

CERN Document Server

Sioshansi, Ramteen

2017-01-01

This textbook covers the fundamentals of optimization, including linear, mixed-integer linear, nonlinear, and dynamic optimization techniques, with a clear engineering focus. It carefully describes classical optimization models and algorithms using an engineering problem-solving perspective, and emphasizes modeling issues using many real-world examples related to a variety of application areas. Providing an appropriate blend of practical applications and optimization theory makes the text useful to both practitioners and students, and gives the reader a good sense of the power of optimization and the potential difficulties in applying optimization to modeling real-world systems. The book is intended for undergraduate and graduate-level teaching in industrial engineering and other engineering specialties. It is also of use to industry practitioners, due to the inclusion of real-world applications, opening the door to advanced courses on both modeling and algorithm development within the industrial engineering ...

Suppression of tunneling by interference in half-integer--spin particles

OpenAIRE

Loss, Daniel; DiVincenzo, David P.; Grinstein, G.

1992-01-01

Within a wide class of ferromagnetic and antiferromagnetic systems, quantum tunneling of magnetization direction is spin-parity dependent: it vanishes for magnetic particles with half-integer spin, but is allowed for integer spin. A coherent-state path integral calculation shows that this topological effect results from interference between tunneling paths.

Algorithms for Scheduling and Network Problems

Science.gov (United States)

1991-09-01

time. We already know, by Lemma 2.2.1, that WOPT = O(log( mpU )), so if we could solve this integer program optimally we would be done. However, the...Folydirat, 15:177-191, 1982. [6] I.S. Belov and Ya. N. Stolin. An algorithm in a single path operations scheduling problem. In Mathematical Economics and

7th Conference on Non-Integer Order Calculus and Its Applications

CERN Document Server

Dworak, Paweł

2016-01-01

This volume is devoted to presentation of new results of research on systems of non-integer order, called also fractional systems. Their analysis and practical implementation have been the object of spontaneous development for a few last decades. The fractional order models can depict a physical plant better than the classical integer order ones. This covers different research fields such as insulator properties, visco-elastic materials, electrodynamic, electrothermal, electrochemical, economic processes modelling etc. On the other hand fractional controllers often outperform their integer order counterparts. This volume contains new ideas and examples of implementation, theoretical and pure practical aspects of using a non-integer order calculus. It is divided into four parts covering: mathematical fundamentals, modeling and approximations, controllability, observability and stability problems and practical applications of fractional control systems. The first part expands the base of tools and methods of th...

A Separation Algorithm for Sources with Temporal Structure Only Using Second-order Statistics

Directory of Open Access Journals (Sweden)

J.G. Wang

2013-09-01

Full Text Available Unlike conventional blind source separation (BSS deals with independent identically distributed (i.i.d. sources, this paper addresses the separation from mixtures of sources with temporal structure, such as linear autocorrelations. Many sequential extraction algorithms have been reported, resulting in inevitable cumulated errors introduced by the deflation scheme. We propose a robust separation algorithm to recover original sources simultaneously, through a joint diagonalizer of several average delayed covariance matrices at positions of the optimal time delay and its integers. The proposed algorithm is computationally simple and efficient, since it is based on the second-order statistics only. Extensive simulation results confirm the validity and high performance of the algorithm. Compared with related extraction algorithms, its separation signal-to-noise rate for a desired source can reach 20dB higher, and it seems rather insensitive to the estimation error of the time delay.

Relative navigation and attitude determination using a GPS/INS integrated system near the International Space Station

Science.gov (United States)

Um, Jaeyong

2001-08-01

The Space Integrated GPS/INS (SIGI) sensor is the primary navigation and attitude determination source for the International Space Station (ISS). The SIGI was successfully demonstrated on-orbit for the first time in the SIGI Orbital Attitude Readiness (SOAR) demonstration on the Space Shuttle Atlantis in May 2000. Numerous proximity operations near the ISS have been and will be performed over the lifetime of the Station. The development of an autonomous relative navigation system is needed to improve the safety and efficiency of vehicle operations near the ISS. A hardware simulation study was performed for the GPS-based relative navigation using the state vector difference approach and the interferometric approach in the absence of multipath. The interferometric approach, where the relative states are estimated directly, showed comparable results for a 1 km baseline. One of the most pressing current technical issues is the design of an autonomous relative navigation system in the proximity of the ISS, where GPS signals are blocked and maneuvers happen frequently. An integrated GPS/INS system is investigated for the possibility of a fully autonomous relative navigation system. Another application of GPS measurements is determination of the vehicle's orientation in space. This study used the SOAR experiment data to characterize the SICI's on-orbit performance for attitude determination. A cold start initialization algorithm was developed for integer ambiguity resolution in any initial orientation. The original algorithm that was used in the SIGI had an operational limitation in the integer ambiguity resolution, which was developed for terrestrial applications, and limited its effectiveness in space. The new algorithm was tested using the SOAR data and has been incorporated in the current SIGI flight software. The attitude estimation performance was examined using two different GPS/INS integration algorithms. The GPS/INS attitude solution using the SOAR data was as

KERNEL MAD ALGORITHM FOR RELATIVE RADIOMETRIC NORMALIZATION

Directory of Open Access Journals (Sweden)

Y. Bai

2016-06-01

Full Text Available The multivariate alteration detection (MAD algorithm is commonly used in relative radiometric normalization. This algorithm is based on linear canonical correlation analysis (CCA which can analyze only linear relationships among bands. Therefore, we first introduce a new version of MAD in this study based on the established method known as kernel canonical correlation analysis (KCCA. The proposed method effectively extracts the non-linear and complex relationships among variables. We then conduct relative radiometric normalization experiments on both the linear CCA and KCCA version of the MAD algorithm with the use of Landsat-8 data of Beijing, China, and Gaofen-1(GF-1 data derived from South China. Finally, we analyze the difference between the two methods. Results show that the KCCA-based MAD can be satisfactorily applied to relative radiometric normalization, this algorithm can well describe the nonlinear relationship between multi-temporal images. This work is the first attempt to apply a KCCA-based MAD algorithm to relative radiometric normalization.

Deterministic integer multiple firing depending on initial state in Wang model

Energy Technology Data Exchange (ETDEWEB)

Xie Yong [Institute of Nonlinear Dynamics, MSSV, Department of Engineering Mechanics, Xi' an Jiaotong University, Xi' an 710049 (China)]. E-mail: yxie@mail.xjtu.edu.cn; Xu Jianxue [Institute of Nonlinear Dynamics, MSSV, Department of Engineering Mechanics, Xi' an Jiaotong University, Xi' an 710049 (China); Jiang Jun [Institute of Nonlinear Dynamics, MSSV, Department of Engineering Mechanics, Xi' an Jiaotong University, Xi' an 710049 (China)

2006-12-15

We investigate numerically dynamical behaviour of the Wang model, which describes the rhythmic activities of thalamic relay neurons. The model neuron exhibits Type I excitability from a global view, but Type II excitability from a local view. There exists a narrow range of bistability, in which a subthreshold oscillation and a suprathreshold firing behaviour coexist. A special firing pattern, integer multiple firing can be found in the certain part of the bistable range. The characteristic feature of such firing pattern is that the histogram of interspike intervals has a multipeaked structure, and the peaks are located at about integer multiples of a basic interspike interval. Since the Wang model is noise-free, the integer multiple firing is a deterministic firing pattern. The existence of bistability leads to the deterministic integer multiple firing depending on the initial state of the model neuron, i.e., the initial values of the state variables.

Deterministic integer multiple firing depending on initial state in Wang model

International Nuclear Information System (INIS)

Xie Yong; Xu Jianxue; Jiang Jun

2006-01-01

We investigate numerically dynamical behaviour of the Wang model, which describes the rhythmic activities of thalamic relay neurons. The model neuron exhibits Type I excitability from a global view, but Type II excitability from a local view. There exists a narrow range of bistability, in which a subthreshold oscillation and a suprathreshold firing behaviour coexist. A special firing pattern, integer multiple firing can be found in the certain part of the bistable range. The characteristic feature of such firing pattern is that the histogram of interspike intervals has a multipeaked structure, and the peaks are located at about integer multiples of a basic interspike interval. Since the Wang model is noise-free, the integer multiple firing is a deterministic firing pattern. The existence of bistability leads to the deterministic integer multiple firing depending on the initial state of the model neuron, i.e., the initial values of the state variables

5th Conference on Non-integer Order Calculus and Its Applications

CERN Document Server

Kacprzyk, Janusz; Baranowski, Jerzy

2013-01-01

This volume presents various aspects of non-integer order systems, also known as fractional systems, which have recently attracted an increasing attention in the scientific community of systems science, applied mathematics, control theory. Non-integer systems have become relevant for many fields of science and technology exemplified by the modeling of signal transmission, electric noise, dielectric polarization, heat transfer, electrochemical reactions, thermal processes,  acoustics, etc. The content is divided into six parts, every of which considers one of the currently relevant problems. In the first part the Realization problem is discussed, with a special focus on positive systems. The second part considers stability of certain classes of non-integer order systems with and without delays. The third part is focused on such important aspects as controllability, observability and optimization especially in discrete time. The fourth part is focused on distributed systems where non-integer calculus leads to ...

Stochastic cluster algorithms for discrete Gaussian (SOS) models

International Nuclear Information System (INIS)

Evertz, H.G.; Hamburg Univ.; Hasenbusch, M.; Marcu, M.; Tel Aviv Univ.; Pinn, K.; Muenster Univ.; Solomon, S.

1990-10-01

We present new Monte Carlo cluster algorithms which eliminate critical slowing down in the simulation of solid-on-solid models. In this letter we focus on the two-dimensional discrete Gaussian model. The algorithms are based on reflecting the integer valued spin variables with respect to appropriately chosen reflection planes. The proper choice of the reflection plane turns out to be crucial in order to obtain a small dynamical exponent z. Actually, the successful versions of our algorithm are a mixture of two different procedures for choosing the reflection plane, one of them ergodic but slow, the other one non-ergodic and also slow when combined with a Metropolis algorithm. (orig.)

Searching for optimal integer solutions to set partitioning problems using column generation

OpenAIRE

Bredström, David; Jörnsten, Kurt; Rönnqvist, Mikael

2007-01-01

We describe a new approach to produce integer feasible columns to a set partitioning problem directly in solving the linear programming (LP) relaxation using column generation. Traditionally, column generation is aimed to solve the LP relaxation as quick as possible without any concern of the integer properties of the columns formed. In our approach we aim to generate the columns forming the optimal integer solution while simultaneously solving the LP relaxation. By this we can re...

An Ant Colony Optimization and Hybrid Metaheuristics Algorithm to Solve the Split Delivery Vehicle Routing Problem

Science.gov (United States)

2015-01-01

solution approach that combines heuristic search and integer programming. Boudia et al. (2007) solved an SDVRP instance using a memetic algorithm with...Boudia, M., Prins, C., Reghioui, M., 2007. An effective memetic algorithm with population management for the split delivery vehicle routing problem

The use of mixed-integer programming for inverse treatment planning with pre-defined field segments

International Nuclear Information System (INIS)

Bednarz, Greg; Michalski, Darek; Houser, Chris; Huq, M. Saiful; Xiao Ying; Rani, Pramila Anne; Galvin, James M.

2002-01-01

Complex intensity patterns generated by traditional beamlet-based inverse treatment plans are often very difficult to deliver. In the approach presented in this work the intensity maps are controlled by pre-defining field segments to be used for dose optimization. A set of simple rules was used to define a pool of allowable delivery segments and the mixed-integer programming (MIP) method was used to optimize segment weights. The optimization problem was formulated by combining real variables describing segment weights with a set of binary variables, used to enumerate voxels in targets and critical structures. The MIP method was compared to the previously used Cimmino projection algorithm. The field segmentation approach was compared to an inverse planning system with a traditional beamlet-based beam intensity optimization. In four complex cases of oropharyngeal cancer the segmental inverse planning produced treatment plans, which competed with traditional beamlet-based IMRT plans. The mixed-integer programming provided mechanism for imposition of dose-volume constraints and allowed for identification of the optimal solution for feasible problems. Additional advantages of the segmental technique presented here are: simplified dosimetry, quality assurance and treatment delivery. (author)

DESIGN STUDY: INTEGER SUBTRACTION OPERATION TEACHING LEARNING USING MULTIMEDIA IN PRIMARY SCHOOL

Directory of Open Access Journals (Sweden)

Rendi Muhammad Aris

2016-12-01

Full Text Available This study aims to develop a learning trajectory to help students understand concept of subtraction of integers using multimedia in the fourth grade. This study is thematic integrative learning in Curriculum 2013 PMRI based. The method used is design research consists of three stages; preparing for the experiment, design experiment, retrospective analysis. The studied was conducted on 20 students of grade four SDN 1 Muara Batun, OKI. The activities of students in this study consisted of six learning trajectories. The first activity asks the students to classify heroism and non-heroism acts, summarize, and classify integers and non-integer. The second activity asks the students to answer the questions in the film given. The third activity asks students to count the remaining gravel in the film. The fourth activity asks students to count remaining spent money in the film. The fifth activity invites students to play rubber seeds in the bag. The last activity asks students to answer the questions in the student worksheet. The media used along the learning activities are a ruler, rubber seed, student worksheet, money, gravel, and film. The results indicate that the learning trajectory using multimedia help students understand the concept of integer subtraction integer. Keywords: Subtraction Integer, PMRI, Multimedia DOI: http://dx.doi.org/10.22342/jme.8.1.3233.95-102

A novel hybrid chaotic ant swarm algorithm for heat exchanger networks synthesis

International Nuclear Information System (INIS)

Zhang, Chunwei; Cui, Guomin; Peng, Fuyu

2016-01-01

Highlights: • The chaotic ant swarm algorithm is proposed to avoid trapping into a local optimum. • The organization variables update strategy makes full use of advantages of the chaotic search. • The structure evolution strategy is developed to handle integer variables optimization. • Overall three cases taken form the literatures are investigated with better optima. - Abstract: The heat exchanger networks synthesis (HENS) still remains an open problem due to its combinatorial nature, which can easily result in suboptimal design and unacceptable calculation effort. In this paper, a novel hybrid chaotic ant swarm algorithm is proposed. The presented algorithm, which consists of a combination of chaotic ant swarm (CAS) algorithm, structure evolution strategy, local optimization strategy and organization variables update strategy, can simultaneously optimize continuous variables and integer variables. The CAS algorithm chaotically searches and generates new solutions in the given space, and subsequently the structure evolution strategy evolves the structures represented by the solutions and limits the search space. Furthermore, the local optimizing strategy and the organization variables update strategy are introduced to enhance the performance of the algorithm. The study of three different cases, found in the literature, revealed special search abilities in both structure space and continuous variable space.

A low-resource quantum factoring algorithm

NARCIS (Netherlands)

Bernstein, D.J.; Biasse, J. F.; Mosca, M.; Lange, T.; Takagi, T.

2017-01-01

In this paper, we present a factoring algorithm that, assuming standard heuristics, uses just (log N)2/3+o(1) qubits to factor an integer N in time Lq+o(1) where L = exp((log N)1/3 (log log N)2/3) and q =3√8/3 ≈ 1.387. For comparison, the lowest asymptotic time complexity for known pre-quantum

District Heating Network Design and Configuration Optimization with Genetic Algorithm

DEFF Research Database (Denmark)

Li, Hongwei; Svendsen, Svend

2013-01-01

In this paper, the configuration of a district heating network which connects from the heating plant to the end users is optimized. Each end user in the network represents a building block. The connections between the heat generation plant and the end users are represented with mixed integer...... and the pipe friction and heat loss formulations are non-linear. In order to find the optimal district heating network configuration, genetic algorithm which handles the mixed integer nonlinear programming problem is chosen. The network configuration is represented with binary and integer encoding...... and it is optimized in terms of the net present cost. The optimization results indicates that the optimal DH network configuration is determined by multiple factors such as the consumer heating load, the distance between the heating plant to the consumer, the design criteria regarding the pressure and temperature...

Sabrewing: A lightweight architecture for combined floating-point and integer arithmetic

NARCIS (Netherlands)

Bruintjes, Tom; Walters, K.H.G.; Gerez, Sabih H.; Molenkamp, Egbert; Smit, Gerardus Johannes Maria

In spite of the fact that floating-point arithmetic is costly in terms of silicon area, the joint design of hardware for floating-point and integer arithmetic is seldom considered. While components like multipliers and adders can potentially be shared, floating-point and integer units in

Maximization Network Throughput Based on Improved Genetic Algorithm and Network Coding for Optical Multicast Networks

Science.gov (United States)

Wei, Chengying; Xiong, Cuilian; Liu, Huanlin

2017-12-01

Maximal multicast stream algorithm based on network coding (NC) can improve the network's throughput for wavelength-division multiplexing (WDM) networks, which however is far less than the network's maximal throughput in terms of theory. And the existing multicast stream algorithms do not give the information distribution pattern and routing in the meantime. In the paper, an improved genetic algorithm is brought forward to maximize the optical multicast throughput by NC and to determine the multicast stream distribution by hybrid chromosomes construction for multicast with single source and multiple destinations. The proposed hybrid chromosomes are constructed by the binary chromosomes and integer chromosomes, while the binary chromosomes represent optical multicast routing and the integer chromosomes indicate the multicast stream distribution. A fitness function is designed to guarantee that each destination can receive the maximum number of decoding multicast streams. The simulation results showed that the proposed method is far superior over the typical maximal multicast stream algorithms based on NC in terms of network throughput in WDM networks.

Reversible Integer Wavelet Transform for the Joint of Image Encryption and Watermarking

Directory of Open Access Journals (Sweden)

Bin Wang

2015-01-01

Full Text Available In recent years, signal processing in the encrypted domain has attracted considerable research interest, especially embedding watermarking in encrypted image. In this work, a novel joint of image encryption and watermarking based on reversible integer wavelet transform is proposed. Firstly, the plain-image is encrypted by chaotic maps and reversible integer wavelet transform. Then the lossless watermarking is embedded in the encrypted image by reversible integer wavelet transform and histogram modification. Finally an encrypted image containing watermarking is obtained by the inverse integer wavelet transform. What is more, the original image and watermarking can be completely recovered by inverse process. Numerical experimental results and comparing with previous works show that the proposed scheme possesses higher security and embedding capacity than previous works. It is suitable for protecting the image information.

Compute-unified device architecture implementation of a block-matching algorithm for multiple graphical processing unit cards.

Science.gov (United States)

Massanes, Francesc; Cadennes, Marie; Brankov, Jovan G

2011-07-01

In this paper we describe and evaluate a fast implementation of a classical block matching motion estimation algorithm for multiple Graphical Processing Units (GPUs) using the Compute Unified Device Architecture (CUDA) computing engine. The implemented block matching algorithm (BMA) uses summed absolute difference (SAD) error criterion and full grid search (FS) for finding optimal block displacement. In this evaluation we compared the execution time of a GPU and CPU implementation for images of various sizes, using integer and non-integer search grids.The results show that use of a GPU card can shorten computation time by a factor of 200 times for integer and 1000 times for a non-integer search grid. The additional speedup for non-integer search grid comes from the fact that GPU has built-in hardware for image interpolation. Further, when using multiple GPU cards, the presented evaluation shows the importance of the data splitting method across multiple cards, but an almost linear speedup with a number of cards is achievable.In addition we compared execution time of the proposed FS GPU implementation with two existing, highly optimized non-full grid search CPU based motion estimations methods, namely implementation of the Pyramidal Lucas Kanade Optical flow algorithm in OpenCV and Simplified Unsymmetrical multi-Hexagon search in H.264/AVC standard. In these comparisons, FS GPU implementation still showed modest improvement even though the computational complexity of FS GPU implementation is substantially higher than non-FS CPU implementation.We also demonstrated that for an image sequence of 720×480 pixels in resolution, commonly used in video surveillance, the proposed GPU implementation is sufficiently fast for real-time motion estimation at 30 frames-per-second using two NVIDIA C1060 Tesla GPU cards.

Genetic algorithms and fuzzy multiobjective optimization

CERN Document Server

Sakawa, Masatoshi

2002-01-01

Since the introduction of genetic algorithms in the 1970s, an enormous number of articles together with several significant monographs and books have been published on this methodology. As a result, genetic algorithms have made a major contribution to optimization, adaptation, and learning in a wide variety of unexpected fields. Over the years, many excellent books in genetic algorithm optimization have been published; however, they focus mainly on single-objective discrete or other hard optimization problems under certainty. There appears to be no book that is designed to present genetic algorithms for solving not only single-objective but also fuzzy and multiobjective optimization problems in a unified way. Genetic Algorithms And Fuzzy Multiobjective Optimization introduces the latest advances in the field of genetic algorithm optimization for 0-1 programming, integer programming, nonconvex programming, and job-shop scheduling problems under multiobjectiveness and fuzziness. In addition, the book treats a w...

Exergetic optimization of shell and tube heat exchangers using a genetic based algorithm

Energy Technology Data Exchange (ETDEWEB)

Oezcelik, Yavuz [Ege University, Bornova, Izmir (Turkey). Engineering Faculty, Chemical Engineering Department

2007-08-15

In the computer-based optimization, many thousands of alternative shell and tube heat exchangers may be examined by varying the high number of exchanger parameters such as tube length, tube outer diameter, pitch size, layout angle, baffle space ratio, number of tube side passes. In the present study, a genetic based algorithm was developed, programmed, and applied to estimate the optimum values of discrete and continuous variables of the MINLP (mixed integer nonlinear programming) test problems. The results of the test problems show that the genetic based algorithm programmed can estimate the acceptable values of continuous variables and optimum values of integer variables. Finally the genetic based algorithm was extended to make parametric studies and to find optimum configuration of heat exchangers by minimizing the sum of the annual capital cost and exergetic cost of the shell and tube heat exchangers. The results of the example problems show that the proposed algorithm is applicable to find optimum and near optimum alternatives of the shell and tube heat exchanger configurations. (author)

Introducing difference recurrence relations for faster semi-global alignment of long sequences.

Science.gov (United States)

Suzuki, Hajime; Kasahara, Masahiro

2018-02-19

The read length of single-molecule DNA sequencers is reaching 1 Mb. Popular alignment software tools widely used for analyzing such long reads often take advantage of single-instruction multiple-data (SIMD) operations to accelerate calculation of dynamic programming (DP) matrices in the Smith-Waterman-Gotoh (SWG) algorithm with a fixed alignment start position at the origin. Nonetheless, 16-bit or 32-bit integers are necessary for storing the values in a DP matrix when sequences to be aligned are long; this situation hampers the use of the full SIMD width of modern processors. We proposed a faster semi-global alignment algorithm, "difference recurrence relations," that runs more rapidly than the state-of-the-art algorithm by a factor of 2.1. Instead of calculating and storing all the values in a DP matrix directly, our algorithm computes and stores mainly the differences between the values of adjacent cells in the matrix. Although the SWG algorithm and our algorithm can output exactly the same result, our algorithm mainly involves 8-bit integer operations, enabling us to exploit the full width of SIMD operations (e.g., 32) on modern processors. We also developed a library, libgaba, so that developers can easily integrate our algorithm into alignment programs. Our novel algorithm and optimized library implementation will facilitate accelerating nucleotide long-read analysis algorithms that use pairwise alignment stages. The library is implemented in the C programming language and available at https://github.com/ocxtal/libgaba .

Stochastic integer programming by dynamic programming

NARCIS (Netherlands)

Lageweg, B.J.; Lenstra, J.K.; Rinnooy Kan, A.H.G.; Stougie, L.; Ermoliev, Yu.; Wets, R.J.B.

1988-01-01

Stochastic integer programming is a suitable tool for modeling hierarchical decision situations with combinatorial features. In continuation of our work on the design and analysis of heuristics for such problems, we now try to find optimal solutions. Dynamic programming techniques can be used to

Population transfer HMQC for half-integer quadrupolar nuclei

International Nuclear Information System (INIS)

Wang, Qiang; Xu, Jun; Feng, Ningdong; Deng, Feng; Li, Yixuan; Trébosc, Julien; Lafon, Olivier; Hu, Bingwen; Chen, Qun; Amoureux, Jean-Paul

2015-01-01

This work presents a detailed analysis of a recently proposed nuclear magnetic resonance method [Wang et al., Chem. Commun. 49(59), 6653-6655 (2013)] for accelerating heteronuclear coherence transfers involving half-integer spin quadrupolar nuclei by manipulating their satellite transitions. This method, called Population Transfer Heteronuclear Multiple Quantum Correlation (PT-HMQC), is investigated in details by combining theoretical analyses, numerical simulations, and experimental investigations. We find that compared to instant inversion or instant saturation, continuous saturation is the most practical strategy to accelerate coherence transfers on half-integer quadrupolar nuclei. We further demonstrate that this strategy is efficient to enhance the sensitivity of J-mediated heteronuclear correlation experiments between two half-integer quadrupolar isotopes (e.g., 27 Al- 17 O). In this case, the build-up is strongly affected by relaxation for small T 2 ′ and J coupling values, and shortening the mixing time makes a huge signal enhancement. Moreover, this concept of population transfer can also be applied to dipolar-mediated HMQC experiments. Indeed, on the AlPO 4 -14 sample, one still observes experimentally a 2-fold shortening of the optimum mixing time albeit with no significant signal gain in the 31 P-( 27 Al) experiments

Edge states and integer quantum Hall effect in topological insulator thin films.

Science.gov (United States)

Zhang, Song-Bo; Lu, Hai-Zhou; Shen, Shun-Qing

2015-08-25

The integer quantum Hall effect is a topological state of quantum matter in two dimensions, and has recently been observed in three-dimensional topological insulator thin films. Here we study the Landau levels and edge states of surface Dirac fermions in topological insulators under strong magnetic field. We examine the formation of the quantum plateaux of the Hall conductance and find two different patterns, in one pattern the filling number covers all integers while only odd integers in the other. We focus on the quantum plateau closest to zero energy and demonstrate the breakdown of the quantum spin Hall effect resulting from structure inversion asymmetry. The phase diagrams of the quantum Hall states are presented as functions of magnetic field, gate voltage and chemical potential. This work establishes an intuitive picture of the edge states to understand the integer quantum Hall effect for Dirac electrons in topological insulator thin films.

Mixed-integer programming methods for transportation and power generation problems

Science.gov (United States)

Damci Kurt, Pelin

This dissertation conducts theoretical and computational research to solve challenging problems in application areas such as supply chain and power systems. The first part of the dissertation studies a transportation problem with market choice (TPMC) which is a variant of the classical transportation problem in which suppliers with limited capacities have a choice of which demands (markets) to satisfy. We show that TPMC is strongly NP-complete. We consider a version of the problem with a service level constraint on the maximum number of markets that can be rejected and show that if the original problem is polynomial, its cardinality-constrained version is also polynomial. We propose valid inequalities for mixed-integer cover and knapsack sets with variable upper bound constraints, which appear as substructures of TPMC and use them in a branch-and-cut algorithm to solve this problem. The second part of this dissertation studies a unit commitment (UC) problem in which the goal is to minimize the operational cost of power generators over a time period subject to physical constraints while satisfying demand. We provide several exponential classes of multi-period ramping and multi-period variable upper bound inequalities. We prove the strength of these inequalities and describe polynomial-time separation algorithms. Computational results show the effectiveness of the proposed inequalities when used as cuts in a branch-and-cut algorithm to solve the UC problem. The last part of this dissertation investigates the effects of uncertain wind power on the UC problem. A two-stage robust model and a three-stage stochastic program are compared.

Network interdiction and stochastic integer programming

CERN Document Server

2003-01-01

On March 15, 2002 we held a workshop on network interdiction and the more general problem of stochastic mixed integer programming at the University of California, Davis. Jesús De Loera and I co-chaired the event, which included presentations of on-going research and discussion. At the workshop, we decided to produce a volume of timely work on the topics. This volume is the result. Each chapter represents state-of-the-art research and all of them were refereed by leading investigators in the respective fields. Problems - sociated with protecting and attacking computer, transportation, and social networks gain importance as the world becomes more dep- dent on interconnected systems. Optimization models that address the stochastic nature of these problems are an important part of the research agenda. This work relies on recent efforts to provide methods for - dressing stochastic mixed integer programs. The book is organized with interdiction papers first and the stochastic programming papers in the second part....

Detecting perfect powers by factoring into coprimes

NARCIS (Netherlands)

Bernstein, D.J.; Lenstra, H.W.; Pila, J.

2007-01-01

This paper presents an algorithm that, given an integer , finds the largest integer such that is a th power. A previous algorithm by the first author took time where ; more precisely, time ; conjecturally, time . The new algorithm takes time . It relies on relatively complicated

Elasticity of fractal materials using the continuum model with non-integer dimensional space

Science.gov (United States)

Tarasov, Vasily E.

2015-01-01

Using a generalization of vector calculus for space with non-integer dimension, we consider elastic properties of fractal materials. Fractal materials are described by continuum models with non-integer dimensional space. A generalization of elasticity equations for non-integer dimensional space, and its solutions for the equilibrium case of fractal materials are suggested. Elasticity problems for fractal hollow ball and cylindrical fractal elastic pipe with inside and outside pressures, for rotating cylindrical fractal pipe, for gradient elasticity and thermoelasticity of fractal materials are solved.

A note on number fields having reciprocal integer generators | Zaïmi ...

African Journals Online (AJOL)

We prove that a totally complex algebraic number field K; having a conjugate which is not closed under complex conjugation, can be generated by a reciprocal integer, when the Galois group of its normal closure is contained in the hyperoctahedral group Bdeg(K)/2. Keywords: Reciprocal integers, unit primitive elements, ...

Predecessor queries in dynamic integer sets

DEFF Research Database (Denmark)

Brodal, Gerth Stølting

1997-01-01

We consider the problem of maintaining a set of n integers in the range 0.2w–1 under the operations of insertion, deletion, predecessor queries, minimum queries and maximum queries on a unit cost RAM with word size w bits. Let f (n) be an arbitrary nondecreasing smooth function satisfying n...

Vector calculus in non-integer dimensional space and its applications to fractal media

Science.gov (United States)

Tarasov, Vasily E.

2015-02-01

We suggest a generalization of vector calculus for the case of non-integer dimensional space. The first and second orders operations such as gradient, divergence, the scalar and vector Laplace operators for non-integer dimensional space are defined. For simplification we consider scalar and vector fields that are independent of angles. We formulate a generalization of vector calculus for rotationally covariant scalar and vector functions. This generalization allows us to describe fractal media and materials in the framework of continuum models with non-integer dimensional space. As examples of application of the suggested calculus, we consider elasticity of fractal materials (fractal hollow ball and fractal cylindrical pipe with pressure inside and outside), steady distribution of heat in fractal media, electric field of fractal charged cylinder. We solve the correspondent equations for non-integer dimensional space models.

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...

An Enhanced OFDM Resource Allocation Algorithm in C-RAN Based 5G Public Safety Network

Directory of Open Access Journals (Sweden)

Lei Feng

2016-01-01

Full Text Available Public Safety Network (PSN is the network for critical communication when disaster occurs. As a key technology in 5G, Cloud-Radio Access Network (C-RAN can play an important role in PSN instead of LTE-based RAN. This paper firstly introduces C-RAN based PSN architecture and models the OFDM resource allocation problem in C-RAN based PSN as an integer quadratic programming, which allows the trade-off between expected bitrates and allocating fairness of PSN Service User (PSU. However, C-RAN based PSN needs to improve the efficiency of allocating algorithm because of a mass of PSU-RRH associations when disaster occurs. To deal with it, the resources allocating problem with integer variables is relaxed into one with continuous variables in the first step and an algorithm based on Generalized Bender’s Decomposition (GBD is proposed to solve it. Then we use Feasible Pump (FP method to get a feasible integer solution on the original OFDM resources allocation problem. The final experiments show the total throughput achieved by C-RAN based PSN is at most higher by 19.17% than the LTE-based one. And the average computational time of the proposed GBD and FP algorithm is at most lower than Barrier by 51.5% and GBD with no relaxation by 30.1%, respectively.

Nonlinear feedback synchronisation control between fractional-order and integer-order chaotic systems

International Nuclear Information System (INIS)

Jia Li-Xin; Dai Hao; Hui Meng

2010-01-01

This paper focuses on the synchronisation between fractional-order and integer-order chaotic systems. Based on Lyapunov stability theory and numerical differentiation, a nonlinear feedback controller is obtained to achieve the synchronisation between fractional-order and integer-order chaotic systems. Numerical simulation results are presented to illustrate the effectiveness of this method

An introduction to quantum computing algorithms

CERN Document Server

Pittenger, Arthur O

2000-01-01

In 1994 Peter Shor [65] published a factoring algorithm for a quantum computer that finds the prime factors of a composite integer N more efficiently than is possible with the known algorithms for a classical com­ puter. Since the difficulty of the factoring problem is crucial for the se­ curity of a public key encryption system, interest (and funding) in quan­ tum computing and quantum computation suddenly blossomed. Quan­ tum computing had arrived. The study of the role of quantum mechanics in the theory of computa­ tion seems to have begun in the early 1980s with the publications of Paul Benioff [6]' [7] who considered a quantum mechanical model of computers and the computation process. A related question was discussed shortly thereafter by Richard Feynman [35] who began from a different perspec­ tive by asking what kind of computer should be used to simulate physics. His analysis led him to the belief that with a suitable class of "quantum machines" one could imitate any quantum system.

Linear Independence of -Logarithms over the Eisenstein Integers

Directory of Open Access Journals (Sweden)

Peter Bundschuh

2010-01-01

Full Text Available For fixed complex with ||>1, the -logarithm is the meromorphic continuation of the series ∑>0/(−1,||1,≠,2,3,…. In 2004, Tachiya showed that this is true in the Subcase =ℚ, ∈ℤ, =−1, and the present authors extended this result to arbitrary integer from an imaginary quadratic number field , and provided a quantitative version. In this paper, the earlier method, in particular its arithmetical part, is further developed to answer the above question in the affirmative if is the Eisenstein number field √ℚ(−3, an integer from , and a primitive third root of unity. Under these conditions, the linear independence holds also for 1,(,(−1, and both results are quantitative.

Application of a non-integer Bessel uniform approximation to inelastic molecular collisions

International Nuclear Information System (INIS)

Connor, J.N.L.; Mayne, H.R.

1979-01-01

A non-integer Bessel uniform approximation has been used to calculate transition probabilities for collinear atom-oscillator collisions. The collision systems used are a harmonic oscillator interacting via a Lennard-Jones potential and a Morse oscillator interacting via an exponential potential. Both classically allowed and classically forbidden transitions have been treated. The order of the Bessel function is chosen by a physical argument that makes use of information contained in the final-action initial-angle plot. Limitations of this procedure are discussed. It is shown that the non-integer Bessel approximation is accurate for elastic 0 → 0 collisions at high collision energies, where the integer Bessel approximation is inaccurate or inapplicable. (author)

Fast half-sibling population reconstruction: theory and algorithms.

Science.gov (United States)

Dexter, Daniel; Brown, Daniel G

2013-07-12

Kinship inference is the task of identifying genealogically related individuals. Kinship information is important for determining mating structures, notably in endangered populations. Although many solutions exist for reconstructing full sibling relationships, few exist for half-siblings. We consider the problem of determining whether a proposed half-sibling population reconstruction is valid under Mendelian inheritance assumptions. We show that this problem is NP-complete and provide a 0/1 integer program that identifies the minimum number of individuals that must be removed from a population in order for the reconstruction to become valid. We also present SibJoin, a heuristic-based clustering approach based on Mendelian genetics, which is strikingly fast. The software is available at http://github.com/ddexter/SibJoin.git+. Our SibJoin algorithm is reasonably accurate and thousands of times faster than existing algorithms. The heuristic is used to infer a half-sibling structure for a population which was, until recently, too large to evaluate.

Integer factoring and modular square roots

Czech Academy of Sciences Publication Activity Database

Jeřábek, Emil

2016-01-01

Roč. 82, č. 2 (2016), s. 380-394 ISSN 0022-0000 R&D Projects: GA AV ČR IAA100190902; GA ČR GBP202/12/G061 Institutional support: RVO:67985840 Keywords : integer factoring * quadratic residue * PPA Subject RIV: BA - General Mathematics Impact factor: 1.678, year: 2016 http://www.sciencedirect.com/science/article/pii/S0022000015000768

Low Cost Design of a Hybrid Architecture of Integer Inverse DCT for H.264, VC-1, AVS, and HEVC

Directory of Open Access Journals (Sweden)

Muhammad Martuza

2012-01-01

Full Text Available The paper presents a unified hybrid architecture to compute the 8×8 integer inverse discrete cosine transform (IDCT of multiple modern video codecs—AVS, H.264/AVC, VC-1, and HEVC (under development. Based on the symmetric structure of the matrices and the similarity in matrix operation, we develop a generalized “decompose and share” algorithm to compute the 8×8 IDCT. The algorithm is later applied to four video standards. The hardware-share approach ensures the maximum circuit reuse during the computation. The architecture is designed with only adders and shifters to reduce the hardware cost significantly. The design is implemented on FPGA and later synthesized in CMOS 0.18 um technology. The results meet the requirements of advanced video coding applications.

Two-Phase Algorithm for Optimal Camera Placement

Directory of Open Access Journals (Sweden)

Jun-Woo Ahn

2016-01-01

Full Text Available As markers for visual sensor networks have become larger, interest in the optimal camera placement problem has continued to increase. The most featured solution for the optimal camera placement problem is based on binary integer programming (BIP. Due to the NP-hard characteristic of the optimal camera placement problem, however, it is difficult to find a solution for a complex, real-world problem using BIP. Many approximation algorithms have been developed to solve this problem. In this paper, a two-phase algorithm is proposed as an approximation algorithm based on BIP that can solve the optimal camera placement problem for a placement space larger than in current studies. This study solves the problem in three-dimensional space for a real-world structure.

Split diversity in constrained conservation prioritization using integer linear programming.

Science.gov (United States)

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

2015-01-01

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

A Fast and High-precision Orientation Algorithm for BeiDou Based on Dimensionality Reduction

Directory of Open Access Journals (Sweden)

ZHAO Jiaojiao

2015-05-01

Full Text Available A fast and high-precision orientation algorithm for BeiDou is proposed by deeply analyzing the constellation characteristics of BeiDou and GEO satellites features.With the advantage of good east-west geometry, the baseline vector candidate values were solved by the GEO satellites observations combined with the dimensionality reduction theory at first.Then, we use the ambiguity function to judge the values in order to obtain the optical baseline vector and get the wide lane integer ambiguities. On this basis, the B1 ambiguities were solved. Finally, the high-precision orientation was estimated by the determinating B1 ambiguities. This new algorithm not only can improve the ill-condition of traditional algorithm, but also can reduce the ambiguity search region to a great extent, thus calculating the integer ambiguities in a single-epoch.The algorithm is simulated by the actual BeiDou ephemeris and the result shows that the method is efficient and fast for orientation. It is capable of very high single-epoch success rate(99.31% and accurate attitude angle (the standard deviation of pitch and heading is respectively 0.07°and 0.13°in a real time and dynamic environment.

Relative Pose Estimation Algorithm with Gyroscope Sensor

Directory of Open Access Journals (Sweden)

Shanshan Wei

2016-01-01

Full Text Available This paper proposes a novel vision and inertial fusion algorithm S2fM (Simplified Structure from Motion for camera relative pose estimation. Different from current existing algorithms, our algorithm estimates rotation parameter and translation parameter separately. S2fM employs gyroscopes to estimate camera rotation parameter, which is later fused with the image data to estimate camera translation parameter. Our contributions are in two aspects. (1 Under the circumstance that no inertial sensor can estimate accurately enough translation parameter, we propose a translation estimation algorithm by fusing gyroscope sensor and image data. (2 Our S2fM algorithm is efficient and suitable for smart devices. Experimental results validate efficiency of the proposed S2fM algorithm.

Obstacles and Affordances for Integer Reasoning: An Analysis of Children's Thinking and the History of Mathematics

Science.gov (United States)

Bishop, Jessica Pierson; Lamb, Lisa L.; Philipp, Randolph A.; Whitacre, Ian; Schappelle, Bonnie P.; Lewis, Melinda L.

2014-01-01

We identify and document 3 cognitive obstacles, 3 cognitive affordances, and 1 type of integer understanding that can function as either an obstacle or affordance for learners while they extend their numeric domains from whole numbers to include negative integers. In particular, we highlight 2 key subsets of integer reasoning: understanding or…

Solving a mixed-integer linear programming model for a multi-skilled project scheduling problem by simulated annealing

Directory of Open Access Journals (Sweden)

H Kazemipoor

2012-04-01

Full Text Available A multi-skilled project scheduling problem (MSPSP has been generally presented to schedule a project with staff members as resources. Each activity in project network requires different skills and also staff members have different skills, too. This causes the MSPSP becomes a special type of a multi-mode resource-constrained project scheduling problem (MM-RCPSP with a huge number of modes. Given the importance of this issue, in this paper, a mixed integer linear programming for the MSPSP is presented. Due to the complexity of the problem, a meta-heuristic algorithm is proposed in order to find near optimal solutions. To validate performance of the algorithm, results are compared against exact solutions solved by the LINGO solver. The results are promising and show that optimal or near-optimal solutions are derived for small instances and good solutions for larger instances in reasonable time.

Mixed integer (0-1) fractional programming for decision support in paper production industry

NARCIS (Netherlands)

Claassen, G.D.H.

2014-01-01

This paper presents an effective and efficient method for solving a special class of mixed integer fractional programming (FP) problems. We take a classical reformulation approach for continuous FP as a starting point and extend it for solving a more general class of mixed integer (0–1) fractional

Optimization of source pencil deployment based on plant growth simulation algorithm

International Nuclear Information System (INIS)

Yang Lei; Liu Yibao; Liu Yujuan

2009-01-01

A plant growth simulation algorithm was proposed for optimizing source pencil deployment for a 60 Co irradiator. A method used to evaluate the calculation results was presented with the objective function defined by relative standard deviation of the exposure rate at the reference points, and the method to transform two kinds of control variables, i.e., position coordinates x j and y j of source pencils in the source plaque, into proper integer variables was also analyzed and solved. The results show that the plant growth simulation algorithm, which possesses both random and directional search mechanism, has good global search ability and can be used conveniently. The results are affected a little by initial conditions, and improve the uniformity in the irradiation fields. It creates a dependable field for the optimization of source bars arrangement at irradiation facility. (authors)

An Integer Programming Model for Multi-Echelon Supply Chain Decision Problem Considering Inventories

Science.gov (United States)

Harahap, Amin; Mawengkang, Herman; Siswadi; Effendi, Syahril

2018-01-01

In this paper we address a problem that is of significance to the industry, namely the optimal decision of a multi-echelon supply chain and the associated inventory systems. By using the guaranteed service approach to model the multi-echelon inventory system, we develop a mixed integer; programming model to simultaneously optimize the transportation, inventory and network structure of a multi-echelon supply chain. To solve the model we develop a direct search approach using a strategy of releasing nonbasic variables from their bounds, combined with the “active constraint” method. This strategy is used to force the appropriate non-integer basic variables to move to their neighbourhood integer points.

An Efficient Integer Coding and Computing Method for Multiscale Time Segment

Directory of Open Access Journals (Sweden)

TONG Xiaochong

2016-12-01

Full Text Available This article focus on the exist problem and status of current time segment coding, proposed a new set of approach about time segment coding: multi-scale time segment integer coding (MTSIC. This approach utilized the tree structure and the sort by size formed among integer, it reflected the relationship among the multi-scale time segments: order, include/contained, intersection, etc., and finally achieved an unity integer coding processing for multi-scale time. On this foundation, this research also studied the computing method for calculating the time relationships of MTSIC, to support an efficient calculation and query based on the time segment, and preliminary discussed the application method and prospect of MTSIC. The test indicated that, the implement of MTSIC is convenient and reliable, and the transformation between it and the traditional method is convenient, it has the very high efficiency in query and calculating.

Load Frequency Control in Microgrids Based on a Stochastic Non-Integer Controller

DEFF Research Database (Denmark)

Khooban, Mohammad-Hassan; Niknam, Taher; Shasadeghi, Mokhtar

2018-01-01

of battery energy storage systems (BESS) can solve the unbalance effects between the load and supply of an isolated MG, their high cost and tendency toward degradation are restrictive factors, which call for the use of alternative power balancing options. In recent years, the concept of utilizing the BESSs...... of EVs, also known as vehicle-to-grid (V2G) concept, for frequency support of MGs has attracted a lot of attention. In order to allow the V2G controller operate optimally under a wide range of operation conditions caused by the intermittent behavior of renewable energy resources (RESs), a new multi...... hole optimization algorithm (MBHA) is utilized for the adaptive tuning of the non-integer fuzzy PID controller coefficients. The performance of the proposed LFC is evaluated by using real world wind and solar radiation data. Finally, the extensive studies and hardware-in-the-loop (HIL) simulations...

Bivium as a Mixed Integer Programming Problem

DEFF Research Database (Denmark)

Borghoff, Julia; Knudsen, Lars Ramkilde; Stolpe, Mathias

2009-01-01

over $GF(2)$ into a combinatorial optimization problem. We convert the Boolean equation system into an equation system over $\\mathbb{R}$ and formulate the problem of finding a $0$-$1$-valued solution for the system as a mixed-integer programming problem. This enables us to make use of several...

A deterministic algorithm for fitting a step function to a weighted point-set

KAUST Repository

Fournier, Hervé ; Vigneron, Antoine E.

2013-01-01

Given a set of n points in the plane, each point having a positive weight, and an integer k>0, we present an optimal O(nlogn)-time deterministic algorithm to compute a step function with k steps that minimizes the maximum weighted vertical distance

OPTIMASI CUTTING STOCK PADA INDUSTRI PEMOTONGAN KERTAS DENGAN MENGGUNAKAN METODE INTEGER LINEAR PROGRAMMING (Studi Kasus di Bhinneka – Semarang

Directory of Open Access Journals (Sweden)

Denny Nurkertamanda

2012-02-01

Full Text Available In paper cutting industry, cutting stock problem (CSP is a problem about how to cutting paper depends on quantity and specify of the demand. CSP related with dimension of pieces and rectangle which is use. In this research, we use one type dimension of rectangle and six type dimension of pieces and cutting all paper by two stage guillotine pattern. The major focus of this research is to formulate the paper cutting problem using integer linear programming. Cutting large objects into small pieces can be found in many industries. Inevitably, the cutting processes produce trim loss. On the rectangle we can put some different dimension of pieces then we can make certain pattern. The modification pattern have to produce minimum trim loss. Thus to develop optimal cutting pattern to reduce trim loss is the main purpose of this research. To reach that, we use branch and bound algorithm then continued with sensitivity analysis.  From the research, we get optimum patten of paper cutting and quantity production for that pattern. Decision for quantity production depends on average demand every day. Beside that, we also give some alternative rules of production system which can take by the company.   Keywords :   Cutting stock problem, two stage guillotine pattern, branch and bound algorithm

Integers in number systems with positive and negative quadratic Pisot base

OpenAIRE

Masáková, Zuzana; Vávra, Tomáš

2013-01-01

We consider numeration systems with base $\\beta$ and $-\\beta$, for quadratic Pisot numbers $\\beta$ and focus on comparing the combinatorial structure of the sets $\\Z_\\beta$ and $\\Z_{-\\beta}$ of numbers with integer expansion in base $\\beta$, resp. $-\\beta$. Our main result is the comparison of languages of infinite words $u_\\beta$ and $u_{-\\beta}$ coding the ordering of distances between consecutive $\\beta$- and $(-\\beta)$-integers. It turns out that for a class of roots $\\beta$ of $x^2-mx-m$...

Optimization of Product Instantiation using Integer Programming

NARCIS (Netherlands)

van den Broek, P.M.; Botterweck, Goetz; Jarzabek, Stan; Kishi, Tomoji

2010-01-01

We show that Integer Programming (IP) can be used as an optimization technique for the instantiation of products of feature models. This is done by showing that the constraints of feature models can be written in linear form. As particular IP technique, we use Gomory cutting planes. We have applied

A high accuracy algorithm of displacement measurement for a micro-positioning stage

Directory of Open Access Journals (Sweden)

Xiang Zhang

2017-05-01

Full Text Available A high accuracy displacement measurement algorithm for a two degrees of freedom compliant precision micro-positioning stage is proposed based on the computer micro-vision technique. The algorithm consists of an integer-pixel and a subpixel matching procedure. Series of simulations are conducted to verify the proposed method. The results show that the proposed algorithm possesses the advantages of high precision and stability, the resolution can attain to 0.01 pixel theoretically. In addition, the consuming time is reduced about 6.7 times compared with the classical normalized cross correlation algorithm. To validate the practical performance of the proposed algorithm, a laser interferometer measurement system (LIMS is built up. The experimental results demonstrate that the algorithm has better adaptability than that of the LIMS.

A polynomial time algorithm for solving the maximum flow problem in directed networks

International Nuclear Information System (INIS)

Tlas, M.

2015-01-01

An efficient polynomial time algorithm for solving maximum flow problems has been proposed in this paper. The algorithm is basically based on the binary representation of capacities; it solves the maximum flow problem as a sequence of O(m) shortest path problems on residual networks with nodes and m arcs. It runs in O(m"2r) time, where is the smallest integer greater than or equal to log B , and B is the largest arc capacity of the network. A numerical example has been illustrated using this proposed algorithm.(author)

Single Allocation Hub-and-spoke Networks Design Based on Ant Colony Optimization Algorithm

Directory of Open Access Journals (Sweden)

Yang Pingle

2014-10-01

Full Text Available Capacitated single allocation hub-and-spoke networks can be abstracted as a mixed integer linear programming model equation with three variables. Introducing an improved ant colony algorithm, which has six local search operators. Meanwhile, introducing the "Solution Pair" concept to decompose and optimize the composition of the problem, the problem can become more specific and effectively meet the premise and advantages of using ant colony algorithm. Finally, location simulation experiment is made according to Australia Post data to demonstrate this algorithm has good efficiency and stability for solving this problem.

A fuzzy mixed integer programming for marketing planning

Directory of Open Access Journals (Sweden)

Abolfazl Danaei

2014-03-01

Full Text Available One of the primary concerns to market a product is to find appropriate channel to target customers. The recent advances on information technology have created new products with tremendous opportunities. This paper presents a mixed integer programming technique based on McCarthy's 4PS to locate suitable billboards for marketing newly introduced IPHONE product. The paper considers two types of information including age and income and tries to find the best places such that potential consumers aged 25-35 with high income visit the billboards and the cost of advertisement is minimized. The model is formulated in terms of mixed integer programming and it has been applied for potential customers who live in city of Tabriz, Iran. Using a typical software package, the model detects appropriate places in various parts of the city.

Spin chain simulations with a meron cluster algorithm

International Nuclear Information System (INIS)

Boyer, T.; Bietenholz, W.; Deutsches Elektronen-Synchrotron; Wuilloud, J.; Geneve Univ.

2007-01-01

We apply a meron cluster algorithm to the XY spin chain, which describes a quantum rotor. This is a multi-cluster simulation supplemented by an improved estimator, which deals with objects of half-integer topological charge. This method is powerful enough to provide precise results for the model with a θ-term - it is therefore one of the rare examples, where a system with a complex action can be solved numerically. In particular we measure the correlation length, as well as the topological and magnetic susceptibility. We discuss the algorithmic efficiency in view of the critical slowing down. Due to the excellent performance that we observe, it is strongly motivated to work on new applications of meron cluster algorithms in higher dimensions. (orig.)

Fabry-Perot Interferometry in the Integer and Fractional Quantum Hall Regimes

Science.gov (United States)

McClure, Douglas; Chang, Willy; Kou, Angela; Marcus, Charles; Pfeiffer, Loren; West, Ken

2011-03-01

We present measurements of electronic Fabry-Perot interferometers in the integer and fractional quantum Hall regimes. Two classes of resistance oscillations may be seen as a function of magnetic field and gate voltage, as we have previously reported. In small interferometers in the integer regime, oscillations of the type associated with Coulomb interaction are ubiquitous, while those consistent with single-particle Aharonov-Bohm interference are seen to co-exist in some configurations. The amplitude scaling of both types with temperature and device size is consistent with a theoretical model. Oscillations are further observed in the fractional quantum Hall regime. Here the dependence of the period on the filling factors in the constrictions and bulk of the interferometer can shed light on the effective charge of the interfering quasiparticles, but care is needed to distinguish these oscillations from those associated with integer quantum Hall states. We acknowledge funding from Microsoft Project Q and IBM.

PARALLEL ADAPTIVE MULTILEVEL SAMPLING ALGORITHMS FOR THE BAYESIAN ANALYSIS OF MATHEMATICAL MODELS

KAUST Repository

Prudencio, Ernesto; Cheung, Sai Hung

2012-01-01

In recent years, Bayesian model updating techniques based on measured data have been applied to many engineering and applied science problems. At the same time, parallel computational platforms are becoming increasingly more powerful and are being used more frequently by the engineering and scientific communities. Bayesian techniques usually require the evaluation of multi-dimensional integrals related to the posterior probability density function (PDF) of uncertain model parameters. The fact that such integrals cannot be computed analytically motivates the research of stochastic simulation methods for sampling posterior PDFs. One such algorithm is the adaptive multilevel stochastic simulation algorithm (AMSSA). In this paper we discuss the parallelization of AMSSA, formulating the necessary load balancing step as a binary integer programming problem. We present a variety of results showing the effectiveness of load balancing on the overall performance of AMSSA in a parallel computational environment.

Improved GPS-based Satellite Relative Navigation Using Femtosecond Laser Relative Distance Measurements

Directory of Open Access Journals (Sweden)

Hyungjik Oh

2016-03-01

Full Text Available This study developed an approach for improving Carrier-phase Differential Global Positioning System (CDGPS based realtime satellite relative navigation by applying laser baseline measurement data. The robustness against the space operational environment was considered, and a Synthetic Wavelength Interferometer (SWI algorithm based on a femtosecond laser measurement model was developed. The phase differences between two laser wavelengths were combined to measure precise distance. Generated laser data were used to improve estimation accuracy for the float ambiguity of CDGPS data. Relative navigation simulations in real-time were performed using the extended Kalman filter algorithm. The GPS and laser-combined relative navigation accuracy was compared with GPS-only relative navigation solutions to determine the impact of laser data on relative navigation. In numerical simulations, the success rate of integer ambiguity resolution increased when laser data was added to GPS data. The relative navigational errors also improved five-fold and two-fold, relative to the GPS-only error, for 250 m and 5 km initial relative distances, respectively. The methodology developed in this study is suitable for application to future satellite formation-flying missions.

An improved cut-and-solve algorithm for the single-source capacitated facility location problem

DEFF Research Database (Denmark)

Gadegaard, Sune Lauth; Klose, Andreas; Nielsen, Lars Relund

2018-01-01

In this paper, we present an improved cut-and-solve algorithm for the single-source capacitated facility location problem. The algorithm consists of three phases. The first phase strengthens the integer program by a cutting plane algorithm to obtain a tight lower bound. The second phase uses a two......-level local branching heuristic to find an upper bound, and if optimality has not yet been established, the third phase uses the cut-and-solve framework to close the optimality gap. Extensive computational results are reported, showing that the proposed algorithm runs 10–80 times faster on average compared...

An Integer Batch Scheduling Model for a Single Machine with Simultaneous Learning and Deterioration Effects to Minimize Total Actual Flow Time

Science.gov (United States)

Yusriski, R.; Sukoyo; Samadhi, T. M. A. A.; Halim, A. H.

2016-02-01

In the manufacturing industry, several identical parts can be processed in batches, and setup time is needed between two consecutive batches. Since the processing times of batches are not always fixed during a scheduling period due to learning and deterioration effects, this research deals with batch scheduling problems with simultaneous learning and deterioration effects. The objective is to minimize total actual flow time, defined as a time interval between the arrival of all parts at the shop and their common due date. The decision variables are the number of batches, integer batch sizes, and the sequence of the resulting batches. This research proposes a heuristic algorithm based on the Lagrange Relaxation. The effectiveness of the proposed algorithm is determined by comparing the resulting solutions of the algorithm to the respective optimal solution obtained from the enumeration method. Numerical experience results show that the average of difference among the solutions is 0.05%.

An Integer Batch Scheduling Model for a Single Machine with Simultaneous Learning and Deterioration Effects to Minimize Total Actual Flow Time

International Nuclear Information System (INIS)

Yusriski, R; Sukoyo; Samadhi, T M A A; Halim, A H

2016-01-01

In the manufacturing industry, several identical parts can be processed in batches, and setup time is needed between two consecutive batches. Since the processing times of batches are not always fixed during a scheduling period due to learning and deterioration effects, this research deals with batch scheduling problems with simultaneous learning and deterioration effects. The objective is to minimize total actual flow time, defined as a time interval between the arrival of all parts at the shop and their common due date. The decision variables are the number of batches, integer batch sizes, and the sequence of the resulting batches. This research proposes a heuristic algorithm based on the Lagrange Relaxation. The effectiveness of the proposed algorithm is determined by comparing the resulting solutions of the algorithm to the respective optimal solution obtained from the enumeration method. Numerical experience results show that the average of difference among the solutions is 0.05%. (paper)

When do evolutionary algorithms optimize separable functions in parallel?

DEFF Research Database (Denmark)

Doerr, Benjamin; Sudholt, Dirk; Witt, Carsten

2013-01-01

is that evolutionary algorithms make progress on all subfunctions in parallel, so that optimizing a separable function does not take not much longer than optimizing the hardest subfunction-subfunctions are optimized "in parallel." We show that this is only partially true, already for the simple (1+1) evolutionary...... algorithm ((1+1) EA). For separable functions composed of k Boolean functions indeed the optimization time is the maximum optimization time of these functions times a small O(log k) overhead. More generally, for sums of weighted subfunctions that each attain non-negative integer values less than r = o(log1...

A simplicial algorithm for testing the integral properties of polytopes : A revision

NARCIS (Netherlands)

Yang, Z.F.

1994-01-01

Given an arbitrary polytope P in the n-dimensional Euclidean space R n , the question is to determine whether P contains an integral point or not. We propose a simplicial algorithm to answer this question based on a specifc integer labeling rule and a specific triangulation of R n . Starting from an

Improved Iterative Hard- and Soft-Reliability Based Majority-Logic Decoding Algorithms for Non-Binary Low-Density Parity-Check Codes

Science.gov (United States)

Xiong, Chenrong; Yan, Zhiyuan

2014-10-01

Non-binary low-density parity-check (LDPC) codes have some advantages over their binary counterparts, but unfortunately their decoding complexity is a significant challenge. The iterative hard- and soft-reliability based majority-logic decoding algorithms are attractive for non-binary LDPC codes, since they involve only finite field additions and multiplications as well as integer operations and hence have significantly lower complexity than other algorithms. In this paper, we propose two improvements to the majority-logic decoding algorithms. Instead of the accumulation of reliability information in the existing majority-logic decoding algorithms, our first improvement is a new reliability information update. The new update not only results in better error performance and fewer iterations on average, but also further reduces computational complexity. Since existing majority-logic decoding algorithms tend to have a high error floor for codes whose parity check matrices have low column weights, our second improvement is a re-selection scheme, which leads to much lower error floors, at the expense of more finite field operations and integer operations, by identifying periodic points, re-selecting intermediate hard decisions, and changing reliability information.

Triangular Numbers, Gaussian Integers, and KenKen

Science.gov (United States)

Watkins, John J.

2012-01-01

Latin squares form the basis for the recreational puzzles sudoku and KenKen. In this article we show how useful several ideas from number theory are in solving a KenKen puzzle. For example, the simple notion of triangular number is surprisingly effective. We also introduce a variation of KenKen that uses the Gaussian integers in order to…

Integer Quantum Magnon Hall Plateau-Plateau Transition in a Spin Ice Model

OpenAIRE

Xu, Baolong; Ohtsuki, Tomi; Shindou, Ryuichi

2016-01-01

Low-energy magnon bands in a two-dimensional spin ice model become integer quantum magnon Hall bands. By calculating the localization length and the two-terminal conductance of magnon transport, we show that the magnon bands with disorders undergo a quantum phase transition from an integer quantum magnon Hall regime to a conventional magnon localized regime. Finite size scaling analysis as well as a critical conductance distribution shows that the quantum critical point belongs to the same un...

Selecting a general-purpose data compression algorithm

Science.gov (United States)

Mathews, Gary Jason

1995-01-01

The National Space Science Data Center's Common Data Formate (CDF) is capable of storing many types of data such as scalar data items, vectors, and multidimensional arrays of bytes, integers, or floating point values. However, regardless of the dimensionality and data type, the data break down into a sequence of bytes that can be fed into a data compression function to reduce the amount of data without losing data integrity and thus remaining fully reconstructible. Because of the diversity of data types and high performance speed requirements, a general-purpose, fast, simple data compression algorithm is required to incorporate data compression into CDF. The questions to ask are how to evaluate and compare compression algorithms, and what compression algorithm meets all requirements. The object of this paper is to address these questions and determine the most appropriate compression algorithm to use within the CDF data management package that would be applicable to other software packages with similar data compression needs.

Implementation of software-based sensor linearization algorithms on low-cost microcontrollers.

Science.gov (United States)

Erdem, Hamit

2010-10-01

Nonlinear sensors and microcontrollers are used in many embedded system designs. As the input-output characteristic of most sensors is nonlinear in nature, obtaining data from a nonlinear sensor by using an integer microcontroller has always been a design challenge. This paper discusses the implementation of six software-based sensor linearization algorithms for low-cost microcontrollers. The comparative study of the linearization algorithms is performed by using a nonlinear optical distance-measuring sensor. The performance of the algorithms is examined with respect to memory space usage, linearization accuracy and algorithm execution time. The implementation and comparison results can be used for selection of a linearization algorithm based on the sensor transfer function, expected linearization accuracy and microcontroller capacity. Copyright © 2010 ISA. Published by Elsevier Ltd. All rights reserved.

Fractional Order Controller Designing with Firefly Algorithm and Parameter Optimization for Hydroturbine Governing System

Directory of Open Access Journals (Sweden)

Li Junyi

2015-01-01

Full Text Available A fractional order PID (FOPID controller, which is suitable for control system designing for being insensitive to the variation in system parameter, is proposed for hydroturbine governing system in the paper. The simultaneous optimization for several parameters of controller, that is, Ki, Kd, Kp, λ, and μ, is done by a recently developed metaheuristic nature-inspired algorithm, namely, the firefly algorithm (FA, for the first time, where the selecting, moving, attractiveness behavior between fireflies and updating of brightness, and decision range are studied in detail to simulate the optimization process. Investigation clearly reveals the advantages of the FOPID controller over the integer controllers in terms of reduced oscillations and settling time. The present work also explores the superiority of FA based optimization technique in finding optimal parameters of the controller. Further, convergence characteristics of the FA are compared with optimum integer order PID (IOPID controller to justify its efficiency. What is more, analysis confirms the robustness of FOPID controller under isolated load operation conditions.

RSM 1.0 - A RESUPPLY SCHEDULER USING INTEGER OPTIMIZATION

Science.gov (United States)

Viterna, L. A.

1994-01-01

RSM, Resupply Scheduling Modeler, is a fully menu-driven program that uses integer programming techniques to determine an optimum schedule for replacing components on or before the end of a fixed replacement period. Although written to analyze the electrical power system on the Space Station Freedom, RSM is quite general and can be used to model the resupply of almost any system subject to user-defined resource constraints. RSM 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 computationally intensive, integer programming was required for accuracy when modeling systems with small quantities of components. Input values for component life cane be real numbers, RSM converts them to integers by dividing the lifetime by the period duration, then reducing the result to the next lowest integer. For each component, there is a set of constraints that insure that it is replaced before its lifetime expires. RSM includes user-defined constraints such as transportation mass and volume limits, as well as component life, available repair crew time and assembly sequences. A weighting factor allows the program to minimize factors such as cost. The program then performs an iterative analysis, which is displayed during the processing. A message gives the first period in which resources are being exceeded on each iteration. If the scheduling problem is unfeasible, the final message will also indicate the first period in which resources were exceeded. RSM is written in APL2 for IBM PC series computers and compatibles. A stand-alone executable version of RSM is provided; however, this is a "packed" version of RSM which can only utilize the memory within the 640K DOS limit. This executable requires at least 640K of memory and DOS 3.1 or higher. Source code for an APL2/PC workspace version is also provided. This version of RSM can make full use of any

Distributed mixed-integer fuzzy hierarchical programming for municipal solid waste management. Part I: System identification and methodology development.

Science.gov (United States)

Cheng, Guanhui; Huang, Guohe; Dong, Cong; Xu, Ye; Chen, Xiujuan; Chen, Jiapei

2017-03-01

Due to the existence of complexities of heterogeneities, hierarchy, discreteness, and interactions in municipal solid waste management (MSWM) systems such as Beijing, China, a series of socio-economic and eco-environmental problems may emerge or worsen and result in irredeemable damages in the following decades. Meanwhile, existing studies, especially ones focusing on MSWM in Beijing, could hardly reflect these complexities in system simulations and provide reliable decision support for management practices. Thus, a framework of distributed mixed-integer fuzzy hierarchical programming (DMIFHP) is developed in this study for MSWM under these complexities. Beijing is selected as a representative case. The Beijing MSWM system is comprehensively analyzed in many aspects such as socio-economic conditions, natural conditions, spatial heterogeneities, treatment facilities, and system complexities, building a solid foundation for system simulation and optimization. Correspondingly, the MSWM system in Beijing is discretized as 235 grids to reflect spatial heterogeneity. A DMIFHP model which is a nonlinear programming problem is constructed to parameterize the Beijing MSWM system. To enable scientific solving of it, a solution algorithm is proposed based on coupling of fuzzy programming and mixed-integer linear programming. Innovations and advantages of the DMIFHP framework are discussed. The optimal MSWM schemes and mechanism revelations will be discussed in another companion paper due to length limitation.

Landau level broadening without disorder, non-integer plateaus without interactions- an alternative model of the quantum Hall effect

International Nuclear Information System (INIS)

Kramer, T.

2006-01-01

I review some aspects of an alternative model of the quantum Hall effect, which is not based on the presence of disorder potentials. Instead, a quantization of the electronic drift current in the presence of crossed electric and magnetic fields is employed to construct a non-linear transport theory. Another important ingredient of the alternative theory is the coupling of the two-dimensional electron gas to the leads and the applied voltages. By working in a picture where the external voltages fix the chemical potential in the 2D subsystem, the experimentally observed linear relation between the voltage and the location of the quantum Hall plateaus finds an natural explanation. Also, the classical Hall effect emerges as a natural limit of the quantum Hall effect. For low temperatures (or high currents), a non-integer substructure splits higher Landau levels into sublevels. The appearance of substructure and non-integer plateaus in the resistivity is not linked to electron-electron interactions, but caused by the presence of a (linear) electric field. Some of the resulting fractions correspond exactly to half-integer plateaus. (Author)

Identifying optimal regional solid waste management strategies through an inexact integer programming model containing infinite objectives and constraints.

Science.gov (United States)

He, Li; Huang, Guo-He; Zeng, Guang-Ming; Lu, Hong-Wei

2009-01-01

The previous inexact mixed-integer linear programming (IMILP) method can only tackle problems with coefficients of the objective function and constraints being crisp intervals, while the existing inexact mixed-integer semi-infinite programming (IMISIP) method can only deal with single-objective programming problems as it merely allows the number of constraints to be infinite. This study proposes, an inexact mixed-integer bi-infinite programming (IMIBIP) method by incorporating the concept of functional intervals into the programming framework. Different from the existing methods, the IMIBIP can tackle the inexact programming problems that contain both infinite objectives and constraints. The developed method is applied to capacity planning of waste management systems under a variety of uncertainties. Four scenarios are considered for comparing the solutions of IMIBIP with those of IMILP. The results indicate that reasonable solutions can be generated by the IMIBIP method. Compared with IMILP, the system cost from IMIBIP would be relatively high since the fluctuating market factors are considered; however, the IMILP solutions are associated with a raised system reliability level and a reduced constraint violation risk level.

Selecting Tools to Model Integer and Binomial Multiplication

Science.gov (United States)

Pratt, Sarah Smitherman; Eddy, Colleen M.

2017-01-01

Mathematics teachers frequently provide concrete manipulatives to students during instruction; however, the rationale for using certain manipulatives in conjunction with concepts may not be explored. This article focuses on area models that are currently used in classrooms to provide concrete examples of integer and binomial multiplication. The…

Core barrier formation near integer q surfaces in DIII-D

International Nuclear Information System (INIS)

Austin, M. E.; Gentle, K. W.; Burrell, K. H.; Waltz, R. E.; Gohil, P.; Greenfield, C. M.; Groebner, R. J.; Petty, C. C.; Prater, R.; Heidbrink, W. W.; Luo, Y.; Kinsey, J. E.; Makowski, M. A.; McKee, G. R.; Shafer, M. W.; Nazikian, R.; Rhodes, T. L.; Van Zeeland, M. A.

2006-01-01

Recent DIII-D experiments have significantly improved the understanding of internal transport barriers (ITBs) that are triggered close to the time when an integer value of the minimum in q is crossed. While this phenomenon has been observed on many tokamaks, the extensive transport and fluctuation diagnostics on DIII-D have permitted a detailed study of the generation mechanisms of q-triggered ITBs as pertaining to turbulence suppression dynamics, shear flows, and energetic particle modes. In these discharges, the evolution of the q profile is measured using motional Stark effect polarimetry and the integer q min crossings are further pinpointed in time by the observation of Alfven cascades. High time resolution measurements of the ion and electron temperatures and the toroidal rotation show that the start of improved confinement is simultaneous in all three channels, and that this event precedes the traversal of integer q min by 5-20 ms. There is no significant low-frequency magnetohydrodynamic activity prior to or just after the crossing of the integer q min and hence magnetic reconnection is determined not to be the precipitant of the confinement change. Instead, results from the GYRO code point to the effects of zonal flows near low order rational q values as playing a role in ITB triggering. A reduction in local turbulent fluctuations is observed at the start of the temperature rise and, concurrently, an increase in turbulence poloidal flow velocity and flow shear is measured with the beam emission spectroscopy diagnostic. For the case of a transition to an enduring internal barrier the fluctuation level remains at a reduced amplitude. The timing and nature of the temperature, rotation, and fluctuation changes leading to internal barriers suggests transport improvement due to increased shear flow arising from the zonal flow structures

A new VLSI complex integer multiplier which uses a quadratic-polynomial residue system with Fermat numbers

Science.gov (United States)

Shyu, H. C.; Reed, I. S.; Truong, T. K.; Hsu, I. S.; Chang, J. J.

1987-01-01

A quadratic-polynomial Fermat residue number system (QFNS) has been used to compute complex integer multiplications. The advantage of such a QFNS is that a complex integer multiplication requires only two integer multiplications. In this article, a new type Fermat number multiplier is developed which eliminates the initialization condition of the previous method. It is shown that the new complex multiplier can be implemented on a single VLSI chip. Such a chip is designed and fabricated in CMOS-Pw technology.

Artificial neural networks and evolutionary algorithms in engineering design

OpenAIRE

T. Velsker; M. Eerme; J. Majak; M. Pohlak; K. Karjust

2011-01-01

Purpose: Purpose of this paper is investigation of optimization strategies eligible for solving complex engineering design problems. An aim is to develop numerical algorithms for solving optimal design problems which may contain real and integer variables, a number of local extremes, linear- and non-linear constraints and multiple optimality criteria.Design/methodology/approach: The methodology proposed for solving optimal design problems is based on integrated use of meta-modeling techniques...

Pinning mode of integer quantum Hall Wigner crystal of skyrmions

Science.gov (United States)

Zhu, Han; Sambandamurthy, G.; Chen, Y. P.; Jiang, P.-H.; Engel, L. W.; Tsui, D. C.; Pfeiffer, L. N.; West, K. W.

2009-03-01

Just away from integer Landau level (LL) filling factors ν, the dilute quasi-particles/holes at the partially filled LL form an integer-quantum-Hall Wigner crystal, which exhibits microwave pinning mode resonances [1]. Due to electron-electron interaction, it was predicted that the elementary excitation around ν= 1 is not a single spin flip, but a larger-scale spin texture, known as a skyrmion [2]. We have compared the pinning mode resonances [1] of integer quantum Hall Wigner crystals formed in the partly filled LL just away from ν= 1 and ν= 2, in the presence of an in-plane magnetic field. As an in-plane field is applied, the peak frequencies of the resonances near ν= 1 increase, while the peak frequencies below ν= 2 show neligible dependence on in-plane field. We interpret this observation as due to a skyrmion crystal phase around ν= 1 and a single-hole Wigner crystal phase below ν= 2. The in-plane field increases the Zeeman gap and causes shrinking of the skyrmion size toward single spin flips. [1] Yong P. Chen et al., Phys. Rev. Lett. 91, 016801 (2003). [2] S. L. Sondhi et al., Phys. Rev. B 47, 16 419 (1993); L. Brey et al., Phys. Rev. Lett. 75, 2562 (1995).

Allocating the Fixed Resources and Setting Targets in Integer Data Envelopment Analysis

Directory of Open Access Journals (Sweden)

Kobra Gholami

2013-11-01

Full Text Available Data envelopment analysis (DEA is a non-parametric approach to evaluate a set of decision making units (DMUs consuming multiple inputs to produce multiple outputs. Formally, DEA use to estimate the efficiency score into the empirical efficient frontier. Also, DEA can be used to allocate resources and set targets for future forecast. The data are continuous in the standard DEA model whereas there are many problems in the real life that data must be integer such as number of employee, machinery, expert and so on. Thus in this paper we propose an approach to allocate fixed resources and set fixed targets with selective integer assumption that is based on an integer data envelopment analysis (IDEA approach for the first time. The major aim in this approach is preserving the efficiency score of DMUs. We use the concept of benchmarking to reach this aim. The numerical example gets to illustrate the applicability of the proposed method.

Note on Integer-Valued Bilinear Time Series Models

NARCIS (Netherlands)

Drost, F.C.; van den Akker, R.; Werker, B.J.M.

2007-01-01

Summary. This note reconsiders the nonnegative integer-valued bilinear processes introduced by Doukhan, Latour, and Oraichi (2006). Using a hidden Markov argument, we extend their result of the existence of a stationary solution for the INBL(1,0,1,1) process to the class of superdiagonal INBL(p; q;

Artificial bee colony algorithm for constrained possibilistic portfolio optimization problem

Science.gov (United States)

Chen, Wei

2015-07-01

In this paper, we discuss the portfolio optimization problem with real-world constraints under the assumption that the returns of risky assets are fuzzy numbers. A new possibilistic mean-semiabsolute deviation model is proposed, in which transaction costs, cardinality and quantity constraints are considered. Due to such constraints the proposed model becomes a mixed integer nonlinear programming problem and traditional optimization methods fail to find the optimal solution efficiently. Thus, a modified artificial bee colony (MABC) algorithm is developed to solve the corresponding optimization problem. Finally, a numerical example is given to illustrate the effectiveness of the proposed model and the corresponding algorithm.

An integer ambiguity resolution method for the global positioning system (GPS)-based land vehicle attitude determination

International Nuclear Information System (INIS)

Wang, Bo; Miao, Lingjuan; Wang, Shunting; Shen, Jun

2009-01-01

During attitude determination using a global positioning system (GPS), cycle slips occur due to the loss of lock and noise disturbance. Therefore, the integer ambiguity needs re-computation to isolate the error in carrier phase. This paper presents a fast method for integer ambiguity resolution for land vehicle application. After the cycle slips are detected, the velocity vector is utilized to obtain the rough baseline vector. The obtained baseline vector is substituted into carrier phase observation equations to solve the float ambiguity solution which can be used as a constraint to accelerate the integer ambiguity search procedure at next epochs. The probability of correct integer estimation in the expanded search space is analyzed. Experimental results demonstrate that the proposed method gives a fast approach to obtain new fixed ambiguities while the regular method takes longer time and sometimes results in incorrect solutions

Scheduling of Iterative Algorithms with Matrix Operations for Efficient FPGA Design—Implementation of Finite Interval Constant Modulus Algorithm

Czech Academy of Sciences Publication Activity Database

Šůcha, P.; Hanzálek, Z.; Heřmánek, Antonín; Schier, Jan

2007-01-01

Roč. 46, č. 1 (2007), s. 35-53 ISSN 0922-5773 R&D Projects: GA AV ČR(CZ) 1ET300750402; GA MŠk(CZ) 1M0567; GA MPO(CZ) FD-K3/082 Institutional research plan: CEZ:AV0Z10750506 Keywords : high-level synthesis * cyclic scheduling * iterative algorithms * imperfectly nested loops * integer linear programming * FPGA * VLSI design * blind equalization * implementation Subject RIV: BA - General Mathematics Impact factor: 0.449, year: 2007 http://www.springerlink.com/content/t217kg0822538014/fulltext.pdf

Spatial “Artistic” Networks: From Deconstructing Integer-Functions to Visual Arts

Directory of Open Access Journals (Sweden)

Ernesto Estrada

2018-01-01

Full Text Available Deconstructivism is an aesthetically appealing architectonic style. Here, we identify some general characteristics of this style, such as decomposition of the whole into parts, superposition of layers, and conservation of the memory of the whole. Using these attributes, we propose a method to deconstruct functions based on integers. Using this integer-function deconstruction we generate spatial networks which display a few artistic attributes such as (i biomorphic shapes, (ii symmetry, and (iii beauty. In building these networks, the deconstructed integer-functions are used as the coordinates of the nodes in a unit square, which are then joined according to a given connection radius like in random geometric graphs (RGGs. Some graph-theoretic invariants of these networks are calculated and compared with the classical RGGs. We then show how these networks inspire an artist to create artistic compositions using mixed techniques on canvas and on paper. Finally, we call for avoiding that the applicability of (network sciences should not go in detriment of curiosity-driven, and aesthetic-driven, researches. We claim that the aesthetic of network research, and not only its applicability, would be an attractor for new minds to this field.

WAVELET-BASED ALGORITHM FOR DETECTION OF BEARING FAULTS IN A GAS TURBINE ENGINE

Directory of Open Access Journals (Sweden)

Sergiy Enchev

2014-07-01

Full Text Available Presented is a gas turbine engine bearing diagnostic system that integrates information from various advanced vibration analysis techniques to achieve robust bearing health state awareness. This paper presents a computational algorithm for identifying power frequency variations and integer harmonics by using wavelet-based transform. The continuous wavelet transform with  the complex Morlet wavelet is adopted to detect the harmonics presented in a power signal. The algorithm based on the discrete stationary wavelet transform is adopted to denoise the wavelet ridges.

FATCOP: A Fault Tolerant Condor-PVM Mixed Integer Program Solver

National Research Council Canada - National Science Library

Chen, Qun

1999-01-01

We describe FATCOP, a new parallel mixed integer program solver written in PVM. The implementation uses the Condor resource management system to provide a virtual machine composed of otherwise idle computers...

Sixth-grade students' reasoning on the order relation of integers as influenced by prior experience: an inferentialist analysis

Science.gov (United States)

Schindler, Maike; Hußmann, Stephan; Nilsson, Per; Bakker, Arthur

2017-12-01

Negative numbers are among the first formalizations students encounter in their mathematics learning that clearly differ from out-of-school experiences. What has not sufficiently been addressed in previous research is the question of how students draw on their prior experiences when reasoning on negative numbers and how they infer from these experiences. This article presents results from an empirical study investigating sixth-grade students' reasoning and inferring from school-based and out-of-school experiences. In particular, it addresses the order relation, which deals with students' very first encounters with negative numbers. Here, students can reason in different ways, depending on the experiences they draw on. We study how students reason before a lesson series and how their reasoning is influenced through this lesson series where the number line and the context debts-and-assets are predominant. For grasping the reasoning's inferential and social nature and conducting in-depth analyses of two students' reasoning, we use an epistemological framework that is based on the philosophical theory of inferentialism. The results illustrate how the students infer their reasoning from out-of-school and from school-based experiences both before and after the lesson series. They reveal interesting phenomena not previously analyzed in the research on the order relation for integers.

A deterministic algorithm for fitting a step function to a weighted point-set

KAUST Repository

Fournier, Hervé

2013-02-01

Given a set of n points in the plane, each point having a positive weight, and an integer k>0, we present an optimal O(nlogn)-time deterministic algorithm to compute a step function with k steps that minimizes the maximum weighted vertical distance to the input points. It matches the expected time bound of the best known randomized algorithm for this problem. Our approach relies on Coles improved parametric searching technique. As a direct application, our result yields the first O(nlogn)-time algorithm for computing a k-center of a set of n weighted points on the real line. © 2012 Elsevier B.V.

Fractional and integer charges from Levinson's theorem

International Nuclear Information System (INIS)

Farhi, E.; Graham, N.; Jaffe, R.L.; Weigel, H.

2001-01-01

We compute fractional and integer fermion quantum numbers of static background field configurations using phase shifts and Levinson's theorem. By extending fermionic scattering theory to arbitrary dimensions, we implement dimensional regularization in a (1+1)-dimensional gauge theory. We demonstrate that this regularization procedure automatically eliminates the anomaly in the vector current that a naive regulator would produce. We also apply these techniques to bag models in one and three dimensions

Solving stochastic programs with integer recourse by enumeration : a framework using Gröbner basis reductions

NARCIS (Netherlands)

Schultz, R.; Stougie, L.; Vlerk, van der M.H.

1998-01-01

In this paper we present a framework for solving stochastic programs with complete integer recourse and discretely distributed right-hand side vector, using Gröbner basis methods from computational algebra to solve the numerous second-stage integer programs. Using structural properties of the

Designing fractional factorial split-plot experiments using integer programming

DEFF Research Database (Denmark)

Capehart, Shay R.; Keha, Ahmet; Kulahci, Murat

2011-01-01

factorial (FF) design, with the restricted randomisation structure to account for the whole plots and subplots. We discuss the formulation of FFSP designs using integer programming (IP) to achieve various design criteria. We specifically look at the maximum number of clear two-factor interactions...

Reliability–redundancy allocation problem considering optimal redundancy strategy using parallel genetic algorithm

International Nuclear Information System (INIS)

Kim, Heungseob; Kim, Pansoo

2017-01-01

To maximize the reliability of a system, the traditional reliability–redundancy allocation problem (RRAP) determines the component reliability and level of redundancy for each subsystem. This paper proposes an advanced RRAP that also considers the optimal redundancy strategy, either active or cold standby. In addition, new examples are presented for it. Furthermore, the exact reliability function for a cold standby redundant subsystem with an imperfect detector/switch is suggested, and is expected to replace the previous approximating model that has been used in most related studies. A parallel genetic algorithm for solving the RRAP as a mixed-integer nonlinear programming model is presented, and its performance is compared with those of previous studies by using numerical examples on three benchmark problems. - Highlights: • Optimal strategy is proposed to solve reliability redundancy allocation problem. • The redundancy strategy uses parallel genetic algorithm. • Improved reliability function for a cold standby subsystem is suggested. • Proposed redundancy strategy enhances the system reliability.

Integers without Large Prime Factors in Short Intervals: Conditional ...

Indian Academy of Sciences (India)

... Public Lectures · Lecture Workshops · Refresher Courses · Symposia · Live Streaming. Home; Journals; Proceedings – Mathematical Sciences; Volume 120; Issue 5. Integers without Large Prime Factors in Short Intervals: Conditional Results. Goutam Pal Satadal Ganguly. Volume 120 Issue 5 November 2010 pp 515-524 ...

The Combination of RSA And Block Chiper Algorithms To Maintain Message Authentication

Science.gov (United States)

Yanti Tarigan, Sepri; Sartika Ginting, Dewi; Lumban Gaol, Melva; Lorensi Sitompul, Kristin

2017-12-01

RSA algorithm is public key algorithm using prime number and even still used today. The strength of this algorithm lies in the exponential process, and the factorial number into 2 prime numbers which until now difficult to do factoring. The RSA scheme itself adopts the block cipher scheme, where prior to encryption, the existing plaintext is divide in several block of the same length, where the plaintext and ciphertext are integers between 1 to n, where n is typically 1024 bit, and the block length itself is smaller or equal to log(n)+1 with base 2. With the combination of RSA algorithm and block chiper it is expected that the authentication of plaintext is secure. The secured message will be encrypted with RSA algorithm first and will be encrypted again using block chiper. And conversely, the chipertext will be decrypted with the block chiper first and decrypted again with the RSA algorithm. This paper suggests a combination of RSA algorithms and block chiper to secure data.

Discovery of functional and approximate functional dependencies in relational databases

Directory of Open Access Journals (Sweden)

Ronald S. King

2003-01-01

Full Text Available This study develops the foundation for a simple, yet efficient method for uncovering functional and approximate functional dependencies in relational databases. The technique is based upon the mathematical theory of partitions defined over a relation's row identifiers. Using a levelwise algorithm the minimal non-trivial functional dependencies can be found using computations conducted on integers. Therefore, the required operations on partitions are both simple and fast. Additionally, the row identifiers provide the added advantage of nominally identifying the exceptions to approximate functional dependencies, which can be used effectively in practical data mining applications.

Integer Set Compression and Statistical Modeling

DEFF Research Database (Denmark)

Larsson, N. Jesper

2014-01-01

enumeration of elements may be arbitrary or random, but where statistics is kept in order to estimate probabilities of elements. We present a recursive subset-size encoding method that is able to benefit from statistics, explore the effects of permuting the enumeration order based on element probabilities......Compression of integer sets and sequences has been extensively studied for settings where elements follow a uniform probability distribution. In addition, methods exist that exploit clustering of elements in order to achieve higher compression performance. In this work, we address the case where...

N-Dimensional LLL Reduction Algorithm with Pivoted Reflection

Directory of Open Access Journals (Sweden)

Zhongliang Deng

2018-01-01

Full Text Available The Lenstra-Lenstra-Lovász (LLL lattice reduction algorithm and many of its variants have been widely used by cryptography, multiple-input-multiple-output (MIMO communication systems and carrier phase positioning in global navigation satellite system (GNSS to solve the integer least squares (ILS problem. In this paper, we propose an n-dimensional LLL reduction algorithm (n-LLL, expanding the Lovász condition in LLL algorithm to n-dimensional space in order to obtain a further reduced basis. We also introduce pivoted Householder reflection into the algorithm to optimize the reduction time. For an m-order positive definite matrix, analysis shows that the n-LLL reduction algorithm will converge within finite steps and always produce better results than the original LLL reduction algorithm with n > 2. The simulations clearly prove that n-LLL is better than the original LLL in reducing the condition number of an ill-conditioned input matrix with 39% improvement on average for typical cases, which can significantly reduce the searching space for solving ILS problem. The simulation results also show that the pivoted reflection has significantly declined the number of swaps in the algorithm by 57%, making n-LLL a more practical reduction algorithm.

Multiobjective genetic algorithm approaches to project scheduling under risk

OpenAIRE

Kılıç, Murat; Kilic, Murat

2003-01-01

In this thesis, project scheduling under risk is chosen as the topic of research. Project scheduling under risk is defined as a biobjective decision problem and is formulated as a 0-1 integer mathematical programming model. In this biobjective formulation, one of the objectives is taken as the expected makespan minimization and the other is taken as the expected cost minimization. As the solution approach to this biobjective formulation genetic algorithm (GA) is chosen. After carefully invest...

On the price of integer charge quarks

International Nuclear Information System (INIS)

Okun, L.B.; Voloshin, M.B.; Zakharov, V.I.

1979-01-01

Implication of the integer charge quark (ICQ) model with a broken SU(3)xU(1) gauge symmetry for interactions in the leptonic sector were discussed. In this model there should be very large deviations of e + e - →μ + μ - annihilation processes in the GeV region from the standard QED behaviour. Such deviations seem to be completely excluded by existing data. Therefore it is concluded that the ICQ model is ruled out

An exact algorithm for optimal MAE stack filter design.

Science.gov (United States)

Dellamonica, Domingos; Silva, Paulo J S; Humes, Carlos; Hirata, Nina S T; Barrera, Junior

2007-02-01

We propose a new algorithm for optimal MAE stack filter design. It is based on three main ingredients. First, we show that the dual of the integer programming formulation of the filter design problem is a minimum cost network flow problem. Next, we present a decomposition principle that can be used to break this dual problem into smaller subproblems. Finally, we propose a specialization of the network Simplex algorithm based on column generation to solve these smaller subproblems. Using our method, we were able to efficiently solve instances of the filter problem with window size up to 25 pixels. To the best of our knowledge, this is the largest dimension for which this problem was ever solved exactly.

Stochastic search in structural optimization - Genetic algorithms and simulated annealing

Science.gov (United States)

Hajela, Prabhat

1993-01-01

An account is given of illustrative applications of genetic algorithms and simulated annealing methods in structural optimization. The advantages of such stochastic search methods over traditional mathematical programming strategies are emphasized; it is noted that these methods offer a significantly higher probability of locating the global optimum in a multimodal design space. Both genetic-search and simulated annealing can be effectively used in problems with a mix of continuous, discrete, and integer design variables.

Independent tasks scheduling in cloud computing via improved estimation of distribution algorithm

Science.gov (United States)

Sun, Haisheng; Xu, Rui; Chen, Huaping

2018-04-01

To minimize makespan for scheduling independent tasks in cloud computing, an improved estimation of distribution algorithm (IEDA) is proposed to tackle the investigated problem in this paper. Considering that the problem is concerned with multi-dimensional discrete problems, an improved population-based incremental learning (PBIL) algorithm is applied, which the parameter for each component is independent with other components in PBIL. In order to improve the performance of PBIL, on the one hand, the integer encoding scheme is used and the method of probability calculation of PBIL is improved by using the task average processing time; on the other hand, an effective adaptive learning rate function that related to the number of iterations is constructed to trade off the exploration and exploitation of IEDA. In addition, both enhanced Max-Min and Min-Min algorithms are properly introduced to form two initial individuals. In the proposed IEDA, an improved genetic algorithm (IGA) is applied to generate partial initial population by evolving two initial individuals and the rest of initial individuals are generated at random. Finally, the sampling process is divided into two parts including sampling by probabilistic model and IGA respectively. The experiment results show that the proposed IEDA not only gets better solution, but also has faster convergence speed.

What Else Is Decidable about Integer Arrays?

OpenAIRE

Habermehl, Peter; Iosif, Radu; Vojnar, Tomáš

2008-01-01

International audience; We introduce a new decidable logic for reasoning about infinite arrays of integers. The logic is in the ∃ * ∀ * first-order fragment and allows (1) Presburger constraints on existentially quantified variables, (2) difference constraints as well as periodicity constraints on universally quantified indices, and (3) difference constraints on values. In particular, using our logic, one can express constraints on consecutive elements of arrays (e.g. ∀i. 0 ≤ i < n → a[i + 1]...

Integer programming for the generalized high school timetabling problem

DEFF Research Database (Denmark)

Kristiansen, Simon; Sørensen, Matias; Stidsen, Thomas Riis

2015-01-01

, the XHSTT format serves as a common ground for researchers within this area. This paper describes the first exact method capable of handling an arbitrary instance of the XHSTT format. The method is based on a mixed-integer linear programming (MIP) model, which is solved in two steps with a commercial...

Efficient density matrix renormalization group algorithm to study Y junctions with integer and half-integer spin

KAUST Repository

Kumar, Manoranjan

2016-02-03

An efficient density matrix renormalization group (DMRG) algorithm is presented and applied to Y junctions, systems with three arms of n sites that meet at a central site. The accuracy is comparable to DMRG of chains. As in chains, new sites are always bonded to the most recently added sites and the superblock Hamiltonian contains only new or once renormalized operators. Junctions of up to N=3n+1≈500 sites are studied with antiferromagnetic (AF) Heisenberg exchange J between nearest-neighbor spins S or electron transfer t between nearest neighbors in half-filled Hubbard models. Exchange or electron transfer is exclusively between sites in two sublattices with NA≠NB. The ground state (GS) and spin densities ρr=⟨Szr⟩ at site r are quite different for junctions with S=1/2, 1, 3/2, and 2. The GS has finite total spin SG=2S(S) for even (odd) N and for MG=SG in the SG spin manifold, ρr>0(<0) at sites of the larger (smaller) sublattice. S=1/2 junctions have delocalized states and decreasing spin densities with increasing N. S=1 junctions have four localized Sz=1/2 states at the end of each arm and centered on the junction, consistent with localized states in S=1 chains with finite Haldane gap. The GS of S=3/2 or 2 junctions of up to 500 spins is a spin density wave with increased amplitude at the ends of arms or near the junction. Quantum fluctuations completely suppress AF order in S=1/2 or 1 junctions, as well as in half-filled Hubbard junctions, but reduce rather than suppress AF order in S=3/2 or 2 junctions.

Efficient density matrix renormalization group algorithm to study Y junctions with integer and half-integer spin

KAUST Repository

Kumar, Manoranjan; Parvej, Aslam; Thomas, Simil; Ramasesha, S.; Soos, Z. G.

2016-01-01

An efficient density matrix renormalization group (DMRG) algorithm is presented and applied to Y junctions, systems with three arms of n sites that meet at a central site. The accuracy is comparable to DMRG of chains. As in chains, new sites are always bonded to the most recently added sites and the superblock Hamiltonian contains only new or once renormalized operators. Junctions of up to N=3n+1≈500 sites are studied with antiferromagnetic (AF) Heisenberg exchange J between nearest-neighbor spins S or electron transfer t between nearest neighbors in half-filled Hubbard models. Exchange or electron transfer is exclusively between sites in two sublattices with NA≠NB. The ground state (GS) and spin densities ρr=⟨Szr⟩ at site r are quite different for junctions with S=1/2, 1, 3/2, and 2. The GS has finite total spin SG=2S(S) for even (odd) N and for MG=SG in the SG spin manifold, ρr>0(<0) at sites of the larger (smaller) sublattice. S=1/2 junctions have delocalized states and decreasing spin densities with increasing N. S=1 junctions have four localized Sz=1/2 states at the end of each arm and centered on the junction, consistent with localized states in S=1 chains with finite Haldane gap. The GS of S=3/2 or 2 junctions of up to 500 spins is a spin density wave with increased amplitude at the ends of arms or near the junction. Quantum fluctuations completely suppress AF order in S=1/2 or 1 junctions, as well as in half-filled Hubbard junctions, but reduce rather than suppress AF order in S=3/2 or 2 junctions.

Development of Web-Based Menu Planning Support System and its Solution Using Genetic Algorithm

Science.gov (United States)

Kashima, Tomoko; Matsumoto, Shimpei; Ishii, Hiroaki

2009-10-01

Recently lifestyle-related diseases have become an object of public concern, while at the same time people are being more health conscious. As an essential factor for causing the lifestyle-related diseases, we assume that the knowledge circulation on dietary habits is still insufficient. This paper focuses on everyday meals close to our life and proposes a well-balanced menu planning system as a preventive measure of lifestyle-related diseases. The system is developed by using a Web-based frontend and it provides multi-user services and menu information sharing capabilities like social networking services (SNS). The system is implemented on a Web server running Apache (HTTP server software), MySQL (database management system), and PHP (scripting language for dynamic Web pages). For the menu planning, a genetic algorithm is applied by understanding this problem as multidimensional 0-1 integer programming.

Origin and diversity of an underutilized fruit tree crop, cempedak (Artocarpus integer, Moraceae).

Science.gov (United States)

Wang, Maria M H; Gardner, Elliot M; Chung, Richard C K; Chew, Ming Yee; Milan, Abd Rahman; Pereira, Joan T; Zerega, Nyree J C

2018-06-06

Underutilized crops and their wild relatives are important resources for crop improvement and food security. Cempedak [Artocarpus integer (Thunb). Merr.] is a significant crop in Malaysia but underutilized elsewhere. Here we performed molecular characterization of cempedak and its putative wild relative bangkong (Artocarpus integer (Thunb). Merr. var. silvestris Corner) to address questions regarding the origin and diversity of cempedak. Using data from 12 microsatellite loci, we assessed the genetic diversity and genetic/geographic structure for 353 cempedak and 175 bangkong accessions from Malaysia and neighboring countries and employed clonal analysis to characterize cempedak cultivars. We conducted haplotype network analyses on the trnH-psbA region in a subset of these samples. We also analyzed key vegetative characters that reportedly differentiate cempedak and bangkong. We show that cempedak and bangkong are sister taxa and distinct genetically and morphologically, but the directionality of domestication origin is unclear. Genetic diversity was generally higher in bangkong than in cempedak. We found a distinct genetic cluster for cempedak from Borneo as compared to cempedak from Peninsular Malaysia. Finally, cempedak cultivars with the same names did not always share the same genetic fingerprint. Cempedak origins are complex, with likely admixture and hybridization with bangkong, warranting further investigation. We provide a baseline of genetic diversity of cempedak and bangkong in Malaysia and found that germplasm collections in Malaysia represent diverse coverage of the four cempedak genetic clusters detected. © 2018 Botanical Society of America.

About approximation of integer factorization problem by the combination fixed-point iteration method and Bayesian rounding for quantum cryptography

Science.gov (United States)

Ogorodnikov, Yuri; Khachay, Michael; Pljonkin, Anton

2018-04-01

We describe the possibility of employing the special case of the 3-SAT problem stemming from the well known integer factorization problem for the quantum cryptography. It is known, that for every instance of our 3-SAT setting the given 3-CNF is satisfiable by a unique truth assignment, and the goal is to find this assignment. Since the complexity status of the factorization problem is still undefined, development of approximation algorithms and heuristics adopts interest of numerous researchers. One of promising approaches to construction of approximation techniques is based on real-valued relaxation of the given 3-CNF followed by minimizing of the appropriate differentiable loss function, and subsequent rounding of the fractional minimizer obtained. Actually, algorithms developed this way differ by the rounding scheme applied on their final stage. We propose a new rounding scheme based on Bayesian learning. The article shows that the proposed method can be used to determine the security in quantum key distribution systems. In the quantum distribution the Shannon rules is applied and the factorization problem is paramount when decrypting secret keys.

An Efficient Inductive Genetic Learning Algorithm for Fuzzy Relational Rules

Directory of Open Access Journals (Sweden)

Antonio

2012-04-01

Full Text Available Fuzzy modelling research has traditionally focused on certain types of fuzzy rules. However, the use of alternative rule models could improve the ability of fuzzy systems to represent a specific problem. In this proposal, an extended fuzzy rule model, that can include relations between variables in the antecedent of rules is presented. Furthermore, a learning algorithm based on the iterative genetic approach which is able to represent the knowledge using this model is proposed as well. On the other hand, potential relations among initial variables imply an exponential growth in the feasible rule search space. Consequently, two filters for detecting relevant potential relations are added to the learning algorithm. These filters allows to decrease the search space complexity and increase the algorithm efficiency. Finally, we also present an experimental study to demonstrate the benefits of using fuzzy relational rules.

Direct comparison of fractional and integer quantized Hall resistance

Science.gov (United States)

Ahlers, Franz J.; Götz, Martin; Pierz, Klaus

2017-08-01

We present precision measurements of the fractional quantized Hall effect, where the quantized resistance {{R}≤ft[ 1/3 \\right]} in the fractional quantum Hall state at filling factor 1/3 was compared with a quantized resistance {{R}[2]} , represented by an integer quantum Hall state at filling factor 2. A cryogenic current comparator bridge capable of currents down to the nanoampere range was used to directly compare two resistance values of two GaAs-based devices located in two cryostats. A value of 1-(5.3  ±  6.3) 10-8 (95% confidence level) was obtained for the ratio ({{R}≤ft[ 1/3 \\right]}/6{{R}[2]} ). This constitutes the most precise comparison of integer resistance quantization (in terms of h/e 2) in single-particle systems and of fractional quantization in fractionally charged quasi-particle systems. While not relevant for practical metrology, such a test of the validity of the underlying physics is of significance in the context of the upcoming revision of the SI.

Rigorous solution to Bargmann-Wigner equation for integer spin

CERN Document Server

Huang Shi Zhong; Wu Ning; Zheng Zhi Peng

2002-01-01

A rigorous method is developed to solve the Bargamann-Wigner equation for arbitrary integer spin in coordinate representation in a step by step way. The Bargmann-Wigner equation is first transformed to a form easier to solve, the new equations are then solved rigorously in coordinate representation, and the wave functions in a closed form are thus derived

A bi-objective integer programming model for partly-restricted flight departure scheduling.

Science.gov (United States)

Zhong, Han; Guan, Wei; Zhang, Wenyi; Jiang, Shixiong; Fan, Lingling

2018-01-01

The normal studies on air traffic departure scheduling problem (DSP) mainly deal with an independent airport in which the departure traffic is not affected by surrounded airports, which, however, is not a consistent case. In reality, there still exist cases where several commercial airports are closely located and one of them possesses a higher priority. During the peak hours, the departure activities of the lower-priority airports are usually required to give way to those of higher-priority airport. These giving-way requirements can inflict a set of changes on the modeling of departure scheduling problem with respect to the lower-priority airports. To the best of our knowledge, studies on DSP under this condition are scarce. Accordingly, this paper develops a bi-objective integer programming model to address the flight departure scheduling of the partly-restricted (e.g., lower-priority) one among several adjacent airports. An adapted tabu search algorithm is designed to solve the current problem. It is demonstrated from the case study of Tianjin Binhai International Airport in China that the proposed method can obviously improve the operation efficiency, while still realizing superior equity and regularity among restricted flows.

Algorithms for Rapidly Dispersing Robot Swarms in Unknown Environments

OpenAIRE

Hsiang, Tien-Ruey; Arkin, Esther M.; Bender, Michael; Fekete, Sandor P.; Mitchell, Joseph S. B.

2002-01-01

We develop and analyze algorithms for dispersing a swarm of primitive robots in an unknown environment, R. The primary objective is to minimize the makespan, that is, the time to fill the entire region. An environment is composed of pixels that form a connected subset of the integer grid. There is at most one robot per pixel and robots move horizontally or vertically at unit speed. Robots enter R by means of k>=1 door pixels Robots are primitive finite automata, only having local communicatio...

Recurrence relations for three-loop prototypes of bubble diagrams with a mass

International Nuclear Information System (INIS)

Avdeev, L.V.

1995-01-01

Recurrence relations derived via the Chetyrkin-Tkachev method of integration by parts are applied to reduce scalar three-loop bubble (vacuum) diagrams with a mass to a limited number of master integrals. The reduction is implemented as a package of computer programs for analytic evaluation in FORM. The algorithms are applicable to diagrams with any integer powers on the lines in an arbitrary dimension. A physical application is the evaluation of the three-loop QCD correction to the electroweak ρ-parameter. 8 refs., 1 fig

Unimodular lattices in dimensions 14 and 15 over the Eisenstein integers

Science.gov (United States)

Abdukhalikov, Kanat; Scharlau, Rudolf

2009-03-01

All indecomposable unimodular hermitian lattices in dimensions 14 and 15 over the ring of integers in mathbb{Q}(sqrt{-3}) are determined. Precisely one lattice in dimension 14 and two lattices in dimension 15 have minimal norm 3.

A property of assignment type mixed integer linear programming problems

NARCIS (Netherlands)

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

1982-01-01

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

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: ...

IMC-PID-fractional-order-filter controllers design for integer order systems.

Science.gov (United States)

Maâmar, Bettayeb; Rachid, Mansouri

2014-09-01

One of the reasons of the great success of standard PID controllers is the presence of simple tuning rules, of the automatic tuning feature and of tables that simplify significantly their design. For the fractional order case, some tuning rules have been proposed in the literature. However, they are not general because they are valid only for some model cases. In this paper, a new approach is investigated. The fractional property is not especially imposed by the controller structure but by the closed loop reference model. The resulting controller is fractional but it has a very interesting structure for its implementation. Indeed, the controller can be decomposed into two transfer functions: an integer transfer function which is generally an integer PID controller and a simple fractional filter. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Comparing the performance of expert user heuristics and an integer linear program in aircraft carrier deck operations.

Science.gov (United States)

Ryan, Jason C; Banerjee, Ashis Gopal; Cummings, Mary L; Roy, Nicholas

2014-06-01

Planning operations across a number of domains can be considered as resource allocation problems with timing constraints. An unexplored instance of such a problem domain is the aircraft carrier flight deck, where, in current operations, replanning is done without the aid of any computerized decision support. Rather, veteran operators employ a set of experience-based heuristics to quickly generate new operating schedules. These expert user heuristics are neither codified nor evaluated by the United States Navy; they have grown solely from the convergent experiences of supervisory staff. As unmanned aerial vehicles (UAVs) are introduced in the aircraft carrier domain, these heuristics may require alterations due to differing capabilities. The inclusion of UAVs also allows for new opportunities for on-line planning and control, providing an alternative to the current heuristic-based replanning methodology. To investigate these issues formally, we have developed a decision support system for flight deck operations that utilizes a conventional integer linear program-based planning algorithm. In this system, a human operator sets both the goals and constraints for the algorithm, which then returns a proposed schedule for operator approval. As a part of validating this system, the performance of this collaborative human-automation planner was compared with that of the expert user heuristics over a set of test scenarios. The resulting analysis shows that human heuristics often outperform the plans produced by an optimization algorithm, but are also often more conservative.

Genetic algorithm based reactive power dispatch for voltage stability improvement

Energy Technology Data Exchange (ETDEWEB)

Devaraj, D. [Department of Electrical and Electronics, Kalasalingam University, Krishnankoil 626 190 (India); Roselyn, J. Preetha [Department of Electrical and Electronics, SRM University, Kattankulathur 603 203, Chennai (India)

2010-12-15

Voltage stability assessment and control form the core function in a modern energy control centre. This paper presents an improved Genetic algorithm (GA) approach for voltage stability enhancement. The proposed technique is based on the minimization of the maximum of L-indices of load buses. Generator voltages, switchable VAR sources and transformer tap changers are used as optimization variables of this problem. The proposed approach permits the optimization variables to be represented in their natural form in the genetic population. For effective genetic processing, the crossover and mutation operators which can directly deal with the floating point numbers and integers are used. The proposed algorithm has been tested on IEEE 30-bus and IEEE 57-bus test systems and successful results have been obtained. (author)

An Elite Decision Making Harmony Search Algorithm for Optimization Problem

Directory of Open Access Journals (Sweden)

Lipu Zhang

2012-01-01

Full Text Available This paper describes a new variant of harmony search algorithm which is inspired by a well-known item “elite decision making.” In the new algorithm, the good information captured in the current global best and the second best solutions can be well utilized to generate new solutions, following some probability rule. The generated new solution vector replaces the worst solution in the solution set, only if its fitness is better than that of the worst solution. The generating and updating steps and repeated until the near-optimal solution vector is obtained. Extensive computational comparisons are carried out by employing various standard benchmark optimization problems, including continuous design variables and integer variables minimization problems from the literature. The computational results show that the proposed new algorithm is competitive in finding solutions with the state-of-the-art harmony search variants.

A new Tevatron Collider working point near the integer

International Nuclear Information System (INIS)

Johnson, R.P.; Zhang, P.

1989-12-01

It is well established that in hadron colliders the beam-beam interaction is more harmful in the presence of machine resonances of the form mν x + nν y = p, where |m| + |n| is the order of the resonance. Since the closest a resonance line can be to the integer stopband is 1/order, the closer the working point is to the integer, the fewer lower order resonances there are to enhance the beam-beam effects. A shift of the working point of the Tevatron from 19.4 to values near 19 and 20 has been studied. Problems with closed orbit control, dispersion matching, and matched low β insertions were considered. An excellent solution for the B0 insertion was found which has an improved β*. A new injection optics allows a transition to the low β optics which is much easier than the one now used. Results from the first machine studies demonstrate the ability to control the orbit with tunes of 19.03 horizontal and 20.03 vertical. Further studies require the activation of additional quadrupole compensation circuits. 4 refs. , 2 figs

Automated System for Teaching Computational Complexity of Algorithms Course

Directory of Open Access Journals (Sweden)

Vadim S. Roublev

2017-01-01

Full Text Available This article describes problems of designing automated teaching system for “Computational complexity of algorithms” course. This system should provide students with means to familiarize themselves with complex mathematical apparatus and improve their mathematical thinking in the respective area. The article introduces the technique of algorithms symbol scroll table that allows estimating lower and upper bounds of computational complexity. Further, we introduce a set of theorems that facilitate the analysis in cases when the integer rounding of algorithm parameters is involved and when analyzing the complexity of a sum. At the end, the article introduces a normal system of symbol transformations that allows one both to perform any symbol transformations and simplifies the automated validation of such transformations. The article is published in the authors’ wording.

A Streaming Distance Transform Algorithm for Neighborhood-Sequence Distances

Directory of Open Access Journals (Sweden)

Nicolas Normand

2014-09-01

Full Text Available We describe an algorithm that computes a “translated” 2D Neighborhood-Sequence Distance Transform (DT using a look up table approach. It requires a single raster scan of the input image and produces one line of output for every line of input. The neighborhood sequence is specified either by providing one period of some integer periodic sequence or by providing the rate of appearance of neighborhoods. The full algorithm optionally derives the regular (centered DT from the “translated” DT, providing the result image on-the-fly, with a minimal delay, before the input image is fully processed. Its efficiency can benefit all applications that use neighborhood- sequence distances, particularly when pipelined processing architectures are involved, or when the size of objects in the source image is limited.

APPLICATION OF NEURAL NETWORK ALGORITHMS FOR BPM LINEARIZATION

Energy Technology Data Exchange (ETDEWEB)

Musson, John C. [JLAB; Seaton, Chad [JLAB; Spata, Mike F. [JLAB; Yan, Jianxun [JLAB

2012-11-01

Stripline BPM sensors contain inherent non-linearities, as a result of field distortions from the pickup elements. Many methods have been devised to facilitate corrections, often employing polynomial fitting. The cost of computation makes real-time correction difficult, particulalry when integer math is utilized. The application of neural-network technology, particularly the multi-layer perceptron algorithm, is proposed as an efficient alternative for electrode linearization. A process of supervised learning is initially used to determine the weighting coefficients, which are subsequently applied to the incoming electrode data. A non-linear layer, known as an activation layer, is responsible for the removal of saturation effects. Implementation of a perceptron in an FPGA-based software-defined radio (SDR) is presented, along with performance comparisons. In addition, efficient calculation of the sigmoidal activation function via the CORDIC algorithm is presented.

Solving the Water Jugs Problem by an Integer Sequence Approach

Science.gov (United States)

Man, Yiu-Kwong

2012-01-01

In this article, we present an integer sequence approach to solve the classic water jugs problem. The solution steps can be obtained easily by additions and subtractions only, which is suitable for manual calculation or programming by computer. This approach can be introduced to secondary and undergraduate students, and also to teachers and…

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

Science.gov (United States)

Zörnig, Peter

2015-08-01

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

Seamless Vertical Handoff using Invasive Weed Optimization (IWO algorithm for heterogeneous wireless networks

Directory of Open Access Journals (Sweden)

T. Velmurugan

2016-03-01

Full Text Available Heterogeneous wireless networks are an integration of two different networks. For better performance, connections are to be exchanged among the different networks using seamless Vertical Handoff. The evolutionary algorithm of invasive weed optimization algorithm popularly known as the IWO has been used in this paper, to solve the Vertical Handoff (VHO and Horizontal Handoff (HHO problems. This integer coded algorithm is based on the colonizing behavior of weed plants and has been developed to optimize the system load and reduce the battery power consumption of the Mobile Node (MN. Constraints such as Receiver Signal Strength (RSS, battery lifetime, mobility, load and so on are taken into account. Individual as well as a combination of a number of factors are considered during decision process to make it more effective. This paper brings out the novel method of IWO algorithm for decision making during Vertical Handoff. Therefore the proposed VHO decision making algorithm is compared with the existing SSF and OPTG methods.

Time-Series INSAR: An Integer Least-Squares Approach For Distributed Scatterers

Science.gov (United States)

Samiei-Esfahany, Sami; Hanssen, Ramon F.

2012-01-01

The objective of this research is to extend the geode- tic mathematical model which was developed for persistent scatterers to a model which can exploit distributed scatterers (DS). The main focus is on the integer least- squares framework, and the main challenge is to include the decorrelation effect in the mathematical model. In order to adapt the integer least-squares mathematical model for DS we altered the model from a single master to a multi-master configuration and introduced the decorrelation effect stochastically. This effect is described in our model by a full covariance matrix. We propose to de- rive this covariance matrix by numerical integration of the (joint) probability distribution function (PDF) of interferometric phases. This PDF is a function of coherence values and can be directly computed from radar data. We show that the use of this model can improve the performance of temporal phase unwrapping of distributed scatterers.

Smart-Grid Backbone Network Real-Time Delay Reduction via Integer Programming.

Science.gov (United States)

Pagadrai, Sasikanth; Yilmaz, Muhittin; Valluri, Pratyush

2016-08-01

This research investigates an optimal delay-based virtual topology design using integer linear programming (ILP), which is applied to the current backbone networks such as smart-grid real-time communication systems. A network traffic matrix is applied and the corresponding virtual topology problem is solved using the ILP formulations that include a network delay-dependent objective function and lightpath routing, wavelength assignment, wavelength continuity, flow routing, and traffic loss constraints. The proposed optimization approach provides an efficient deterministic integration of intelligent sensing and decision making, and network learning features for superior smart grid operations by adaptively responding the time-varying network traffic data as well as operational constraints to maintain optimal virtual topologies. A representative optical backbone network has been utilized to demonstrate the proposed optimization framework whose simulation results indicate that superior smart-grid network performance can be achieved using commercial networks and integer programming.

Pattern-set generation algorithm for the one-dimensional multiple stock sizes cutting stock problem

Science.gov (United States)

Cui, Yaodong; Cui, Yi-Ping; Zhao, Zhigang

2015-09-01

A pattern-set generation algorithm (PSG) for the one-dimensional multiple stock sizes cutting stock problem (1DMSSCSP) is presented. The solution process contains two stages. In the first stage, the PSG solves the residual problems repeatedly to generate the patterns in the pattern set, where each residual problem is solved by the column-generation approach, and each pattern is generated by solving a single large object placement problem. In the second stage, the integer linear programming model of the 1DMSSCSP is solved using a commercial solver, where only the patterns in the pattern set are considered. The computational results of benchmark instances indicate that the PSG outperforms existing heuristic algorithms and rivals the exact algorithm in solution quality.

Application of Integer and Fractional Models in Electrochemical Systems

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Isabel S. Jesus

2012-01-01

Full Text Available This paper describes the use of integer and fractional electrical elements, for modelling two electrochemical systems. A first type of system consists of botanical elements and a second type is implemented by electrolyte processes with fractal electrodes. Experimental results are analyzed in the frequency domain, and the pros and cons of adopting fractional-order electrical components for modelling these systems are compared.

Penempatan Optimal Phasor Measurement Unit (PMU) Dengan Integer Programming

OpenAIRE

Amrulloh, Yunan Helmy

2013-01-01

Phasor Measurement Unit (PMU) merupakan peralatan yang mampu memberikan pengukuran fasor tegangan dan arus secara real-time. PMU dapat digunakan untuk monitoring, proteksi dan kontrol pada sistem tenaga listrik. Tugas akhir ini membahas penempatan PMU secara optimal berdasarkan topologi jaringan sehingga sistem tenaga listrik dapat diobservasi. Penempatan optimal PMU dirumuskan sebagai masalah Binary Integer Programming (BIP) yang akan memberikan variabel dengan pilihan nilai (0,1) yang menu...

How to build institutionalization on students: a pilot experiment on a didactical design of addition and subtraction involving negative integers

Science.gov (United States)

Fuadiah, N. F.; Suryadi, D.; Turmudi

2018-05-01

This study focuses on the design of a didactical situation in addition and subtraction involving negative integers at the pilot experiment phase. As we know, negative numbers become an obstacle for students in solving problems related to them. This study aims to create a didactical design that can assist students in understanding the addition and subtraction. Another expected result in this way is that students are introduced to the characteristics of addition and subtraction of integers. The design was implemented on 32 seventh grade students in one of the classes in a junior secondary school as the pilot experiment. Learning activities were observed thoroughly including the students’ responses that emerged during the learning activities. The written documentation of the students was also used to support the analysis in the learning activities. The results of the analysis showed that this method could help the students perform a large number of integer operations that could not be done with a number line. The teacher’s support as a didactical potential contract was still needed to encourage institutionalization processes. The results of the design analysis used as the basis of the revision are expected to be implemented by the teacher in the teaching experiment.

Half-integer flux quantum effect in cuprate superconductors - a probe of pairing symmetry

International Nuclear Information System (INIS)

Tsuei, C.C.; Kirtley, J.R.; Gupta, A.; Sun, J.Z.; Moler, K.A.; Wang, J.H.

1996-01-01

Based on macroscopic quantum coherence effects arising from pair tunneling and flux quantization, a series of tricrystal experiments have been designed and carried out to test the order parameter symmetry in high-T c cuprate superconductors. By using a scanning SQUID microscope, we have directly and non-invasively observed the spontaneously generated half-integer flux quantum effect in controlled-orientation tricrystal cuprate superconducting systems. The presence or absence of the half-integer flux quantum effect as a function of the tricrystal geometry allows us to prove that the order parameter symmetry in the YBCO and Tl2201 systems is consistent with that of the d x 2 -y 2 pair state. (orig.)

DESIGN OF DYADIC-INTEGER-COEFFICIENTS BASED BI-ORTHOGONAL WAVELET FILTERS FOR IMAGE SUPER-RESOLUTION USING SUB-PIXEL IMAGE REGISTRATION

Directory of Open Access Journals (Sweden)

P.B. Chopade

2014-05-01

Full Text Available This paper presents image super-resolution scheme based on sub-pixel image registration by the design of a specific class of dyadic-integer-coefficient based wavelet filters derived from the construction of a half-band polynomial. First, the integer-coefficient based half-band polynomial is designed by the splitting approach. Next, this designed half-band polynomial is factorized and assigned specific number of vanishing moments and roots to obtain the dyadic-integer coefficients low-pass analysis and synthesis filters. The possibility of these dyadic-integer coefficients based wavelet filters is explored in the field of image super-resolution using sub-pixel image registration. The two-resolution frames are registered at a specific shift from one another to restore the resolution lost by CCD array of camera. The discrete wavelet transform (DWT obtained from the designed coefficients is applied on these two low-resolution images to obtain the high resolution image. The developed approach is validated by comparing the quality metrics with existing filter banks.

Conference on Commutative rings, integer-valued polynomials and polynomial functions

CERN Document Server

Frisch, Sophie; Glaz, Sarah; Commutative Algebra : Recent Advances in Commutative Rings, Integer-Valued Polynomials, and Polynomial Functions

2014-01-01

This volume presents a multi-dimensional collection of articles highlighting recent developments in commutative algebra. It also includes an extensive bibliography and lists a substantial number of open problems that point to future directions of research in the represented subfields. The contributions cover areas in commutative algebra that have flourished in the last few decades and are not yet well represented in book form. Highlighted topics and research methods include Noetherian and non- Noetherian ring theory as well as integer-valued polynomials and functions. Specific topics include: ·    Homological dimensions of Prüfer-like rings ·    Quasi complete rings ·    Total graphs of rings ·    Properties of prime ideals over various rings ·    Bases for integer-valued polynomials ·    Boolean subrings ·    The portable property of domains ·    Probabilistic topics in Intn(D) ·    Closure operations in Zariski-Riemann spaces of valuation domains ·    Stability of do...

Behavioral Heterogeneity Affects Individual Performances in Experimental and Computational Lowest Unique Integer Games

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Takashi Yamada

2017-12-01

Full Text Available This study computationally examines (1 how the behaviors of subjects are represented, (2 whether the classification of subjects is related to the scale of the game, and (3 what kind of behavioral models are successful in small-sized lowest unique integer games (LUIGs. In a LUIG, N (≥ 3 players submit a positive integer up to M(> 1 and the player choosing the smallest number not chosen by anyone else wins. For this purpose, the author considers four LUIGs with N = {3, 4} and M = {3, 4} and uses the behavioral data obtained in the laboratory experiment by Yamada and Hanaki [1]. For computational experiments, the author calibrates the parameters of typical learning models for each subject and then pursues round robin competitions. The main findings are in the following: First, the subjects who played not differently from the mixed-strategy Nash equilibrium (MSE prediction tended to made use of not only their choices but also the game outcomes. Meanwhile those who deviated from the MSE prediction took care of only their choices as the complexity of the game increased. Second, the heterogeneity of player strategies depends on both the number of players (N and the upper limit (M. Third, when groups consist of different agents like in the earlier laboratory experiment, sticking behavior is quite effective to win.

Behavioral heterogeneity affects individual performances in experimental and computational lowest unique integer games

Science.gov (United States)

Yamada, Takashi

2017-12-01

This study computationally examines (1) how the behaviors of subjects are represented, (2) whether the classification of subjects is related to the scale of the game, and (3) what kind of behavioral models are successful in small-sized lowest unique integer games (LUIGs). In a LUIG, N (>= 3) players submit a positive integer up to M(> 1) and the player choosing the smallest number not chosen by anyone else wins. For this purpose, the author considers four LUIGs with N = {3, 4} and M = {3, 4} and uses the behavioral data obtained in the laboratory experiment by Yamada and Hanaki (Physica A 463, pp. 88–102, 2016). For computational experiments, the author calibrates the parameters of typical learning models for each subject and then pursues round robin competitions. The main findings are in the following: First, the subjects who played not differently from the mixed-strategy Nash equilibrium (MSE) prediction tended to made use of not only their choices but also the game outcomes. Meanwhile those who deviated from the MSE prediction took care of only their choices as the complexity of the game increased. Second, the heterogeneity of player strategies depends on both the number of players (N) and the upper limit (M). Third, when groups consist of different agents like in the earlier laboratory experiment, sticking behavior is quite effective to win.

Cause and effect analysis by fuzzy relational equations and a genetic algorithm

International Nuclear Information System (INIS)

Rotshtein, Alexander P.; Posner, Morton; Rakytyanska, Hanna B.

2006-01-01

This paper proposes using a genetic algorithm as a tool to solve the fault diagnosis problem. The fault diagnosis problem is based on a cause and effect analysis which is formally described by fuzzy relations. Fuzzy relations are formed on the basis of expert assessments. Application of expert fuzzy relations to restore and identify the causes through the observed effects requires the solution to a system of fuzzy relational equations. In this study this search for a solution amounts to solving a corresponding optimization problem. An optimization algorithm is based on the application of genetic operations of crossover, mutation and selection. The genetic algorithm suggested here represents an application in expert systems of fault diagnosis and quality control

Continuous-time quantum algorithms for unstructured problems

International Nuclear Information System (INIS)

Hen, Itay

2014-01-01

We consider a family of unstructured optimization problems, for which we propose a method for constructing analogue, continuous-time (not necessarily adiabatic) quantum algorithms that are faster than their classical counterparts. In this family of problems, which we refer to as ‘scrambled input’ problems, one has to find a minimum-cost configuration of a given integer-valued n-bit black-box function whose input values have been scrambled in some unknown way. Special cases within this set of problems are Grover’s search problem of finding a marked item in an unstructured database, certain random energy models, and the functions of the Deutsch–Josza problem. We consider a couple of examples in detail. In the first, we provide an O(1) deterministic analogue quantum algorithm to solve the seminal problem of Deutsch and Josza, in which one has to determine whether an n-bit boolean function is constant (gives 0 on all inputs or 1 on all inputs) or balanced (returns 0 on half the input states and 1 on the other half). We also study one variant of the random energy model, and show that, as one might expect, its minimum energy configuration can be found quadratically faster with a quantum adiabatic algorithm than with classical algorithms. (paper)

A relation between irreversibility and unlinkability for biometric template protection algorithms

OpenAIRE

井沼, 学

2014-01-01

For biometric recognition systems, privacy protection of enrolled users’ biometric information, which are called biometric templates, is a critical problem. Recently, various template protection algorithms have been proposed and many related previous works have discussed security notions to evaluate the protection performance of these protection algorithms. Irreversibility and unlinkability are important security notions discussed in many related previous works. In this paper, we prove that u...

Maximum likelihood pedigree reconstruction using integer linear programming.

Science.gov (United States)

Cussens, James; Bartlett, Mark; Jones, Elinor M; Sheehan, Nuala A

2013-01-01

Large population biobanks of unrelated individuals have been highly successful in detecting common genetic variants affecting diseases of public health concern. However, they lack the statistical power to detect more modest gene-gene and gene-environment interaction effects or the effects of rare variants for which related individuals are ideally required. In reality, most large population studies will undoubtedly contain sets of undeclared relatives, or pedigrees. Although a crude measure of relatedness might sometimes suffice, having a good estimate of the true pedigree would be much more informative if this could be obtained efficiently. Relatives are more likely to share longer haplotypes around disease susceptibility loci and are hence biologically more informative for rare variants than unrelated cases and controls. Distant relatives are arguably more useful for detecting variants with small effects because they are less likely to share masking environmental effects. Moreover, the identification of relatives enables appropriate adjustments of statistical analyses that typically assume unrelatedness. We propose to exploit an integer linear programming optimisation approach to pedigree learning, which is adapted to find valid pedigrees by imposing appropriate constraints. Our method is not restricted to small pedigrees and is guaranteed to return a maximum likelihood pedigree. With additional constraints, we can also search for multiple high-probability pedigrees and thus account for the inherent uncertainty in any particular pedigree reconstruction. The true pedigree is found very quickly by comparison with other methods when all individuals are observed. Extensions to more complex problems seem feasible. © 2012 Wiley Periodicals, Inc.

Metaheuristic Algorithms Applied to Bioenergy Supply Chain Problems: Theory, Review, Challenges, and Future

Directory of Open Access Journals (Sweden)

Krystel K. Castillo-Villar

2014-11-01

Full Text Available Bioenergy is a new source of energy that accounts for a substantial portion of the renewable energy production in many countries. The production of bioenergy is expected to increase due to its unique advantages, such as no harmful emissions and abundance. Supply-related problems are the main obstacles precluding the increase of use of biomass (which is bulky and has low energy density to produce bioenergy. To overcome this challenge, large-scale optimization models are needed to be solved to enable decision makers to plan, design, and manage bioenergy supply chains. Therefore, the use of effective optimization approaches is of great importance. The traditional mathematical methods (such as linear, integer, and mixed-integer programming frequently fail to find optimal solutions for non-convex and/or large-scale models whereas metaheuristics are efficient approaches for finding near-optimal solutions that use less computational resources. This paper presents a comprehensive review by studying and analyzing the application of metaheuristics to solve bioenergy supply chain models as well as the exclusive challenges of the mathematical problems applied in the bioenergy supply chain field. The reviewed metaheuristics include: (1 population approaches, such as ant colony optimization (ACO, the genetic algorithm (GA, particle swarm optimization (PSO, and bee colony algorithm (BCA; and (2 trajectory approaches, such as the tabu search (TS and simulated annealing (SA. Based on the outcomes of this literature review, the integrated design and planning of bioenergy supply chains problem has been solved primarily by implementing the GA. The production process optimization was addressed primarily by using both the GA and PSO. The supply chain network design problem was treated by utilizing the GA and ACO. The truck and task scheduling problem was solved using the SA and the TS, where the trajectory-based methods proved to outperform the population

Exact solutions to traffic density estimation problems involving the Lighthill-Whitham-Richards traffic flow model using mixed integer programming

KAUST Repository

Canepa, Edward S.; Claudel, Christian G.

2012-01-01

This article presents a new mixed integer programming formulation of the traffic density estimation problem in highways modeled by the Lighthill Whitham Richards equation. We first present an equivalent formulation of the problem using an Hamilton-Jacobi equation. Then, using a semi-analytic formula, we show that the model constraints resulting from the Hamilton-Jacobi equation result in linear constraints, albeit with unknown integers. We then pose the problem of estimating the density at the initial time given incomplete and inaccurate traffic data as a Mixed Integer Program. We then present a numerical implementation of the method using experimental flow and probe data obtained during Mobile Century experiment. © 2012 IEEE.

Exact solutions to traffic density estimation problems involving the Lighthill-Whitham-Richards traffic flow model using mixed integer programming

KAUST Repository

Canepa, Edward S.

2012-09-01

This article presents a new mixed integer programming formulation of the traffic density estimation problem in highways modeled by the Lighthill Whitham Richards equation. We first present an equivalent formulation of the problem using an Hamilton-Jacobi equation. Then, using a semi-analytic formula, we show that the model constraints resulting from the Hamilton-Jacobi equation result in linear constraints, albeit with unknown integers. We then pose the problem of estimating the density at the initial time given incomplete and inaccurate traffic data as a Mixed Integer Program. We then present a numerical implementation of the method using experimental flow and probe data obtained during Mobile Century experiment. © 2012 IEEE.

Optimizing models for production and inventory control using a genetic algorithm

Directory of Open Access Journals (Sweden)

Dragan S. Pamučar

2012-01-01

Full Text Available In order to make the Economic Production Quantity (EPQ model more applicable to real-world production and inventory control problems, in this paper we expand this model by assuming that some imperfect items of different product types being produced such as reworks are allowed. In addition, we may have more than one product and supplier along with warehouse space and budget limitation. We show that the model of the problem is a constrained non-linear integer program and propose a genetic algorithm to solve it. Moreover, a design of experiments is employed to calibrate the parameters of the algorithm for different problem sizes. In the end, a numerical example is presented to demonstrate the application of the proposed methodology.

Energetic integration of discontinuous processes by means of genetic algorithms, GABSOBHIN; Integration energetique de procedes discontinus a l'aide d'algorithmes genetiques, GABSOBHIN

Energy Technology Data Exchange (ETDEWEB)

Krummenacher, P.; Renaud, B.; Marechal, F.; Favrat, D.

2001-07-01

This report presents a new methodological approach for the optimal design of energy-integrated batch processes. The main emphasis is put on indirect and, to some extend, on direct heat exchange networks with the possibility of introducing closed or open storage systems. The study demonstrates the feasibility of optimising with genetic algorithms while highlighting the pros and cons of this type of approach. The study shows that the resolution of such problems should preferably be done in several steps to better target the expected solutions. Demonstration is made that in spite of relatively large computer times (on PCs) the use of genetic algorithm allows the consideration of both continuous decision variables (size, operational rating of equipment, etc.) and integer variables (related to the structure at design and during operation). Comparison of two optimisation strategies is shown with a preference for a two-steps optimisation scheme. One of the strengths of genetic algorithms is the capacity to accommodate heuristic rules, which can be introduced in the model. However, a rigorous modelling strategy is advocated to improve robustness and adequate coding of the decision variables. The practical aspects of the research work are converted into a software developed with MATLAB to solve the energy integration of batch processes with a reasonable number of closed or open stores. This software includes the model of superstructures, including the heat exchangers and the storage alternatives, as well as the link to the Struggle algorithm developed at MIT via a dedicated new interface. The package also includes a user-friendly pre-processing using EXCEL, which is to facilitate to application to other similar industrial problems. These software developments have been validated both on an academic and on an industrial type of problems. (author)

Non-Porod scattering and non-integer scaling of resistance in rough films

Science.gov (United States)

Bupathy, Arunkumar; Verma, Rupesh; Banerjee, Varsha; Puri, Sanjay

2017-04-01

In many physical systems, films are rough due to the stochastic behavior of depositing particles. They are characterized by non-Porod power law decays in the structure factor S (k) . Theoretical studies predict anomalous diffusion in such morphologies, with important implications for diffusivity, conductivity, etc. We use the non-Porod decay to accurately determine the fractal properties of two prototypical nanoparticle films: (i) Palladium (Pd) and (ii) Cu2O. Using scaling arguments, we find that the resistance of rough films of lateral size L obeys a non-integer power law R ∼L-ζ , in contrast to integer power laws for compact structures. The exponent ζ is anisotropic. We confirm our predictions by re-analyzing experimental data from Cu2O nano-particle films. Our results are valuable for understanding recent experiments that report anisotropic electrical properties in (rough) thin films.

Accurate Computation of Periodic Regions' Centers in the General M-Set with Integer Index Number

Directory of Open Access Journals (Sweden)

Wang Xingyuan

2010-01-01

Full Text Available This paper presents two methods for accurately computing the periodic regions' centers. One method fits for the general M-sets with integer index number, the other fits for the general M-sets with negative integer index number. Both methods improve the precision of computation by transforming the polynomial equations which determine the periodic regions' centers. We primarily discuss the general M-sets with negative integer index, and analyze the relationship between the number of periodic regions' centers on the principal symmetric axis and in the principal symmetric interior. We can get the centers' coordinates with at least 48 significant digits after the decimal point in both real and imaginary parts by applying the Newton's method to the transformed polynomial equation which determine the periodic regions' centers. In this paper, we list some centers' coordinates of general M-sets' k-periodic regions (k=3,4,5,6 for the index numbers α=−25,−24,…,−1 , all of which have highly numerical accuracy.

A branch-and-cut algorithm for the vehicle routing problem with multiple use of vehicles

Directory of Open Access Journals (Sweden)

İsmail Karaoğlan

2015-06-01

Full Text Available This paper addresses the vehicle routing problem with multiple use of vehicles (VRPMUV, an important variant of the classic vehicle routing problem (VRP. Unlike the classical VRP, vehicles are allowed to use more than one route in the VRPMUV. We propose a branch-and-cut algorithm for solving the VRPMUV. The proposed algorithm includes several valid inequalities from the literature for the purpose of improving its lower bounds, and a heuristic algorithm based on simulated annealing and a mixed integer programming-based intensification procedure for obtaining the upper bounds. The algorithm is evaluated in terms of the test problems derived from the literature. The computational results which follow show that, if there were 120 customers on the route (in the simulation, the problem would be solved optimally in a reasonable amount of time.

Music algorithm for imaging of a sound-hard arc in limited-view inverse scattering problem

Science.gov (United States)

Park, Won-Kwang

2017-07-01

MUltiple SIgnal Classification (MUSIC) algorithm for a non-iterative imaging of sound-hard arc in limited-view inverse scattering problem is considered. In order to discover mathematical structure of MUSIC, we derive a relationship between MUSIC and an infinite series of Bessel functions of integer order. This structure enables us to examine some properties of MUSIC in limited-view problem. Numerical simulations are performed to support the identified structure of MUSIC.

Integer Charge Transfer and Hybridization at an Organic Semiconductor/Conductive Oxide Interface

KAUST Repository

Gruenewald, Marco; Schirra, Laura K.; Winget, Paul; Kozlik, Michael; Ndione, Paul F.; Sigdel, Ajaya K.; Berry, Joseph J.; Forker, Roman; Bredas, Jean-Luc; Fritz, Torsten; Monti, Oliver L. A.

2015-01-01

with localized states (the shallow donors) in the substrate and charge back-donation, resulting in an effectively integer charge transfer across the interface. Charge transfer is thus not merely a question of locating the Fermi level above the PTCDA electron

Applications exponential approximation by integer shifts of Gaussian functions

Directory of Open Access Journals (Sweden)

S. M. Sitnik

2013-01-01

Full Text Available In this paper we consider approximations of functions using integer shifts of Gaussians – quadratic exponentials. A method is proposed to find coefficients of node functions by solving linear systems of equations. The explicit formula for the determinant of the system is found, based on it solvability of linear system under consideration is proved and uniqueness of its solution. We compare results with known ones and briefly indicate applications to signal theory.

Binary integer programming solution for troubleshooting with dependent actions

Czech Academy of Sciences Publication Activity Database

Lín, Václav

2017-01-01

Roč. 53, č. 3 (2017), s. 493-512 ISSN 0023-5954 R&D Projects: GA ČR GA13-20012S Institutional support: RVO:67985556 Keywords : binary integer programming * decision-theoretic troubleshooting Subject RIV: JD - Computer Applications, Robotics OBOR OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8) Impact factor: 0.379, year: 2016 http://library.utia.cas.cz/separaty/2017/MTR/lin-0476547.pdf

Sheaves in Elementary Mathematics: The case of positive integer numbers

OpenAIRE

Luna-Torres, Joaquin

2015-01-01

We aim to use the concept of sheaf to establish a link between certain aspects of the set of positive integers numbers, a topic corresponding to the elementary mathematics, and some fundamental ideas of contemporary mathematics. We hope that this type of approach helps the school students to restate some problems of elementary mathematics in an environment deeper and suitable for its study.

New Mathematical Model and Algorithm for Economic Lot Scheduling Problem in Flexible Flow Shop

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H. Zohali

2018-03-01

Full Text Available This paper addresses the lot sizing and scheduling problem for a number of products in flexible flow shop with identical parallel machines. The production stages are in series, while separated by finite intermediate buffers. The objective is to minimize the sum of setup and inventory holding costs per unit of time. The available mathematical model of this problem in the literature suffers from huge complexity in terms of size and computation. In this paper, a new mixed integer linear program is developed for delay with the huge dimentions of the problem. Also, a new meta heuristic algorithm is developed for the problem. The results of the numerical experiments represent a significant advantage of the proposed model and algorithm compared with the available models and algorithms in the literature.

Improving energy efficiency in handheld biometric applications

Science.gov (United States)

Hoyle, David C.; Gale, John W.; Schultz, Robert C.; Rakvic, Ryan N.; Ives, Robert W.

2012-06-01

With improved smartphone and tablet technology, it is becoming increasingly feasible to implement powerful biometric recognition algorithms on portable devices. Typical iris recognition algorithms, such as Ridge Energy Direction (RED), utilize two-dimensional convolution in their implementation. This paper explores the energy consumption implications of 12 different methods of implementing two-dimensional convolution on a portable device. Typically, convolution is implemented using floating point operations. If a given algorithm implemented integer convolution vice floating point convolution, it could drastically reduce the energy consumed by the processor. The 12 methods compared include 4 major categories: Integer C, Integer Java, Floating Point C, and Floating Point Java. Each major category is further divided into 3 implementations: variable size looped convolution, static size looped convolution, and unrolled looped convolution. All testing was performed using the HTC Thunderbolt with energy measured directly using a Tektronix TDS5104B Digital Phosphor oscilloscope. Results indicate that energy savings as high as 75% are possible by using Integer C versus Floating Point C. Considering the relative proportion of processing time that convolution is responsible for in a typical algorithm, the savings in energy would likely result in significantly greater time between battery charges.

Performance of a cavity-method-based algorithm for the prize-collecting Steiner tree problem on graphs

Science.gov (United States)

Biazzo, Indaco; Braunstein, Alfredo; Zecchina, Riccardo

2012-08-01

We study the behavior of an algorithm derived from the cavity method for the prize-collecting steiner tree (PCST) problem on graphs. The algorithm is based on the zero temperature limit of the cavity equations and as such is formally simple (a fixed point equation resolved by iteration) and distributed (parallelizable). We provide a detailed comparison with state-of-the-art algorithms on a wide range of existing benchmarks, networks, and random graphs. Specifically, we consider an enhanced derivative of the Goemans-Williamson heuristics and the dhea solver, a branch and cut integer linear programming based approach. The comparison shows that the cavity algorithm outperforms the two algorithms in most large instances both in running time and quality of the solution. Finally we prove a few optimality properties of the solutions provided by our algorithm, including optimality under the two postprocessing procedures defined in the Goemans-Williamson derivative and global optimality in some limit cases.

Integer programming of cement distribution by train

Science.gov (United States)

Indarsih

2018-01-01

Cement industry in Central Java distributes cement by train to meet daily demand in Yogyakarta and Central Java area. There are five destination stations. For each destination station, there is a warehouse to load cements. Decision maker of cement industry have a plan to redesign the infrastructure and transportation system. The aim is to determine how many locomotives, train wagons, and containers and how to arrange train schedules with subject to the delivery time. For this purposes, we consider an integer programming to minimize the total of operational cost. Further, we will discuss a case study and the solution the problem can be calculated by LINGO software.

CBLIB 2014: a benchmark library for conic mixed-integer and continuous optimization

DEFF Research Database (Denmark)

Friberg, Henrik Alsing

2016-01-01

The Conic Benchmark Library is an ongoing community-driven project aiming to challenge commercial and open source solvers on mainstream cone support. In this paper, 121 mixed-integer and continuous second-order cone problem instances have been selected from 11 categories as representative...

Mixed-integer nonlinear approach for the optimal scheduling of a head-dependent hydro chain

Energy Technology Data Exchange (ETDEWEB)

Catalao, J.P.S.; Pousinho, H.M.I. [Department of Electromechanical Engineering, University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilha (Portugal); Mendes, V.M.F. [Department of Electrical Engineering and Automation, Instituto Superior de Engenharia de Lisboa, R. Conselheiro Emidio Navarro, 1950-062 Lisbon (Portugal)

2010-08-15

This paper is on the problem of short-term hydro scheduling (STHS), particularly concerning a head-dependent hydro chain. We propose a novel mixed-integer nonlinear programming (MINLP) approach, considering hydroelectric power generation as a nonlinear function of water discharge and of the head. As a new contribution to earlier studies, we model the on-off behavior of the hydro plants using integer variables, in order to avoid water discharges at forbidden areas. Thus, an enhanced STHS is provided due to the more realistic modeling presented in this paper. Our approach has been applied successfully to solve a test case based on one of the Portuguese cascaded hydro systems with a negligible computational time requirement. (author)

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

Directory of Open Access Journals (Sweden)

Adi Wicaksono Purnawan

2018-01-01

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

A multiobjective non-dominated sorting genetic algorithm (NSGA-II for the Multiple Traveling Salesman Problem

Directory of Open Access Journals (Sweden)

Rubén Iván Bolaños

2015-06-01

Full Text Available This paper considers a multi-objective version of the Multiple Traveling Salesman Problem (MOmTSP. In particular, two objectives are considered: the minimization of the total traveled distance and the balance of the working times of the traveling salesmen. The problem is formulated as an integer multi-objective optimization model. A non-dominated sorting genetic algorithm (NSGA-II is proposed to solve the MOmTSP. The solution scheme allows one to find a set of ordered solutions in Pareto fronts by considering the concept of dominance. Tests on real world instances and instances adapted from the literature show the effectiveness of the proposed algorithm.

On-line Certification for All: The PINVOX Algorithm

Directory of Open Access Journals (Sweden)

E Canessa

2012-09-01

Full Text Available A protoype algorithm: PINVOX (“Personal Identification Number by Voice" for on-line certification is introduced to guarantee that scholars have followed, i.e., listened and watched, a complete recorded lecture with the option of earning a certificate or diploma of completion after remotely attending courses. It is based on the injection of unique, randomly selected and pre-recorded integer numbers (or single letters or words within the audio trace of a video stream at places where silence is automatically detected. The certificate of completion or “virtual attendance” is generated on-the-fly after the successful identification of the embedded PINVOX code by a video viewer student.

Raw material utilization in slaughterhouses – optimizing expected profit using mixed-integer programming

DEFF Research Database (Denmark)

Jensen, Toke Koldborg; Kjærsgaard, Niels Christian

Slaughterhouses are major players in the pork supply chain, and supply and demand must be matched in order to generate the highest profit. In particular, carcasses must be sorted in order to produce the “right” final products from the “right” carcasses. We develop a mixed-integer programming (MIP) ...... at slaughterhouses. Finally, we comment on the expected effect of variations in the raw material supply and the demand as well as future research concerning joint modelling of supply chain aspects.......Slaughterhouses are major players in the pork supply chain, and supply and demand must be matched in order to generate the highest profit. In particular, carcasses must be sorted in order to produce the “right” final products from the “right” carcasses. We develop a mixed-integer programming (MIP...

Complexity transitions in global algorithms for sparse linear systems over finite fields

Science.gov (United States)

Braunstein, A.; Leone, M.; Ricci-Tersenghi, F.; Zecchina, R.

2002-09-01

We study the computational complexity of a very basic problem, namely that of finding solutions to a very large set of random linear equations in a finite Galois field modulo q. Using tools from statistical mechanics we are able to identify phase transitions in the structure of the solution space and to connect them to the changes in the performance of a global algorithm, namely Gaussian elimination. Crossing phase boundaries produces a dramatic increase in memory and CPU requirements necessary for the algorithms. In turn, this causes the saturation of the upper bounds for the running time. We illustrate the results on the specific problem of integer factorization, which is of central interest for deciphering messages encrypted with the RSA cryptosystem.

Complexity transitions in global algorithms for sparse linear systems over finite fields

International Nuclear Information System (INIS)

Braunstein, A.; Leone, M.; Ricci-Tersenghi, F. . Federico.Ricci@roma1.infn.it; Zecchina, R.

2002-01-01

We study the computational complexity of a very basic problem, namely that of finding solutions to a very large set of random linear equations in a finite Galois field modulo q. Using tools from statistical mechanics we are able to identify phase transitions in the structure of the solution space and to connect them to the changes in the performance of a global algorithm, namely Gaussian elimination. Crossing phase boundaries produces a dramatic increase in memory and CPU requirements necessary for the algorithms. In turn, this causes the saturation of the upper bounds for the running time. We illustrate the results on the specific problem of integer factorization, which is of central interest for deciphering messages encrypted with the RSA cryptosystem. (author)

A hybrid Constraint Programming/Mixed Integer Programming framework for the preventive signaling maintenance crew scheduling problem

DEFF Research Database (Denmark)

Pour, Shahrzad M.; Drake, John H.; Ejlertsen, Lena Secher

2017-01-01

A railway signaling system is a complex and interdependent system which should ensure the safe operation of trains. We introduce and address a mixed integer optimisation model for the preventive signal maintenance crew scheduling problem in the Danish railway system. The problem contains many...... to feed as ‘warm start’ solutions to a Mixed Integer Programming (MIP) solver for further optimisation. We apply the CP/MIP framework to a section of the Danish rail network and benchmark our results against both direct application of a MIP solver and modelling the problem as a Constraint Optimisation...

Experimental design for estimating unknown groundwater pumping using genetic algorithm and reduced order model

Science.gov (United States)

Ushijima, Timothy T.; Yeh, William W.-G.

2013-10-01

An optimal experimental design algorithm is developed to select locations for a network of observation wells that provide maximum information about unknown groundwater pumping in a confined, anisotropic aquifer. The design uses a maximal information criterion that chooses, among competing designs, the design that maximizes the sum of squared sensitivities while conforming to specified design constraints. The formulated optimization problem is non-convex and contains integer variables necessitating a combinatorial search. Given a realistic large-scale model, the size of the combinatorial search required can make the problem difficult, if not impossible, to solve using traditional mathematical programming techniques. Genetic algorithms (GAs) can be used to perform the global search; however, because a GA requires a large number of calls to a groundwater model, the formulated optimization problem still may be infeasible to solve. As a result, proper orthogonal decomposition (POD) is applied to the groundwater model to reduce its dimensionality. Then, the information matrix in the full model space can be searched without solving the full model. Results from a small-scale test case show identical optimal solutions among the GA, integer programming, and exhaustive search methods. This demonstrates the GA's ability to determine the optimal solution. In addition, the results show that a GA with POD model reduction is several orders of magnitude faster in finding the optimal solution than a GA using the full model. The proposed experimental design algorithm is applied to a realistic, two-dimensional, large-scale groundwater problem. The GA converged to a solution for this large-scale problem.

Relaxation and decomposition methods for mixed integer nonlinear programming

CERN Document Server

Nowak, Ivo; Bank, RE

2005-01-01

This book presents a comprehensive description of efficient methods for solving nonconvex mixed integer nonlinear programs, including several numerical and theoretical results, which are presented here for the first time. It contains many illustrations and an up-to-date bibliography. Because on the emphasis on practical methods, as well as the introduction into the basic theory, the book is accessible to a wide audience. It can be used both as a research and as a graduate text.

An efficient particle swarm approach for mixed-integer programming in reliability-redundancy optimization applications

International Nuclear Information System (INIS)

Santos Coelho, Leandro dos

2009-01-01

The reliability-redundancy optimization problems can involve the selection of components with multiple choices and redundancy levels that produce maximum benefits, and are subject to the cost, weight, and volume constraints. Many classical mathematical methods have failed in handling nonconvexities and nonsmoothness in reliability-redundancy optimization problems. As an alternative to the classical optimization approaches, the meta-heuristics have been given much attention by many researchers due to their ability to find an almost global optimal solutions. One of these meta-heuristics is the particle swarm optimization (PSO). PSO is a population-based heuristic optimization technique inspired by social behavior of bird flocking and fish schooling. This paper presents an efficient PSO algorithm based on Gaussian distribution and chaotic sequence (PSO-GC) to solve the reliability-redundancy optimization problems. In this context, two examples in reliability-redundancy design problems are evaluated. Simulation results demonstrate that the proposed PSO-GC is a promising optimization technique. PSO-GC performs well for the two examples of mixed-integer programming in reliability-redundancy applications considered in this paper. The solutions obtained by the PSO-GC are better than the previously best-known solutions available in the recent literature

An efficient particle swarm approach for mixed-integer programming in reliability-redundancy optimization applications

Energy Technology Data Exchange (ETDEWEB)

Santos Coelho, Leandro dos [Industrial and Systems Engineering Graduate Program, LAS/PPGEPS, Pontifical Catholic University of Parana, PUCPR, Imaculada Conceicao, 1155, 80215-901 Curitiba, Parana (Brazil)], E-mail: leandro.coelho@pucpr.br

2009-04-15

The reliability-redundancy optimization problems can involve the selection of components with multiple choices and redundancy levels that produce maximum benefits, and are subject to the cost, weight, and volume constraints. Many classical mathematical methods have failed in handling nonconvexities and nonsmoothness in reliability-redundancy optimization problems. As an alternative to the classical optimization approaches, the meta-heuristics have been given much attention by many researchers due to their ability to find an almost global optimal solutions. One of these meta-heuristics is the particle swarm optimization (PSO). PSO is a population-based heuristic optimization technique inspired by social behavior of bird flocking and fish schooling. This paper presents an efficient PSO algorithm based on Gaussian distribution and chaotic sequence (PSO-GC) to solve the reliability-redundancy optimization problems. In this context, two examples in reliability-redundancy design problems are evaluated. Simulation results demonstrate that the proposed PSO-GC is a promising optimization technique. PSO-GC performs well for the two examples of mixed-integer programming in reliability-redundancy applications considered in this paper. The solutions obtained by the PSO-GC are better than the previously best-known solutions available in the recent literature.

Multiplicity of summands in the random partitions of an integer

Indian Academy of Sciences (India)

We prove that the probability that there is a summand of multiplicity j in any randomly chosen partition or composition of an integer n goes to zero asymptotically with n provided j is larger than a critical value. As a corollary, we strengthen a result due to Erdös and Lehner (Duke. Math. J. 8 (1941) 335–345) that concerns the ...

A novel minimum cost maximum power algorithm for future smart home energy management.

Science.gov (United States)

Singaravelan, A; Kowsalya, M

2017-11-01

With the latest development of smart grid technology, the energy management system can be efficiently implemented at consumer premises. In this paper, an energy management system with wireless communication and smart meter are designed for scheduling the electric home appliances efficiently with an aim of reducing the cost and peak demand. For an efficient scheduling scheme, the appliances are classified into two types: uninterruptible and interruptible appliances. The problem formulation was constructed based on the practical constraints that make the proposed algorithm cope up with the real-time situation. The formulated problem was identified as Mixed Integer Linear Programming (MILP) problem, so this problem was solved by a step-wise approach. This paper proposes a novel Minimum Cost Maximum Power (MCMP) algorithm to solve the formulated problem. The proposed algorithm was simulated with input data available in the existing method. For validating the proposed MCMP algorithm, results were compared with the existing method. The compared results prove that the proposed algorithm efficiently reduces the consumer electricity consumption cost and peak demand to optimum level with 100% task completion without sacrificing the consumer comfort.

A Relative-Localization Algorithm Using Incomplete Pairwise Distance Measurements for Underwater Applications

Directory of Open Access Journals (Sweden)

Kae Y. Foo

2010-01-01

Full Text Available The task of localizing underwater assets involves the relative localization of each unit using only pairwise distance measurements, usually obtained from time-of-arrival or time-delay-of-arrival measurements. In the fluctuating underwater environment, a complete set of pair-wise distance measurements can often be difficult to acquire, thus hindering a straightforward closed-form solution in deriving the assets' relative coordinates. An iterative multidimensional scaling approach is presented based upon a weighted-majorization algorithm that tolerates missing or inaccurate distance measurements. Substantial modifications are proposed to optimize the algorithm, while the effects of refractive propagation paths are considered. A parametric study of the algorithm based upon simulation results is shown. An acoustic field-trial was then carried out, presenting field measurements to highlight the practical implementation of this algorithm.

Unwinding the hairball graph: Pruning algorithms for weighted complex networks

Science.gov (United States)

Dianati, Navid

2016-01-01

Empirical networks of weighted dyadic relations often contain "noisy" edges that alter the global characteristics of the network and obfuscate the most important structures therein. Graph pruning is the process of identifying the most significant edges according to a generative null model and extracting the subgraph consisting of those edges. Here, we focus on integer-weighted graphs commonly arising when weights count the occurrences of an "event" relating the nodes. We introduce a simple and intuitive null model related to the configuration model of network generation and derive two significance filters from it: the marginal likelihood filter (MLF) and the global likelihood filter (GLF). The former is a fast algorithm assigning a significance score to each edge based on the marginal distribution of edge weights, whereas the latter is an ensemble approach which takes into account the correlations among edges. We apply these filters to the network of air traffic volume between US airports and recover a geographically faithful representation of the graph. Furthermore, compared with thresholding based on edge weight, we show that our filters extract a larger and significantly sparser giant component.

Learning decision trees with flexible constraints and objectives using integer optimization

NARCIS (Netherlands)

Verwer, S.; Zhang, Y.

2017-01-01

We encode the problem of learning the optimal decision tree of a given depth as an integer optimization problem. We show experimentally that our method (DTIP) can be used to learn good trees up to depth 5 from data sets of size up to 1000. In addition to being efficient, our new formulation allows

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.

Improved Genetic and Simulating Annealing Algorithms to Solve the Traveling Salesman Problem Using Constraint Programming

Directory of Open Access Journals (Sweden)

M. Abdul-Niby

2016-04-01

Full Text Available The Traveling Salesman Problem (TSP is an integer programming problem that falls into the category of NP-Hard problems. As the problem become larger, there is no guarantee that optimal tours will be found within reasonable computation time. Heuristics techniques, like genetic algorithm and simulating annealing, can solve TSP instances with different levels of accuracy. Choosing which algorithm to use in order to get a best solution is still considered as a hard choice. This paper suggests domain reduction as a tool to be combined with any meta-heuristic so that the obtained results will be almost the same. The hybrid approach of combining domain reduction with any meta-heuristic encountered the challenge of choosing an algorithm that matches the TSP instance in order to get the best results.

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

Directory of Open Access Journals (Sweden)

Alin Cristian Ioan

2010-03-01

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

Integer Charge Transfer and Hybridization at an Organic Semiconductor/Conductive Oxide Interface

KAUST Repository

Gruenewald, Marco

2015-02-11

We investigate the prototypical hybrid interface formed between PTCDA and conductive n-doped ZnO films by means of complementary optical and electronic spectroscopic techniques. We demonstrate that shallow donors in the vicinity of the ZnO surface cause an integer charge transfer to PTCDA, which is clearly restricted to the first monolayer. By means of DFT calculations, we show that the experimental signatures of the anionic PTCDA species can be understood in terms of strong hybridization with localized states (the shallow donors) in the substrate and charge back-donation, resulting in an effectively integer charge transfer across the interface. Charge transfer is thus not merely a question of locating the Fermi level above the PTCDA electron-transport level but requires rather an atomistic understanding of the interfacial interactions. The study reveals that defect sites and dopants can have a significant influence on the specifics of interfacial coupling and thus on carrier injection or extraction.

Testosterone metabolism in the estuarine mysid Neomysis integer (Crustacea; Mysidacea) following tributyltin exposure.

Science.gov (United States)

Verslycke, Tim; Poelmans, Sofie; De Wasch, Katia; Vercauteren, Jordy; Devos, Christophe; Moens, Luc; Sandra, Patrick; De Brabander, Hubert F; Janssen, Colin R

2003-09-01

Current evidence suggests that the biocide tributyltin (TBT) causes the development of imposex, a state of pseudohermaphrodism in which females exhibit functional secondary male characteristics, by altering the biotransformation or elimination of testosterone. Imposex in gastropods following TBT exposure is the most complete example of the effects of an endocrine disrupter on marine invertebrates. Previous studies have demonstrated that the estuarine mysid Neomysis integer converts testosterone into multiple polar and nonpolar metabolites resulting from both phase I and phase II biotransformations. In this study, the effects of TBT chloride (TBTCl) on the phase I and II testosterone metabolism of N. integer were evaluated. The TBTCl was highly toxic to N. integer (96-h median lethal concentration [LC50] of 164 ng/L). To assess the effects on testosterone metabolism, mysids were exposed for 96 h to different concentrations of TBTCl (control, 10, 100, and 1,000 ng/L), and testosterone elimination as polar hydroxylated, nonpolar oxido-reduced, and glucose- and sulfate-conjugated metabolites was examined. The TBTCl differentially affected testosterone metabolism. The effect of TBTCl on phase I metabolism was unclear and has been shown to vary among species, likely depending on the inducibility or presence of certain P450 isozyme families. Reductase activity and metabolic androgenization were induced in the 10-ng/L treatment, whereas higher concentrations resulted in a reduction of sulfate conjugation. The exact mechanisms underlying TBT-induced imposex and alterations in the steroid metabolism need to be further elucidated.

Integer-linear-programing optimization in scalable video multicast with adaptive modulation and coding in wireless networks.

Science.gov (United States)

Lee, Dongyul; Lee, Chaewoo

2014-01-01

The advancement in wideband wireless network supports real time services such as IPTV and live video streaming. However, because of the sharing nature of the wireless medium, efficient resource allocation has been studied to achieve a high level of acceptability and proliferation of wireless multimedia. Scalable video coding (SVC) with adaptive modulation and coding (AMC) provides an excellent solution for wireless video streaming. By assigning different modulation and coding schemes (MCSs) to video layers, SVC can provide good video quality to users in good channel conditions and also basic video quality to users in bad channel conditions. For optimal resource allocation, a key issue in applying SVC in the wireless multicast service is how to assign MCSs and the time resources to each SVC layer in the heterogeneous channel condition. We formulate this problem with integer linear programming (ILP) and provide numerical results to show the performance under 802.16 m environment. The result shows that our methodology enhances the overall system throughput compared to an existing algorithm.

Integer-Linear-Programing Optimization in Scalable Video Multicast with Adaptive Modulation and Coding in Wireless Networks

Directory of Open Access Journals (Sweden)

Dongyul Lee

2014-01-01

Full Text Available The advancement in wideband wireless network supports real time services such as IPTV and live video streaming. However, because of the sharing nature of the wireless medium, efficient resource allocation has been studied to achieve a high level of acceptability and proliferation of wireless multimedia. Scalable video coding (SVC with adaptive modulation and coding (AMC provides an excellent solution for wireless video streaming. By assigning different modulation and coding schemes (MCSs to video layers, SVC can provide good video quality to users in good channel conditions and also basic video quality to users in bad channel conditions. For optimal resource allocation, a key issue in applying SVC in the wireless multicast service is how to assign MCSs and the time resources to each SVC layer in the heterogeneous channel condition. We formulate this problem with integer linear programming (ILP and provide numerical results to show the performance under 802.16 m environment. The result shows that our methodology enhances the overall system throughput compared to an existing algorithm.

A Mixed Integer Programming for Port Anzali Development Plan

OpenAIRE

Mahdieh Allahviranloo

2009-01-01

This paper introduces a mixed integer programming model to find the optimum development plan for port Anzali. The model minimizes total system costs taking into account both port infrastructure costs and shipping costs. Due to the multipurpose function of the port, the model consists of 1020 decision variables and 2490 constraints. Results of the model determine the optimum number of berths that should be constructed in each period and for each type of cargo. In addition to, the results of se...

Ant Colony Algorithm and Simulation for Robust Airport Gate Assignment

Directory of Open Access Journals (Sweden)

Hui Zhao

2014-01-01

Full Text Available Airport gate assignment is core task for airport ground operations. Due to the fact that the departure and arrival time of flights may be influenced by many random factors, the airport gate assignment scheme may encounter gate conflict and many other problems. This paper aims at finding a robust solution for airport gate assignment problem. A mixed integer model is proposed to formulate the problem, and colony algorithm is designed to solve this model. Simulation result shows that, in consideration of robustness, the ability of antidisturbance for airport gate assignment scheme has much improved.

ALGORITHM FOR DYNAMIC SCALING RELATIONAL DATABASE IN CLOUDS

Directory of Open Access Journals (Sweden)

Alexander V. Boichenko

2014-01-01

Full Text Available This article analyzes the main methods of scalingdatabases (replication, sharding and their supportat the popular relational databases and NoSQLsolutions with different data models: document-oriented, key-value, column-oriented and graph.The article presents an algorithm for the dynamicscaling of a relational database (DB, that takesinto account the specifics of the different types of logic database model. This article was prepared with the support of RFBR (grant № 13-07-00749.

Runway Operations Planning: A Two-Stage Heuristic Algorithm

Science.gov (United States)

Anagnostakis, Ioannis; Clarke, John-Paul

2003-01-01

The airport runway is a scarce resource that must be shared by different runway operations (arrivals, departures and runway crossings). Given the possible sequences of runway events, careful Runway Operations Planning (ROP) is required if runway utilization is to be maximized. From the perspective of departures, ROP solutions are aircraft departure schedules developed by optimally allocating runway time for departures given the time required for arrivals and crossings. In addition to the obvious objective of maximizing throughput, other objectives, such as guaranteeing fairness and minimizing environmental impact, can also be incorporated into the ROP solution subject to constraints introduced by Air Traffic Control (ATC) procedures. This paper introduces a two stage heuristic algorithm for solving the Runway Operations Planning (ROP) problem. In the first stage, sequences of departure class slots and runway crossings slots are generated and ranked based on departure runway throughput under stochastic conditions. In the second stage, the departure class slots are populated with specific flights from the pool of available aircraft, by solving an integer program with a Branch & Bound algorithm implementation. Preliminary results from this implementation of the two-stage algorithm on real-world traffic data are presented.

Complex dynamics of the integer quantum Hall effect

International Nuclear Information System (INIS)

Trugman, S.A.; Nicopoulos, V.N.; Florida Univ., Gainesville, FL

1991-01-01

We investigate both classical and quantum potential scattering in two dimensions in a magnetic field, with applications to the integer quantum Hall effect. Classical scattering is complex, due in one case to the approach of scattering states to an infinite number of bound states. We show that bound states are generic, and occur for all but extremely smooth scattering potentials (|rvec ∇| → 0). Quantum scattering follows the classical behavior rather closely, exhibiting sharp resonances rather than classical bound states. Extended scatterers provide an explanation for the breakdown of the QHE at a comparatively small Hall voltage. 16 refs., 14 figs

Competitive Supply Chain Network Design Considering Marketing Strategies: A Hybrid Metaheuristic Algorithm

Directory of Open Access Journals (Sweden)

Ali Akbar Hasani

2016-11-01

Full Text Available In this paper, a comprehensive model is proposed to design a network for multi-period, multi-echelon, and multi-product inventory controlled the supply chain. Various marketing strategies and guerrilla marketing approaches are considered in the design process under the static competition condition. The goal of the proposed model is to efficiently respond to the customers’ demands in the presence of the pre-existing competitors and the price inelasticity of demands. The proposed optimization model considers multiple objectives that incorporate both market share and total profit of the considered supply chain network, simultaneously. To tackle the proposed multi-objective mixed-integer nonlinear programming model, an efficient hybrid meta-heuristic algorithm is developed that incorporates a Taguchi-based non-dominated sorting genetic algorithm-II and a particle swarm optimization. A variable neighborhood decomposition search is applied to enhance a local search process of the proposed hybrid solution algorithm. Computational results illustrate that the proposed model and solution algorithm are notably efficient in dealing with the competitive pressure by adopting the proper marketing strategies.

Efficient sequential and parallel algorithms for planted motif search.

Science.gov (United States)

Nicolae, Marius; Rajasekaran, Sanguthevar

2014-01-31

Motif searching is an important step in the detection of rare events occurring in a set of DNA or protein sequences. One formulation of the problem is known as (l,d)-motif search or Planted Motif Search (PMS). In PMS we are given two integers l and d and n biological sequences. We want to find all sequences of length l that appear in each of the input sequences with at most d mismatches. The PMS problem is NP-complete. PMS algorithms are typically evaluated on certain instances considered challenging. Despite ample research in the area, a considerable performance gap exists because many state of the art algorithms have large runtimes even for moderately challenging instances. This paper presents a fast exact parallel PMS algorithm called PMS8. PMS8 is the first algorithm to solve the challenging (l,d) instances (25,10) and (26,11). PMS8 is also efficient on instances with larger l and d such as (50,21). We include a comparison of PMS8 with several state of the art algorithms on multiple problem instances. This paper also presents necessary and sufficient conditions for 3 l-mers to have a common d-neighbor. The program is freely available at http://engr.uconn.edu/~man09004/PMS8/. We present PMS8, an efficient exact algorithm for Planted Motif Search. PMS8 introduces novel ideas for generating common neighborhoods. We have also implemented a parallel version for this algorithm. PMS8 can solve instances not solved by any previous algorithms.

Automatic Design of Synthetic Gene Circuits through Mixed Integer Non-linear Programming

Science.gov (United States)

Huynh, Linh; Kececioglu, John; Köppe, Matthias; Tagkopoulos, Ilias

2012-01-01

Automatic design of synthetic gene circuits poses a significant challenge to synthetic biology, primarily due to the complexity of biological systems, and the lack of rigorous optimization methods that can cope with the combinatorial explosion as the number of biological parts increases. Current optimization methods for synthetic gene design rely on heuristic algorithms that are usually not deterministic, deliver sub-optimal solutions, and provide no guaranties on convergence or error bounds. Here, we introduce an optimization framework for the problem of part selection in synthetic gene circuits that is based on mixed integer non-linear programming (MINLP), which is a deterministic method that finds the globally optimal solution and guarantees convergence in finite time. Given a synthetic gene circuit, a library of characterized parts, and user-defined constraints, our method can find the optimal selection of parts that satisfy the constraints and best approximates the objective function given by the user. We evaluated the proposed method in the design of three synthetic circuits (a toggle switch, a transcriptional cascade, and a band detector), with both experimentally constructed and synthetic promoter libraries. Scalability and robustness analysis shows that the proposed framework scales well with the library size and the solution space. The work described here is a step towards a unifying, realistic framework for the automated design of biological circuits. PMID:22536398

Positive integer solutions of the diophantine equation x2 −Lnxy +(−1 ...

Indian Academy of Sciences (India)

ny2 = ±5r when the equation has positive integer solutions. Keywords. Fibonacci numbers; Lucas numbers; diophantine equations. Mathematics Subject Classification. 11B37, 11B39. 1. Introduction. The Fibonacci sequence {Fn} is defined by F0 ...

Optimal Airport Surface Traffic Planning Using Mixed-Integer Linear Programming

Directory of Open Access Journals (Sweden)

P. C. Roling

2008-01-01

Full Text Available We describe an ongoing research effort pertaining to the development of a surface traffic automation system that will help controllers to better coordinate surface traffic movements related to arrival and departure traffic. More specifically, we describe the concept for a taxi-planning support tool that aims to optimize the routing and scheduling of airport surface traffic in such a way as to deconflict the taxi plans while optimizing delay, total taxi-time, or some other airport efficiency metric. Certain input parameters related to resource demand, such as the expected landing times and the expected pushback times, are rather difficult to predict accurately. Due to uncertainty in the input data driving the taxi-planning process, the taxi-planning tool is designed such that it produces solutions that are robust to uncertainty. The taxi-planning concept presented herein, which is based on mixed-integer linear programming, is designed such that it is able to adapt to perturbations in these input conditions, as well as to account for failure in the actual execution of surface trajectories. The capabilities of the tool are illustrated in a simple hypothetical airport.

On Secure Two-Party Integer Division

DEFF Research Database (Denmark)

Dahl, Morten; Ning, Chao; Toft, Tomas

2012-01-01

{\\mathcal{O}}(\\ell)$ arithmetic operations on encrypted values (secure addition and multiplication) in $\\ensuremath{\\mathcal{O}}(1)$ rounds. This is the most efficient constant-rounds solution to date. The second protocol requires only $\\ensuremath{\\mathcal{O}} \\left( (\\log^2 \\ell)(\\kappa + \\operatorname{loglog} \\ell) \\right......We consider the problem of secure integer division: given two Paillier encryptions of ℓ-bit values n and d, determine an encryption of $\\lfloor \\frac{n}{d}\\rfloor$ without leaking any information about n or d. We propose two new protocols solving this problem. The first requires $\\ensuremath......)$ arithmetic operations in $\\ensuremath{\\mathcal{O}}(\\log^2 \\ell)$ rounds, where κ is a correctness parameter. Theoretically, this is the most efficient solution to date as all previous solutions have required Ω(ℓ) operations. Indeed, the fact that an o(ℓ) solution is possible at all is highly surprising....

Optimization of Wind-Marine Hybrid Power System Configuration Based on Genetic Algorithm

Institute of Scientific and Technical Information of China (English)

SHI Hongda; LI Linna; ZHAO Chenyu

2017-01-01

Multi-energy power systems can use energy generated from various sources to improve power generation reliability.This paper presents a cost-power generation model of a wind-tide-wave energy hybrid power system for use on a remote island,where the configuration is optimized using a genetic algorithm.A mixed integer programming model is used and a novel object function,including cost and power generation,is proposed to solve the boundary problem caused by existence of two goals.Using this model,the final optimized result is found to have a good fit with local resources.

A necessary condition for applying MUSIC algorithm in limited-view inverse scattering problem

Science.gov (United States)

Park, Taehoon; Park, Won-Kwang

2015-09-01

Throughout various results of numerical simulations, it is well-known that MUltiple SIgnal Classification (MUSIC) algorithm can be applied in the limited-view inverse scattering problems. However, the application is somehow heuristic. In this contribution, we identify a necessary condition of MUSIC for imaging of collection of small, perfectly conducting cracks. This is based on the fact that MUSIC imaging functional can be represented as an infinite series of Bessel function of integer order of the first kind. Numerical experiments from noisy synthetic data supports our investigation.

Speedup of minimum discontinuity phase unwrapping algorithm with a reference phase distribution

Science.gov (United States)

Liu, Yihang; Han, Yu; Li, Fengjiao; Zhang, Qican

2018-06-01

In three-dimensional (3D) shape measurement based on phase analysis, the phase analysis process usually produces a wrapped phase map ranging from - π to π with some 2 π discontinuities, and thus a phase unwrapping algorithm is necessary to recover the continuous and nature phase map from which 3D height distribution can be restored. Usually, the minimum discontinuity phase unwrapping algorithm can be used to solve many different kinds of phase unwrapping problems, but its main drawback is that it requires a large amount of computations and has low efficiency in searching for the improving loop within the phase's discontinuity area. To overcome this drawback, an improvement to speedup of the minimum discontinuity phase unwrapping algorithm by using the phase distribution on reference plane is proposed. In this improved algorithm, before the minimum discontinuity phase unwrapping algorithm is carried out to unwrap phase, an integer number K was calculated from the ratio of the wrapped phase to the nature phase on a reference plane. And then the jump counts of the unwrapped phase can be reduced by adding 2K π, so the efficiency of the minimum discontinuity phase unwrapping algorithm is significantly improved. Both simulated and experimental data results verify the feasibility of the proposed improved algorithm, and both of them clearly show that the algorithm works very well and has high efficiency.

Fibonacci’s Computation Methods vs Modern Algorithms

Directory of Open Access Journals (Sweden)

Ernesto Burattini

2013-12-01

Full Text Available In this paper we discuss some computational procedures given by Leonardo Pisano Fibonacci in his famous Liber Abaci book, and we propose their translation into a modern language for computers (C ++. Among the other we describe the method of “cross” multiplication, we evaluate its computational complexity in algorithmic terms and we show the output of a C ++ code that describes the development of the method applied to the product of two integers. In a similar way we show the operations performed on fractions introduced by Fibonacci. Thanks to the possibility to reproduce on a computer, the Fibonacci’s different computational procedures, it was possible to identify some calculation errors present in the different versions of the original text.

Physical Applications of a Simple Approximation of Bessel Functions of Integer Order

Science.gov (United States)

Barsan, V.; Cojocaru, S.

2007-01-01

Applications of a simple approximation of Bessel functions of integer order, in terms of trigonometric functions, are discussed for several examples from electromagnetism and optics. The method may be applied in the intermediate regime, bridging the "small values regime" and the "asymptotic" one, and covering, in this way, an area of great…

An Endosymbiotic Evolutionary Algorithm for the Hub Location-Routing Problem

Directory of Open Access Journals (Sweden)

Ji Ung Sun

2015-01-01

Full Text Available We consider a capacitated hub location-routing problem (HLRP which combines the hub location problem and multihub vehicle routing decisions. The HLRP not only determines the locations of the capacitated p-hubs within a set of potential hubs but also deals with the routes of the vehicles to meet the demands of customers. This problem is formulated as a 0-1 mixed integer programming model with the objective of the minimum total cost including routing cost, fixed hub cost, and fixed vehicle cost. As the HLRP has impractically demanding for the large sized problems, we develop a solution method based on the endosymbiotic evolutionary algorithm (EEA which solves hub location and vehicle routing problem simultaneously. The performance of the proposed algorithm is examined through a comparative study. The experimental results show that the proposed EEA can be a viable solution method for the supply chain network planning.

An integer programming model for gate assignment problem at airline terminals

Science.gov (United States)

Chun, Chong Kok; Nordin, Syarifah Zyurina

2015-05-01

In this paper, we concentrate on a gate assignment problem (GAP) at the airlines terminal. Our problem is to assign an arrival plane to a suitable gate. There are two considerations needed to take. One of its is passenger walking distance from arrival gate to departure gate while another consideration is the transport baggage distance from one gate to another. Our objective is to minimize the total distance between the gates that related to assign the arrival plane to the suitable gates. An integer linear programming (ILP) model is proposed to solve this gate assignment problem. We also conduct a computational experiment using CPLEX 12.1 solver in AIMMS 3.10 software to analyze the performance of the model. Results of the computational experiments are presented. The efficiency of flights assignment is depends on the ratio of the weight for both total passenger traveling distances and total baggage transport distances.

TRACKING SIMULATIONS NEAR HALF-INTEGER RESONANCE AT PEP-II

International Nuclear Information System (INIS)

Nosochkov, Yuri

2003-01-01

Beam-beam simulations predict that PEP-II luminosity can be increased by operating the horizontal betatron tune near and above a half-integer resonance. However, effects of the resonance and its synchrotron sidebands significantly enhance betatron and chromatic perturbations which tend to reduce dynamic aperture. In the study, chromatic variation of horizontal tune near the resonance was minimized by optimizing local sextupoles in the Interaction Region. Dynamic aperture was calculated using tracking simulations in LEGO code. Dependence of dynamic aperture on the residual orbit, dispersion and β distortion after correction was investigated

Integer channels in nonuniform non-equilibrium 2D systems

Science.gov (United States)

Shikin, V.

2018-01-01

We discuss the non-equilibrium properties of integer channels in nonuniform 2D electron (hole) systems in the presence of a strong magnetic field. The results are applied to a qualitative explanation of the Corbino disk current-voltage characteristics (IVC) in the quantum Hall effect (QHE) regime. Special consideration is paid to the so-called "QHE breakdown" effect, which is readily observed in both the Hall bar and Corbino geometries of the tested cells. The QHE breakdown is especially evident in the Corbino samples, allowing for a more in-depth study of these effects.

An efficient genetic algorithm for a hybrid flow shop scheduling problem with time lags and sequence-dependent setup time

Directory of Open Access Journals (Sweden)

Farahmand-Mehr Mohammad

2014-01-01

Full Text Available In this paper, a hybrid flow shop scheduling problem with a new approach considering time lags and sequence-dependent setup time in realistic situations is presented. Since few works have been implemented in this field, the necessity of finding better solutions is a motivation to extend heuristic or meta-heuristic algorithms. This type of production system is found in industries such as food processing, chemical, textile, metallurgical, printed circuit board, and automobile manufacturing. A mixed integer linear programming (MILP model is proposed to minimize the makespan. Since this problem is known as NP-Hard class, a meta-heuristic algorithm, named Genetic Algorithm (GA, and three heuristic algorithms (Johnson, SPTCH and Palmer are proposed. Numerical experiments of different sizes are implemented to evaluate the performance of presented mathematical programming model and the designed GA in compare to heuristic algorithms and a benchmark algorithm. Computational results indicate that the designed GA can produce near optimal solutions in a short computational time for different size problems.

A Hybrid Shared-Memory Parallel Max-Tree Algorithm for Extreme Dynamic-Range Images.

Science.gov (United States)

Moschini, Ugo; Meijster, Arnold; Wilkinson, Michael H F

2018-03-01

Max-trees, or component trees, are graph structures that represent the connected components of an image in a hierarchical way. Nowadays, many application fields rely on images with high-dynamic range or floating point values. Efficient sequential algorithms exist to build trees and compute attributes for images of any bit depth. However, we show that the current parallel algorithms perform poorly already with integers at bit depths higher than 16 bits per pixel. We propose a parallel method combining the two worlds of flooding and merging max-tree algorithms. First, a pilot max-tree of a quantized version of the image is built in parallel using a flooding method. Later, this structure is used in a parallel leaf-to-root approach to compute efficiently the final max-tree and to drive the merging of the sub-trees computed by the threads. We present an analysis of the performance both on simulated and actual 2D images and 3D volumes. Execution times are about better than the fastest sequential algorithm and speed-up goes up to on 64 threads.

A Computational Investigation of Heuristic Algorithms for 2-Edge-Connectivity Augmentation

DEFF Research Database (Denmark)

Bang-Jensen, Jørgen; Chiarandini, Marco; Morling, Peter

2010-01-01

an equivalent set covering   formulation.  The results indicate that exact solutions by means of a   basic integer programming model can be obtained in reasonably short   time even on networks with 800 vertices and around 287,000   edges. Alternatively, an advanced heuristic algorithm based on   subgradient...... programming, simple construction heuristics and   metaheuristics. As part of the design of heuristics, we consider   different neighborhood structures for local search, among which is a very   large scale neighborhood. In all cases, we exploit approaches through   the graph formulation as well as through...

Optimal sensor placement for leak location in water distribution networks using genetic algorithms.

Science.gov (United States)

Casillas, Myrna V; Puig, Vicenç; Garza-Castañón, Luis E; Rosich, Albert

2013-11-04

This paper proposes a new sensor placement approach for leak location in water distribution networks (WDNs). The sensor placement problem is formulated as an integer optimization problem. The optimization criterion consists in minimizing the number of non-isolable leaks according to the isolability criteria introduced. Because of the large size and non-linear integer nature of the resulting optimization problem, genetic algorithms (GAs) are used as the solution approach. The obtained results are compared with a semi-exhaustive search method with higher computational effort, proving that GA allows one to find near-optimal solutions with less computational load. Moreover, three ways of increasing the robustness of the GA-based sensor placement method have been proposed using a time horizon analysis, a distance-based scoring and considering different leaks sizes. A great advantage of the proposed methodology is that it does not depend on the isolation method chosen by the user, as long as it is based on leak sensitivity analysis. Experiments in two networks allow us to evaluate the performance of the proposed approach.

Optimal Sensor Placement for Leak Location in Water Distribution Networks Using Genetic Algorithms

Directory of Open Access Journals (Sweden)

Luis E. Garza-Castañón

2013-11-01

Full Text Available This paper proposes a new sensor placement approach for leak location in water distribution networks (WDNs. The sensor placement problem is formulated as an integer optimization problem. The optimization criterion consists in minimizing the number of non-isolable leaks according to the isolability criteria introduced. Because of the large size and non-linear integer nature of the resulting optimization problem, genetic algorithms (GAs are used as the solution approach. The obtained results are compared with a semi-exhaustive search method with higher computational effort, proving that GA allows one to find near-optimal solutions with less computational load. Moreover, three ways of increasing the robustness of the GA-based sensor placement method have been proposed using a time horizon analysis, a distance-based scoring and considering different leaks sizes. A great advantage of the proposed methodology is that it does not depend on the isolation method chosen by the user, as long as it is based on leak sensitivity analysis. Experiments in two networks allow us to evaluate the performance of the proposed approach.

Optimal Sensor Placement for Leak Location in Water Distribution Networks Using Genetic Algorithms

Science.gov (United States)

Casillas, Myrna V.; Puig, Vicenç; Garza-Castañón, Luis E.; Rosich, Albert

2013-01-01

This paper proposes a new sensor placement approach for leak location in water distribution networks (WDNs). The sensor placement problem is formulated as an integer optimization problem. The optimization criterion consists in minimizing the number of non-isolable leaks according to the isolability criteria introduced. Because of the large size and non-linear integer nature of the resulting optimization problem, genetic algorithms (GAs) are used as the solution approach. The obtained results are compared with a semi-exhaustive search method with higher computational effort, proving that GA allows one to find near-optimal solutions with less computational load. Moreover, three ways of increasing the robustness of the GA-based sensor placement method have been proposed using a time horizon analysis, a distance-based scoring and considering different leaks sizes. A great advantage of the proposed methodology is that it does not depend on the isolation method chosen by the user, as long as it is based on leak sensitivity analysis. Experiments in two networks allow us to evaluate the performance of the proposed approach. PMID:24193099

A fast algorithm for sparse matrix computations related to inversion

International Nuclear Information System (INIS)

Li, S.; Wu, W.; Darve, E.

2013-01-01

We have developed a fast algorithm for computing certain entries of the inverse of a sparse matrix. Such computations are critical to many applications, such as the calculation of non-equilibrium Green’s functions G r and G for nano-devices. The FIND (Fast Inverse using Nested Dissection) algorithm is optimal in the big-O sense. However, in practice, FIND suffers from two problems due to the width-2 separators used by its partitioning scheme. One problem is the presence of a large constant factor in the computational cost of FIND. The other problem is that the partitioning scheme used by FIND is incompatible with most existing partitioning methods and libraries for nested dissection, which all use width-1 separators. Our new algorithm resolves these problems by thoroughly decomposing the computation process such that width-1 separators can be used, resulting in a significant speedup over FIND for realistic devices — up to twelve-fold in simulation. The new algorithm also has the added advantage that desired off-diagonal entries can be computed for free. Consequently, our algorithm is faster than the current state-of-the-art recursive methods for meshes of any size. Furthermore, the framework used in the analysis of our algorithm is the first attempt to explicitly apply the widely-used relationship between mesh nodes and matrix computations to the problem of multiple eliminations with reuse of intermediate results. This framework makes our algorithm easier to generalize, and also easier to compare against other methods related to elimination trees. Finally, our accuracy analysis shows that the algorithms that require back-substitution are subject to significant extra round-off errors, which become extremely large even for some well-conditioned matrices or matrices with only moderately large condition numbers. When compared to these back-substitution algorithms, our algorithm is generally a few orders of magnitude more accurate, and our produced round-off errors

A fast algorithm for sparse matrix computations related to inversion

Energy Technology Data Exchange (ETDEWEB)

Li, S., E-mail: lisong@stanford.edu [Institute for Computational and Mathematical Engineering, Stanford University, 496 Lomita Mall, Durand Building, Stanford, CA 94305 (United States); Wu, W. [Department of Electrical Engineering, Stanford University, 350 Serra Mall, Packard Building, Room 268, Stanford, CA 94305 (United States); Darve, E. [Institute for Computational and Mathematical Engineering, Stanford University, 496 Lomita Mall, Durand Building, Stanford, CA 94305 (United States); Department of Mechanical Engineering, Stanford University, 496 Lomita Mall, Durand Building, Room 209, Stanford, CA 94305 (United States)

2013-06-01

We have developed a fast algorithm for computing certain entries of the inverse of a sparse matrix. Such computations are critical to many applications, such as the calculation of non-equilibrium Green’s functions G{sup r} and G{sup <} for nano-devices. The FIND (Fast Inverse using Nested Dissection) algorithm is optimal in the big-O sense. However, in practice, FIND suffers from two problems due to the width-2 separators used by its partitioning scheme. One problem is the presence of a large constant factor in the computational cost of FIND. The other problem is that the partitioning scheme used by FIND is incompatible with most existing partitioning methods and libraries for nested dissection, which all use width-1 separators. Our new algorithm resolves these problems by thoroughly decomposing the computation process such that width-1 separators can be used, resulting in a significant speedup over FIND for realistic devices — up to twelve-fold in simulation. The new algorithm also has the added advantage that desired off-diagonal entries can be computed for free. Consequently, our algorithm is faster than the current state-of-the-art recursive methods for meshes of any size. Furthermore, the framework used in the analysis of our algorithm is the first attempt to explicitly apply the widely-used relationship between mesh nodes and matrix computations to the problem of multiple eliminations with reuse of intermediate results. This framework makes our algorithm easier to generalize, and also easier to compare against other methods related to elimination trees. Finally, our accuracy analysis shows that the algorithms that require back-substitution are subject to significant extra round-off errors, which become extremely large even for some well-conditioned matrices or matrices with only moderately large condition numbers. When compared to these back-substitution algorithms, our algorithm is generally a few orders of magnitude more accurate, and our produced round

Scheduling algorithms for rapid imaging using agile Cubesat constellations

Science.gov (United States)

Nag, Sreeja; Li, Alan S.; Merrick, James H.

2018-02-01

Distributed Space Missions such as formation flight and constellations, are being recognized as important Earth Observation solutions to increase measurement samples over space and time. Cubesats are increasing in size (27U, ∼40 kg in development) with increasing capabilities to host imager payloads. Given the precise attitude control systems emerging in the commercial market, Cubesats now have the ability to slew and capture images within short notice. We propose a modular framework that combines orbital mechanics, attitude control and scheduling optimization to plan the time-varying, full-body orientation of agile Cubesats in a constellation such that they maximize the number of observed images and observation time, within the constraints of Cubesat hardware specifications. The attitude control strategy combines bang-bang and PD control, with constraints such as power consumption, response time, and stability factored into the optimality computations and a possible extension to PID control to account for disturbances. Schedule optimization is performed using dynamic programming with two levels of heuristics, verified and improved upon using mixed integer linear programming. The automated scheduler is expected to run on ground station resources and the resultant schedules uplinked to the satellites for execution, however it can be adapted for onboard scheduling, contingent on Cubesat hardware and software upgrades. The framework is generalizable over small steerable spacecraft, sensor specifications, imaging objectives and regions of interest, and is demonstrated using multiple 20 kg satellites in Low Earth Orbit for two case studies - rapid imaging of Landsat's land and coastal images and extended imaging of global, warm water coral reefs. The proposed algorithm captures up to 161% more Landsat images than nadir-pointing sensors with the same field of view, on a 2-satellite constellation over a 12-h simulation. Integer programming was able to verify that

A novel minimum cost maximum power algorithm for future smart home energy management

Directory of Open Access Journals (Sweden)

A. Singaravelan

2017-11-01

Full Text Available With the latest development of smart grid technology, the energy management system can be efficiently implemented at consumer premises. In this paper, an energy management system with wireless communication and smart meter are designed for scheduling the electric home appliances efficiently with an aim of reducing the cost and peak demand. For an efficient scheduling scheme, the appliances are classified into two types: uninterruptible and interruptible appliances. The problem formulation was constructed based on the practical constraints that make the proposed algorithm cope up with the real-time situation. The formulated problem was identified as Mixed Integer Linear Programming (MILP problem, so this problem was solved by a step-wise approach. This paper proposes a novel Minimum Cost Maximum Power (MCMP algorithm to solve the formulated problem. The proposed algorithm was simulated with input data available in the existing method. For validating the proposed MCMP algorithm, results were compared with the existing method. The compared results prove that the proposed algorithm efficiently reduces the consumer electricity consumption cost and peak demand to optimum level with 100% task completion without sacrificing the consumer comfort.

Solving recurrence relations for multi-loop Feynman integrals

International Nuclear Information System (INIS)

Smirnov, Vladimir A.; Steinhauser, Matthias

2003-01-01

We study the problem of solving integration-by-parts recurrence relations for a given class of Feynman integrals which is characterized by an arbitrary polynomial in the numerator and arbitrary integer powers of propagators, i.e., the problem of expressing any Feynman integral from this class as a linear combination of master integrals. We show how the parametric representation invented by Baikov [Phys. Lett. B 385 (1996) 404, Nucl. Instrum. Methods A 389 (1997) 347] can be used to characterize the master integrals and to construct an algorithm for evaluating the corresponding coefficient functions. To illustrate this procedure we use simple one-loop examples as well as the class of diagrams appearing in the calculation of the two-loop heavy quark potential

A necessary condition for applying MUSIC algorithm in limited-view inverse scattering problem

International Nuclear Information System (INIS)

Park, Taehoon; Park, Won-Kwang

2015-01-01

Throughout various results of numerical simulations, it is well-known that MUltiple SIgnal Classification (MUSIC) algorithm can be applied in the limited-view inverse scattering problems. However, the application is somehow heuristic. In this contribution, we identify a necessary condition of MUSIC for imaging of collection of small, perfectly conducting cracks. This is based on the fact that MUSIC imaging functional can be represented as an infinite series of Bessel function of integer order of the first kind. Numerical experiments from noisy synthetic data supports our investigation. (paper)

Enhanced index tracking modeling in portfolio optimization with mixed-integer programming z approach

Science.gov (United States)

Siew, Lam Weng; Jaaman, Saiful Hafizah Hj.; Ismail, Hamizun bin

2014-09-01

Enhanced index tracking is a popular form of portfolio management in stock market investment. Enhanced index tracking aims to construct an optimal portfolio to generate excess return over the return achieved by the stock market index without purchasing all of the stocks that make up the index. The objective of this paper is to construct an optimal portfolio using mixed-integer programming model which adopts regression approach in order to generate higher portfolio mean return than stock market index return. In this study, the data consists of 24 component stocks in Malaysia market index which is FTSE Bursa Malaysia Kuala Lumpur Composite Index from January 2010 until December 2012. The results of this study show that the optimal portfolio of mixed-integer programming model is able to generate higher mean return than FTSE Bursa Malaysia Kuala Lumpur Composite Index return with only selecting 30% out of the total stock market index components.

Estimating Most Productive Scale Size in Data Envelopment Analysis with Integer Value Data

Science.gov (United States)

Dwi Sari, Yunita; Angria S, Layla; Efendi, Syahril; Zarlis, Muhammad

2018-01-01

The most productive scale size (MPSS) is a measurement that states how resources should be organized and utilized to achieve optimal results. The most productive scale size (MPSS) can be used as a benchmark for the success of an industry or company in producing goods or services. To estimate the most productive scale size (MPSS), each decision making unit (DMU) should pay attention the level of input-output efficiency, by data envelopment analysis (DEA) method decision making unit (DMU) can identify units used as references that can help to find the cause and solution from inefficiencies can optimize productivity that main advantage in managerial applications. Therefore, data envelopment analysis (DEA) is chosen to estimating most productive scale size (MPSS) that will focus on the input of integer value data with the CCR model and the BCC model. The purpose of this research is to find the best solution for estimating most productive scale size (MPSS) with input of integer value data in data envelopment analysis (DEA) method.

Extension of the Poincaré group with half-integer spin generators: hypergravity and beyond

Energy Technology Data Exchange (ETDEWEB)

Fuentealba, Oscar [Centro de Estudios Científicos (CECs), Av. Arturo Prat 514, Valdivia (Chile); Departamento de Física, Universidad de Concepción, Casilla 160-C, Concepción (Chile); Matulich, Javier; Troncoso, Ricardo [Centro de Estudios Científicos (CECs), Av. Arturo Prat 514, Valdivia (Chile)

2015-09-01

An extension of the Poincaré group with half-integer spin generators is explicitly constructed. We start discussing the case of three spacetime dimensions, and as an application, it is shown that hypergravity can be formulated so as to incorporate this structure as its local gauge symmetry. Since the algebra admits a nontrivial Casimir operator, the theory can be described in terms of gauge fields associated to the extension of the Poincaré group with a Chern-Simons action. The algebra is also shown to admit an infinite-dimensional non-linear extension, that in the case of fermionic spin-3/2 generators, corresponds to a subset of a contraction of two copies of WB{sub 2}. Finally, we show how the Poincaré group can be extended with half-integer spin generators for d≥3 dimensions.

Design of a fractional order PID controller for hydraulic turbine regulating system using chaotic non-dominated sorting genetic algorithm II

International Nuclear Information System (INIS)

Chen, Zhihuan; Yuan, Xiaohui; Ji, Bin; Wang, Pengtao; Tian, Hao

2014-01-01

Highlights: • Multi-objective optimization based fractional order controller is designed for HTRS. • NSGAII is improved by iterative chaotic map with infinite collapses (ICMIC) operator. • ISE and ITSE are as chosen as objective functions in tuning parameters of HTRS. • FOPID controller outperforms the PID controller under various running conditions. • Trade-off between speed of reference tracking and damping of oscillation are shown. - Abstract: Fractional-order PID (FOPID) controller is a generalization of traditional PID controller using fractional calculus. Compared to the traditional PID controller, in FOPID controller, the order of derivative portion and integral portion is not integer, which provides more flexibility in achieving control objectives. Design stage of such an FOPID controller consists of determining five parameters, i.e. proportional, integral and derivative gains {Kp, Ki, Kd}, and extra integration and differentiation orders {λ,μ}, which has a large difference comparing with the conventional PID tuning rules, thus a suitable optimization algorithm is essential to the parameters tuning of FOPID controller. This paper focuses on the design of the FOPID controller using chaotic non-dominated sorting genetic algorithm II (NSGAII) for hydraulic turbine regulating system (HTRS). The parameters chosen of the FOPID controller is formulated as a multi-objective optimization problem, in which the objective functions are composed by the integral of the squared error (ISE) and integral of the time multiplied squared error (ITSE). The chaotic NSGAII algorithm, which is an incorporation of chaotic behaviors into NSGAII, is used as the optimizer to search true Pareto-front of the FOPID controller and designers can implement each of them based on objective functions priority. The designed chaotic NSGAII based FOPID controller procedure is applied to a HTRS system. A comparison study between the optimum integer order PID controller and optimum

Optimization of Energy Efficiency and Conservation in Green Building Design Using Duelist, Killer-Whale and Rain-Water Algorithms

Science.gov (United States)

Biyanto, T. R.; Matradji; Syamsi, M. N.; Fibrianto, H. Y.; Afdanny, N.; Rahman, A. H.; Gunawan, K. S.; Pratama, J. A. D.; Malwindasari, A.; Abdillah, A. I.; Bethiana, T. N.; Putra, Y. A.

2017-11-01

The development of green building has been growing in both design and quality. The development of green building was limited by the issue of expensive investment. Actually, green building can reduce the energy usage inside the building especially in utilization of cooling system. External load plays major role in reducing the usage of cooling system. External load is affected by type of wall sheathing, glass and roof. The proper selection of wall, type of glass and roof material are very important to reduce external load. Hence, the optimization of energy efficiency and conservation in green building design is required. Since this optimization consist of integer and non-linear equations, this problem falls into Mixed-Integer-Non-Linear-Programming (MINLP) that required global optimization technique such as stochastic optimization algorithms. In this paper the optimized variables i.e. type of glass and roof were chosen using Duelist, Killer-Whale and Rain-Water Algorithms to obtain the optimum energy and considering the minimal investment. The optimization results exhibited the single glass Planibel-G with the 3.2 mm thickness and glass wool insulation provided maximum ROI of 36.8486%, EUI reduction of 54 kWh/m2·year, CO2 emission reduction of 486.8971 tons/year and reduce investment of 4,078,905,465 IDR.

Using Integer Programming for Airport Service Planning in Staff Scheduling

Directory of Open Access Journals (Sweden)

W.H. Ip

2010-09-01

Full Text Available Reliability and safety in flight is extremely necessary and that depend on the adoption of proper maintenance system. Therefore, it is essential for aircraft maintenance companies to perform the manpower scheduling efficiently. One of the objectives of this paper is to provide an Integer Programming approach to determine the optimal solutions to aircraft maintenance planning and scheduling and hence the planning and scheduling processes can become more efficient and effective. Another objective is to develop a set of computational schedules for maintenance manpower to cover all scheduled flights. In this paper, a sequential methodology consisting of 3 stages is proposed. They are initial maintenance demand schedule, the maintenance pairing and the maintenance group(s assignment. Since scheduling would split up into different stages, different mathematical techniques have been adopted to cater for their own problem characteristics. Microsoft Excel would be used. Results from the first stage and second stage would be inputted into integer programming model using Microsoft Excel Solver to find the optimal solution. Also, Microsoft Excel VBA is used for devising a scheduling system in order to reduce the manual process and provide a user friendly interface. For the results, all can be obtained optimal solution and the computation time is reasonable and acceptable. Besides, the comparison of the peak time and non-peak time is discussed.

Self-affine scaling from non-integer phase-space partition in $\\pi^{+}p$ and $K^{+}p$ collisions at 250 GeV/$c$

CERN Document Server

Agababian, N M

1998-01-01

A factorial-moment analysis with real (integer and non-integer) phase space partition is applied to $\\pi^+$p and K$^+$p collisions at 250 GeV/$c$. Clear evidence is shown for self-affine rather than self-similar power-law scaling in multiparticle production. The three-dimensional self-affine second-order scaling exponent is determined to be 0.061$\\pm$0.010.

Integer Programming Formulation of the Problem of Generating Milton Babbitt's All-partition Arrays

DEFF Research Database (Denmark)

Tanaka, Tsubasa; Bemman, Brian; Meredith, David

2016-01-01

Milton Babbitt (1916–2011) was a composer of twelve-tone serial music noted for creating the all-partition array. The problem of generating an all-partition array involves finding a rectangular array of pitch-class integers that can be partitioned into regions, each of which represents a distinct...

A mixed integer program to model spatial wildfire behavior and suppression placement decisions

Science.gov (United States)

Erin J. Belval; Yu Wei; Michael. Bevers

2015-01-01

Wildfire suppression combines multiple objectives and dynamic fire behavior to form a complex problem for decision makers. This paper presents a mixed integer program designed to explore integrating spatial fire behavior and suppression placement decisions into a mathematical programming framework. Fire behavior and suppression placement decisions are modeled using...

Comparing Mixed & Integer Programming vs. Constraint Programming by solving Job-Shop Scheduling Problems

Directory of Open Access Journals (Sweden)

Renata Melo e Silva de Oliveira

2015-03-01

Full Text Available Scheduling is a key factor for operations management as well as for business success. From industrial Job-shop Scheduling problems (JSSP, many optimization challenges have emerged since de 1960s when improvements have been continuously required such as bottlenecks allocation, lead-time reductions and reducing response time to requests.  With this in perspective, this work aims to discuss 3 different optimization models for minimizing Makespan. Those 3 models were applied on 17 classical problems of examples JSSP and produced different outputs.  The first model resorts on Mixed and Integer Programming (MIP and it resulted on optimizing 60% of the studied problems. The other models were based on Constraint Programming (CP and approached the problem in two different ways: a model CP1 is a standard IBM algorithm whereof restrictions have an interval structure that fail to solve 53% of the proposed instances, b Model CP-2 approaches the problem with disjunctive constraints and optimized 88% of the instances. In this work, each model is individually analyzed and then compared considering: i Optimization success performance, ii Computational processing time, iii Greatest Resource Utilization and, iv Minimum Work-in-process Inventory. Results demonstrated that CP-2 presented best results on criteria i and ii, but MIP was superior on criteria iii and iv and those findings are discussed at the final section of this work.

Real-Time Algorithm for Relative Position Estimation Between Person and Robot Using a Monocular Camera

Energy Technology Data Exchange (ETDEWEB)

Lee, Jung Uk [Samsung Electroics, Suwon (Korea, Republic of); Sun, Ju Young; Won, Mooncheol [Chungnam Nat' l Univ., Daejeon (Korea, Republic of)

2013-12-15

In this paper, we propose a real-time algorithm for estimating the relative position of a person with respect to a robot (camera) using a monocular camera. The algorithm detects the head and shoulder regions of a person using HOG (Histogram of Oriented Gradient) feature vectors and an SVM (Support Vector Machine) classifier. The size and location of the detected area are used for calculating the relative distance and angle between the person and the camera on a robot. To increase the speed of the algorithm, we use a GPU and NVIDIA's CUDA library; the resulting algorithm speed is ∼ 15 Hz. The accuracy of the algorithm is compared with the output of a SICK laser scanner.

Real-Time Algorithm for Relative Position Estimation Between Person and Robot Using a Monocular Camera

International Nuclear Information System (INIS)

Lee, Jung Uk; Sun, Ju Young; Won, Mooncheol

2013-01-01

In this paper, we propose a real-time algorithm for estimating the relative position of a person with respect to a robot (camera) using a monocular camera. The algorithm detects the head and shoulder regions of a person using HOG (Histogram of Oriented Gradient) feature vectors and an SVM (Support Vector Machine) classifier. The size and location of the detected area are used for calculating the relative distance and angle between the person and the camera on a robot. To increase the speed of the algorithm, we use a GPU and NVIDIA's CUDA library; the resulting algorithm speed is ∼ 15 Hz. The accuracy of the algorithm is compared with the output of a SICK laser scanner

Equitably Distributing Quality of Marine Security Guards Using Integer Programming

Science.gov (United States)

2013-03-01

ARB BALMOD COM DoD DoS E HAF HQ 10 IP IQ LP MOS MCESG MSG MSGAT NLP NMC OSAB PCS PP&O Q RSO SAl SD SE SNCO T-ODP LIST OF...and Eurasia 2 Abu Dhabi, United Arab Emirates India and the Middle East 3 Bangkok, Thailand East Asia and Pacific 4 Fort Lauderdale, Florida South...integer, goal, and quadratic programming. LP models and nonlinear programming ( NLP ) models are very similar in model development for both maximizing

Statistical analysis of the limitation of half integer resonances on the available momentum acceptance of the High Energy Photon Source

Energy Technology Data Exchange (ETDEWEB)

Jiao, Yi, E-mail: jiaoyi@ihep.ac.cn; Duan, Zhe

2017-01-01

In a diffraction-limited storage ring, half integer resonances can have strong effects on the beam dynamics, associated with the large detuning terms from the strong focusing and strong sextupoles as required for an ultralow emittance. In this study, the limitation of half integer resonances on the available momentum acceptance (MA) was statistically analyzed based on one design of the High Energy Photon Source (HEPS). It was found that the probability of MA reduction due to crossing of half integer resonances is closely correlated with the level of beta beats at the nominal tunes, but independent of the error sources. The analysis indicated that for the presented HEPS lattice design, the rms amplitude of beta beats should be kept below 1.5% horizontally and 2.5% vertically to reach a small MA reduction probability of about 1%.

6th Conference on Non-integer Order Calculus and Its Applications

CERN Document Server

Łukaniszyn, Marian; Stanisławski, Rafał

2015-01-01

This volume presents selected aspects of non-integer, or fractional order systems, whose analysis, synthesis and applications have increasingly become a real challenge for various research communities, ranging from science to engineering. The spectrum of applications of the fractional order calculus has incredibly expanded, in fact it would be hard to find a science/engineering-related subject area where the fractional calculus had not been incorporated. The content of the fractional calculus is ranged from pure mathematics to engineering implementations and so is the content of this volume. The volume is subdivided into six parts, reflecting particular aspects of the fractional order calculus. The first part contains a single invited paper on a new formulation of fractional-order descriptor observers for fractional-order descriptor continous LTI systems. The second part provides new elements to the mathematical theory of fractional-order systems. In the third part of this volume, a bunch of new results in ap...

Half-integer ghost states and simple BRST quantization

International Nuclear Information System (INIS)

Marnelius, R.

1987-01-01

Quantum mechanical BRST systems are considered. As is well known an odd number of ghost operators has a representation with respect to the ghost number operator consisting of states with half-integer ghost numbers. Here it is shown that an eigenstate representation of the ghost operators requires a particular mixed Grassmann character of the states. It is also shown that such states always may be avoided provided only one starts from a lagrangian where the fundamental constraints are generated by Lagrange multipliers. In the latter case there also exists an anti-BRST charge. Some relevant properties of the different BRST approaches are displayed. The existence of inequivalent physical representations is demonstrated. (orig.)

Mixed-integer evolution strategies for parameter optimization and their applications to medical image analysis

NARCIS (Netherlands)

Li, Rui

2009-01-01

The target of this work is to extend the canonical Evolution Strategies (ES) from traditional real-valued parameter optimization domain to mixed-integer parameter optimization domain. This is necessary because there exist numerous practical optimization problems from industry in which the set of

INTEG INSPEC, Accident Frequencies and Safety Analysis for Nuclear Power Plant

International Nuclear Information System (INIS)

Arnett, L.M.

1976-01-01

1 - Description of problem or function: These programs analyze the characteristics of a general model developed to represent the safety aspects of an operating nuclear reactor. These characteristics are the frequencies of incidents that are departures from the expected behavior of the reactor. Each incident is assumed to be preceded by a sequence of events starting at some initiating event. At each member in this sequence there may be functions such as safety circuits, and personnel operations that stop the sequence at that member. When mechanical devices fail they are assumed to remain inoperative until repaired. The model accounts for scheduled inspection and maintenance of all equipment in the system. 2 - Method of solution: In INTEG, the discontinuous density function is integrated by the trapezoidal rule from time equals zero to time equals t. INSPEC is based on the simulation of reactor operation as a Markov process. A vector of probabilities is successively multiplied by a transition matrix. 3 - Restrictions on the complexity of the problem: INSPEC is limited to subsystems with no more than 7 safety circuits. The transition matrix can be made up as desired so that any intercorrelations between failures of circuits can be accommodated. In INTEG, failure rates of safety circuits are restricted to independence

Artificial immune system and sheep flock algorithms for two-stage fixed-charge transportation problem

DEFF Research Database (Denmark)

Kannan, Devika; Govindan, Kannan; Soleimani, Hamed

2014-01-01

In this paper, we cope with a two-stage distribution planning problem of supply chain regarding fixed charges. The focus of the paper is on developing efficient solution methodologies of the selected NP-hard problem. Based on computational limitations, common exact and approximation solution...... approaches are unable to solve real-world instances of such NP-hard problems in a reasonable time. These approaches involve cumbersome computational steps in real-size cases. In order to solve the mixed integer linear programming model, we develop an artificial immune system and a sheep flock algorithm...

Reducing the time requirement of k-means algorithm.

Science.gov (United States)

Osamor, Victor Chukwudi; Adebiyi, Ezekiel Femi; Oyelade, Jelilli Olarenwaju; Doumbia, Seydou

2012-01-01

Traditional k-means and most k-means variants are still computationally expensive for large datasets, such as microarray data, which have large datasets with large dimension size d. In k-means clustering, we are given a set of n data points in d-dimensional space R(d) and an integer k. The problem is to determine a set of k points in R(d), called centers, so as to minimize the mean squared distance from each data point to its nearest center. In this work, we develop a novel k-means algorithm, which is simple but more efficient than the traditional k-means and the recent enhanced k-means. Our new algorithm is based on the recently established relationship between principal component analysis and the k-means clustering. We provided the correctness proof for this algorithm. Results obtained from testing the algorithm on three biological data and six non-biological data (three of these data are real, while the other three are simulated) also indicate that our algorithm is empirically faster than other known k-means algorithms. We assessed the quality of our algorithm clusters against the clusters of a known structure using the Hubert-Arabie Adjusted Rand index (ARI(HA)). We found that when k is close to d, the quality is good (ARI(HA)>0.8) and when k is not close to d, the quality of our new k-means algorithm is excellent (ARI(HA)>0.9). In this paper, emphases are on the reduction of the time requirement of the k-means algorithm and its application to microarray data due to the desire to create a tool for clustering and malaria research. However, the new clustering algorithm can be used for other clustering needs as long as an appropriate measure of distance between the centroids and the members is used. This has been demonstrated in this work on six non-biological data.

Web page sorting algorithm based on query keyword distance relation

Science.gov (United States)

Yang, Han; Cui, Hong Gang; Tang, Hao

2017-08-01

In order to optimize the problem of page sorting, according to the search keywords in the web page in the relationship between the characteristics of the proposed query keywords clustering ideas. And it is converted into the degree of aggregation of the search keywords in the web page. Based on the PageRank algorithm, the clustering degree factor of the query keyword is added to make it possible to participate in the quantitative calculation. This paper proposes an improved algorithm for PageRank based on the distance relation between search keywords. The experimental results show the feasibility and effectiveness of the method.

Fast parallel algorithms that compute transitive closure of a fuzzy relation

Science.gov (United States)

Kreinovich, Vladik YA.

1993-01-01

The notion of a transitive closure of a fuzzy relation is very useful for clustering in pattern recognition, for fuzzy databases, etc. The original algorithm proposed by L. Zadeh (1971) requires the computation time O(n(sup 4)), where n is the number of elements in the relation. In 1974, J. C. Dunn proposed a O(n(sup 2)) algorithm. Since we must compute n(n-1)/2 different values s(a, b) (a not equal to b) that represent the fuzzy relation, and we need at least one computational step to compute each of these values, we cannot compute all of them in less than O(n(sup 2)) steps. So, Dunn's algorithm is in this sense optimal. For small n, it is ok. However, for big n (e.g., for big databases), it is still a lot, so it would be desirable to decrease the computation time (this problem was formulated by J. Bezdek). Since this decrease cannot be done on a sequential computer, the only way to do it is to use a computer with several processors working in parallel. We show that on a parallel computer, transitive closure can be computed in time O((log(sub 2)(n))2).

MIP Models and Hybrid Algorithms for Simultaneous Job Splitting and Scheduling on Unrelated Parallel Machines

Science.gov (United States)

Ozmutlu, H. Cenk

2014-01-01

We developed mixed integer programming (MIP) models and hybrid genetic-local search algorithms for the scheduling problem of unrelated parallel machines with job sequence and machine-dependent setup times and with job splitting property. The first contribution of this paper is to introduce novel algorithms which make splitting and scheduling simultaneously with variable number of subjobs. We proposed simple chromosome structure which is constituted by random key numbers in hybrid genetic-local search algorithm (GAspLA). Random key numbers are used frequently in genetic algorithms, but it creates additional difficulty when hybrid factors in local search are implemented. We developed algorithms that satisfy the adaptation of results of local search into the genetic algorithms with minimum relocation operation of genes' random key numbers. This is the second contribution of the paper. The third contribution of this paper is three developed new MIP models which are making splitting and scheduling simultaneously. The fourth contribution of this paper is implementation of the GAspLAMIP. This implementation let us verify the optimality of GAspLA for the studied combinations. The proposed methods are tested on a set of problems taken from the literature and the results validate the effectiveness of the proposed algorithms. PMID:24977204

MIP models and hybrid algorithms for simultaneous job splitting and scheduling on unrelated parallel machines.

Science.gov (United States)

Eroglu, Duygu Yilmaz; Ozmutlu, H Cenk

2014-01-01

We developed mixed integer programming (MIP) models and hybrid genetic-local search algorithms for the scheduling problem of unrelated parallel machines with job sequence and machine-dependent setup times and with job splitting property. The first contribution of this paper is to introduce novel algorithms which make splitting and scheduling simultaneously with variable number of subjobs. We proposed simple chromosome structure which is constituted by random key numbers in hybrid genetic-local search algorithm (GAspLA). Random key numbers are used frequently in genetic algorithms, but it creates additional difficulty when hybrid factors in local search are implemented. We developed algorithms that satisfy the adaptation of results of local search into the genetic algorithms with minimum relocation operation of genes' random key numbers. This is the second contribution of the paper. The third contribution of this paper is three developed new MIP models which are making splitting and scheduling simultaneously. The fourth contribution of this paper is implementation of the GAspLAMIP. This implementation let us verify the optimality of GAspLA for the studied combinations. The proposed methods are tested on a set of problems taken from the literature and the results validate the effectiveness of the proposed algorithms.

Exact diagonalization study of domain structures in integer filling factor quantum Hall ferromagnets

Czech Academy of Sciences Publication Activity Database

Rezayi, E. H.; Jungwirth, Tomáš; MacDonald, A. H.; Haldane, F. D. M.

2003-01-01

Roč. 67, č. 20 (2003), s. 201305-1 - 201305-4 ISSN 0163-1829 R&D Projects: GA ČR GA202/01/0754 Institutional research plan: CEZ:AV0Z1010914 Keywords : domain structure * integer filling factor * quantum Hall ferromagnets Subject RIV: BM - Solid Matter Physics ; Magnetism Impact factor: 2.962, year: 2003

Electrostatic and Quantum Transport Simulations of Quantum Point Contacts in the Integer Quantum Hall Regime

Science.gov (United States)

Sahasrabudhe, Harshad; Fallahi, Saeed; Nakamura, James; Povolotskyi, Michael; Novakovic, Bozidar; Rahman, Rajib; Manfra, Michael; Klimeck, Gerhard

Quantum Point Contacts (QPCs) are extensively used in semiconductor devices for charge sensing, tunneling and interference experiments. Fabry-Pérot interferometers containing 2 QPCs have applications in quantum computing, in which electrons/quasi-particles undergo interference due to back-scattering from the QPCs. Such experiments have turned out to be difficult because of the complex structure of edge states near the QPC boundary. We present realistic simulations of the edge states in QPCs based on GaAs/AlGaAs heterostructures, which can be used to predict conductance and edge state velocities. Conduction band profile is obtained by solving decoupled effective mass Schrödinger and Poisson equations self-consistently on a finite element mesh of a realistic geometry. In the integer quantum Hall regime, we obtain compressible and in-compressible regions near the edges. We then use the recursive Green`s function algorithm to solve Schrödinger equation with open boundary conditions for calculating transmission and local current density in the QPCs. Impurities are treated by inserting bumps in the potential with a Gaussian distribution. We compare observables with experiments for fitting some adjustable parameters. The authors would like to thank Purdue Research Foundation and Purdue Center for Topological Materials for their support.

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

Directory of Open Access Journals (Sweden)

Animesh Biswas

2016-04-01

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

Mixed Integer Programming and Heuristic Scheduling for Space Communication

Science.gov (United States)

Lee, Charles H.; Cheung, Kar-Ming

2013-01-01

Optimal planning and scheduling for a communication network was created where the nodes within the network are communicating at the highest possible rates while meeting the mission requirements and operational constraints. The planning and scheduling problem was formulated in the framework of Mixed Integer Programming (MIP) to introduce a special penalty function to convert the MIP problem into a continuous optimization problem, and to solve the constrained optimization problem using heuristic optimization. The communication network consists of space and ground assets with the link dynamics between any two assets varying with respect to time, distance, and telecom configurations. One asset could be communicating with another at very high data rates at one time, and at other times, communication is impossible, as the asset could be inaccessible from the network due to planetary occultation. Based on the network's geometric dynamics and link capabilities, the start time, end time, and link configuration of each view period are selected to maximize the communication efficiency within the network. Mathematical formulations for the constrained mixed integer optimization problem were derived, and efficient analytical and numerical techniques were developed to find the optimal solution. By setting up the problem using MIP, the search space for the optimization problem is reduced significantly, thereby speeding up the solution process. The ratio of the dimension of the traditional method over the proposed formulation is approximately an order N (single) to 2*N (arraying), where N is the number of receiving antennas of a node. By introducing a special penalty function, the MIP problem with non-differentiable cost function and nonlinear constraints can be converted into a continuous variable problem, whose solution is possible.

Deviation of the Variances of Classical Estimators and Negative Integer Moment Estimator from Minimum Variance Bound with Reference to Maxwell Distribution

Directory of Open Access Journals (Sweden)

G. R. Pasha

2006-07-01

Full Text Available In this paper, we present that how much the variances of the classical estimators, namely, maximum likelihood estimator and moment estimator deviate from the minimum variance bound while estimating for the Maxwell distribution. We also sketch this difference for the negative integer moment estimator. We note the poor performance of the negative integer moment estimator in the said consideration while maximum likelihood estimator attains minimum variance bound and becomes an attractive choice.

A synthesis/design optimization algorithm for Rankine cycle based energy systems

International Nuclear Information System (INIS)

Toffolo, Andrea

2014-01-01

The algorithm presented in this work has been developed to search for the optimal topology and design parameters of a set of Rankine cycles forming an energy system that absorbs/releases heat at different temperature levels and converts part of the absorbed heat into electricity. This algorithm can deal with several applications in the field of energy engineering: e.g., steam cycles or bottoming cycles in combined/cogenerative plants, steam networks, low temperature organic Rankine cycles. The main purpose of this algorithm is to overcome the limitations of the search space introduced by the traditional mixed-integer programming techniques, which assume that possible solutions are derived from a single superstructure embedding them all. The algorithm presented in this work is a hybrid evolutionary/traditional optimization algorithm organized in two levels. A complex original codification of the topology and the intensive design parameters of the system is managed by the upper level evolutionary algorithm according to the criteria set by the HEATSEP method, which are used for the first time to automatically synthesize a “basic” system configuration from a set of elementary thermodynamic cycles. The lower SQP (sequential quadratic programming) algorithm optimizes the objective function(s) with respect to cycle mass flow rates only, taking into account the heat transfer feasibility constraint within the undefined heat transfer section. A challenging example of application is also presented to show the capabilities of the algorithm. - Highlights: • Energy systems based on Rankine cycles are used in many applications. • A hybrid algorithm is proposed to optimize the synthesis/design of such systems. • The topology of the candidate solutions is not limited by a superstructure. • Topology is managed by the genetic operators of the upper level algorithm. • The effectiveness of the algorithm is proved in a complex test case

A Finer Classification of the Unit Sum Number of the Ring of Integers ...

Indian Academy of Sciences (India)

Here we introduce a finer classification for the unit sum number of a ring and in this new classification we completely determine the unit sum number of the ring of integers of a quadratic field. Further we obtain some results on cubic complex fields which one can decide whether the unit sum number is or ∞. Then we ...

Distribution Locational Marginal Pricing for Optimal Electric Vehicle Charging through Chance Constrained Mixed-Integer Programming

DEFF Research Database (Denmark)

Liu, Zhaoxi; Wu, Qiuwei; Oren, Shmuel S.

2017-01-01

This paper presents a distribution locational marginal pricing (DLMP) method through chance constrained mixed-integer programming designed to alleviate the possible congestion in the future distribution network with high penetration of electric vehicles (EVs). In order to represent the stochastic...

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

DEFF Research Database (Denmark)

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

2017-01-01

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

Imaging the Conductance of Integer and Fractional Quantum Hall Edge States

Directory of Open Access Journals (Sweden)

Nikola Pascher

2014-01-01

Full Text Available We measure the conductance of a quantum point contact while the biased tip of a scanning probe microscope induces a depleted region in the electron gas underneath. At a finite magnetic field, we find plateaus in the real-space maps of the conductance as a function of tip position at integer (ν=1, 2, 3, 4, 6, 8 and fractional (ν=1/3, 2/3, 5/3, 4/5 values of transmission. They resemble theoretically predicted compressible and incompressible stripes of quantum Hall edge states. The scanning tip allows us to shift the constriction limiting the conductance in real space over distances of many microns. The resulting stripes of integer and fractional filling factors are rugged on scales of a few hundred nanometers, i.e., on a scale much smaller than the zero-field elastic mean free path of the electrons. Our experiments demonstrate that microscopic inhomogeneities are relevant even in high-quality samples and lead to locally strongly fluctuating widths of incompressible regions even down to their complete suppression for certain tip positions. The macroscopic quantization of the Hall resistance measured experimentally in a nonlocal contact configuration survives in the presence of these inhomogeneities, and the relevant local energy scale for the ν=2 state turns out to be independent of tip position.

Fitness Estimation Based Particle Swarm Optimization Algorithm for Layout Design of Truss Structures

Directory of Open Access Journals (Sweden)

Ayang Xiao

2014-01-01

Full Text Available Due to the fact that vastly different variables and constraints are simultaneously considered, truss layout optimization is a typical difficult constrained mixed-integer nonlinear program. Moreover, the computational cost of truss analysis is often quite expensive. In this paper, a novel fitness estimation based particle swarm optimization algorithm with an adaptive penalty function approach (FEPSO-AP is proposed to handle this problem. FEPSO-AP adopts a special fitness estimate strategy to evaluate the similar particles in the current population, with the purpose to reduce the computational cost. Further more, a laconic adaptive penalty function is employed by FEPSO-AP, which can handle multiple constraints effectively by making good use of historical iteration information. Four benchmark examples with fixed topologies and up to 44 design dimensions were studied to verify the generality and efficiency of the proposed algorithm. Numerical results of the present work compared with results of other state-of-the-art hybrid algorithms shown in the literature demonstrate that the convergence rate and the solution quality of FEPSO-AP are essentially competitive.

Improved Harmony Search Algorithm for Truck Scheduling Problem in Multiple-Door Cross-Docking Systems

Directory of Open Access Journals (Sweden)

Zhanzhong Wang

2018-01-01

Full Text Available The key of realizing the cross docking is to design the joint of inbound trucks and outbound trucks, so a proper sequence of trucks will make the cross-docking system much more efficient and need less makespan. A cross-docking system is proposed with multiple receiving and shipping dock doors. The objective is to find the best door assignments and the sequences of trucks in the principle of products distribution to minimize the total makespan of cross docking. To solve the problem that is regarded as a mixed integer linear programming (MILP model, three metaheuristics, namely, harmony search (HS, improved harmony search (IHS, and genetic algorithm (GA, are proposed. Furthermore, the fixed parameters are optimized by Taguchi experiments to improve the accuracy of solutions further. Finally, several numerical examples are put forward to evaluate the performances of proposed algorithms.

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

STUDY OF SOLUTION REPRESENTATION LANGUAGE INFLUENCE ON EFFICIENCY OF INTEGER SEQUENCES PREDICTION

Directory of Open Access Journals (Sweden)

A. S. Potapov

2015-01-01

Full Text Available Methods based on genetic programming for the problem solution of integer sequences extrapolation are the subjects for study in the paper. In order to check the hypothesis about the influence of language expression of program representation on the prediction effectiveness, the genetic programming method based on several limited languages for recurrent sequences has been developed. On the single sequence sample the implemented method with the use of more complete language has shown results, significantly better than the results of one of the current methods represented in literature based on artificial neural networks. Analysis of experimental comparison results for the realized method with the usage of different languages has shown that language extension increases the difficulty of consistent patterns search in languages, available for prediction in a simpler language though it makes new sequence classes accessible for prediction. This effect can be reduced but not eliminated completely at language extension by the constructions, which make solutions more compact. Carried out researches have drawn to the conclusion that alone the choice of an adequate language for solution representation is not enough for the full problem solution of integer sequences prediction (and, all the more, universal prediction problem. However, practically applied methods can be received by the usage of genetic programming.

Metaheurística algoritmo genético para solução de problemas de planejamento florestal com restrições de integridade Genetic algorithm metaheuristic to solve forest planning problem with integer constraints

Directory of Open Access Journals (Sweden)

Flávio Lopes Rodrigues

2004-04-01

Full Text Available Os objetivos deste trabalho foram desenvolver e testar um algoritmo genético (AG para a solução de problemas de gerenciamento florestal com restrições de integridade. O AG foi testado em quatro problemas, contendo entre 93 e 423 variáveis de decisão, sujeitos às restrições de singularidade, produção mínima e produção máxima, periodicamente. Todos os problemas tiveram como objetivo a maximização do valor presente líquido. O AG foi codificado em ambiente delphi 5.0 e os testes foram realizados em um microcomputador AMD K6II 500 MHZ, com memória RAM de 64 MB e disco rígido de 15GB. O desempenho do AG foi avaliado de acordo com as medidas de eficácia e eficiência. Os valores ou categorias dos parâmetros do AG foram testados e comparados quanto aos seus efeitos na eficácia do algoritmo. A seleção da melhor configuração de parâmetros foi feita com o teste L&O, a 1% de probabilidade, e as análises foram realizadas através de estatísticas descritivas. A melhor configuração de parâmetros propiciou ao AG eficácia média de 94,28%, valor mínimo de 90,01%, valor máximo de 98,48%, com coeficiente de variação de 2,08% do ótimo matemático, obtido pelo algoritmo exato branch and bound. Para o problema de maior porte, a eficiência do AG foi cinco vezes superior à eficiência do algoritmo exato branch and bound. O AG apresentou-se como uma abordagem bastante atrativa para solução de importantes problemas de gerenciamento florestal.The objectives of this work was to develop and test a Genetic Algorithm (GA to solve problems of forest management with integer constraints. GA was tested in five problems containing 93 - 423 decision variables, periodically subject to singularity constraints, minimum and maximum production. The problems had the objective of maximizing the net present value. GA was codified into delphi 5.0 language and the tests were performed in a microcomputer AMD K6II 500 MHZ, with RAM memory of 64 MB

Identifying and Analyzing Novel Epilepsy-Related Genes Using Random Walk with Restart Algorithm

Directory of Open Access Journals (Sweden)

Wei Guo

2017-01-01

Full Text Available As a pathological condition, epilepsy is caused by abnormal neuronal discharge in brain which will temporarily disrupt the cerebral functions. Epilepsy is a chronic disease which occurs in all ages and would seriously affect patients’ personal lives. Thus, it is highly required to develop effective medicines or instruments to treat the disease. Identifying epilepsy-related genes is essential in order to understand and treat the disease because the corresponding proteins encoded by the epilepsy-related genes are candidates of the potential drug targets. In this study, a pioneering computational workflow was proposed to predict novel epilepsy-related genes using the random walk with restart (RWR algorithm. As reported in the literature RWR algorithm often produces a number of false positive genes, and in this study a permutation test and functional association tests were implemented to filter the genes identified by RWR algorithm, which greatly reduce the number of suspected genes and result in only thirty-three novel epilepsy genes. Finally, these novel genes were analyzed based upon some recently published literatures. Our findings implicate that all novel genes were closely related to epilepsy. It is believed that the proposed workflow can also be applied to identify genes related to other diseases and deepen our understanding of the mechanisms of these diseases.

Developing optimal nurses work schedule using integer programming

Science.gov (United States)

Shahidin, Ainon Mardhiyah; Said, Mohd Syazwan Md; Said, Noor Hizwan Mohamad; Sazali, Noor Izatie Amaliena

2017-08-01

Time management is the art of arranging, organizing and scheduling one's time for the purpose of generating more effective work and productivity. Scheduling is the process of deciding how to commit resources between varieties of possible tasks. Thus, it is crucial for every organization to have a good work schedule for their staffs. The job of Ward nurses at hospitals runs for 24 hours every day. Therefore, nurses will be working using shift scheduling. This study is aimed to solve the nurse scheduling problem at an emergency ward of a private hospital. A 7-day work schedule for 7 consecutive weeks satisfying all the constraints set by the hospital will be developed using Integer Programming. The work schedule for the nurses obtained gives an optimal solution where all the constraints are being satisfied successfully.

FPSoC-Based Architecture for a Fast Motion Estimation Algorithm in H.264/AVC

Directory of Open Access Journals (Sweden)

Obianuju Ndili

2009-01-01

Full Text Available There is an increasing need for high quality video on low power, portable devices. Possible target applications range from entertainment and personal communications to security and health care. While H.264/AVC answers the need for high quality video at lower bit rates, it is significantly more complex than previous coding standards and thus results in greater power consumption in practical implementations. In particular, motion estimation (ME, in H.264/AVC consumes the largest power in an H.264/AVC encoder. It is therefore critical to speed-up integer ME in H.264/AVC via fast motion estimation (FME algorithms and hardware acceleration. In this paper, we present our hardware oriented modifications to a hybrid FME algorithm, our architecture based on the modified algorithm, and our implementation and prototype on a PowerPC-based Field Programmable System on Chip (FPSoC. Our results show that the modified hybrid FME algorithm on average, outperforms previous state-of-the-art FME algorithms, while its losses when compared with FSME, in terms of PSNR performance and computation time, are insignificant. We show that although our implementation platform is FPGA-based, our implementation results compare favourably with previous architectures implemented on ASICs. Finally we also show an improvement over some existing architectures implemented on FPGAs.

An application of the discrete-time Toda lattice to the progressive algorithm by Lanczos and related problems

Science.gov (United States)

Nakamura, Yoshimasa; Sekido, Hiroto

2018-04-01

The finite or the semi-infinite discrete-time Toda lattice has many applications to various areas in applied mathematics. The purpose of this paper is to review how the Toda lattice appears in the Lanczos algorithm through the quotient-difference algorithm and its progressive form (pqd). Then a multistep progressive algorithm (MPA) for solving linear systems is presented. The extended Lanczos parameters can be given not by computing inner products of the extended Lanczos vectors but by using the pqd algorithm with highly relative accuracy in a lower cost. The asymptotic behavior of the pqd algorithm brings us some applications of MPA related to eigenvectors.

Highway Passenger Transport Based Express Parcel Service Network Design: Model and Algorithm

Directory of Open Access Journals (Sweden)

Yuan Jiang

2017-01-01

Full Text Available Highway passenger transport based express parcel service (HPTB-EPS is an emerging business that uses unutilised room of coach trunk to ship parcels between major cities. While it is reaping more and more express market, the managers are facing difficult decisions to design the service network. This paper investigates the HPTB-EPS network design problem and analyses the time-space characteristics of such network. A mixed-integer programming model is formulated integrating the service decision, frequency, and network flow distribution. To solve the model, a decomposition-based heuristic algorithm is designed by decomposing the problem as three steps: construction of service network, service path selection, and distribution of network flow. Numerical experiment using real data from our partner company demonstrates the effectiveness of our model and algorithm. We found that our solution could reduce the total cost by up to 16.3% compared to the carrier’s solution. The sensitivity analysis demonstrates the robustness and flexibility of the solutions of the model.

Communication complexity of distributed computing and a parallel algorithm for polynomial roots

International Nuclear Information System (INIS)

Tiwari, P.

1986-01-01

The first part of this thesis begins with a discussion of the minimum communication requirements in some distributed networks. The main result is a general technique for determining lower bounds on the communication complexity of problems on various distributed computer networks. This general technique is derived by simulating the general network by a linear array and then using a lower bound on the communication complexity of the problem on the linear array. Applications of this technique yield nontrivial optimal or near-optimal lower bounds on the communication complexity of distinctness, ranking, uniqueness, merging, and triangle detection on a ring, a mesh, and a complete binary tree of processors. A technique similar to the one used in proving the above results, yields interesting graph theoretic results concerning decomposition of a graph into complete bipartite subgraphs. The second part of the this is devoted to the design of a fast parallel algorithm for determining all roots of a polynomial. Given a polynomial rho(z) of degree n with m bit integer coefficients and an integer μ, the author considers the problem of determining all its roots with error less than 2/sup -μ/. It is shown that this problem is in the class NC if rho(z) has all real roots

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

OpenAIRE

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

2015-01-01

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

A Hybrid alldifferent-Tabu Search Algorithm for Solving Sudoku Puzzles

Directory of Open Access Journals (Sweden)

Ricardo Soto

2015-01-01

Full Text Available The Sudoku problem is a well-known logic-based puzzle of combinatorial number-placement. It consists in filling a n2 × n2 grid, composed of n columns, n rows, and n subgrids, each one containing distinct integers from 1 to n2. Such a puzzle belongs to the NP-complete collection of problems, to which there exist diverse exact and approximate methods able to solve it. In this paper, we propose a new hybrid algorithm that smartly combines a classic tabu search procedure with the alldifferent global constraint from the constraint programming world. The alldifferent constraint is known to be efficient for domain filtering in the presence of constraints that must be pairwise different, which are exactly the kind of constraints that Sudokus own. This ability clearly alleviates the work of the tabu search, resulting in a faster and more robust approach for solving Sudokus. We illustrate interesting experimental results where our proposed algorithm outperforms the best results previously reported by hybrids and approximate methods.

Spherical Bessel functions jsub(n) and ysub(n) of integer order and real argument

International Nuclear Information System (INIS)

Ardill, R.W.B.; Moriarty, K.J.M.

1978-01-01

The spherical Bessel function appears in a variety of physical applications, and especially in phase shift analysis. The package SPHBES contains a subroutine to calculate jsub(n)(x) and ysub(n)(x) for any integer order n and real argument x. The functions jsub(n)(x) and ysub(n)(x) are produced simultaneously and efficiently. (Auth.)

A particle-based simplified swarm optimization algorithm for reliability redundancy allocation problems

International Nuclear Information System (INIS)

Huang, Chia-Ling

2015-01-01

This paper proposes a new swarm intelligence method known as the Particle-based Simplified Swarm Optimization (PSSO) algorithm while undertaking a modification of the Updating Mechanism (UM), called N-UM and R-UM, and simultaneously applying an Orthogonal Array Test (OA) to solve reliability–redundancy allocation problems (RRAPs) successfully. One difficulty of RRAP is the need to maximize system reliability in cases where the number of redundant components and the reliability of corresponding components in each subsystem are simultaneously decided with nonlinear constraints. In this paper, four RRAP benchmarks are used to display the applicability of the proposed PSSO that advances the strengths of both PSO and SSO to enable optimizing the RRAP that belongs to mixed-integer nonlinear programming. When the computational results are compared with those of previously developed algorithms in existing literature, the findings indicate that the proposed PSSO is highly competitive and performs well. - Highlights: • This paper proposes a particle-based simplified swarm optimization algorithm (PSSO) to optimize RRAP. • Furthermore, the UM and an OA are adapted to advance in optimizing RRAP. • Four systems are introduced and the results demonstrate the PSSO performs particularly well

Scheduling of head-dependent cascaded hydro systems: Mixed-integer quadratic programming approach

International Nuclear Information System (INIS)

Catalao, J.P.S.; Pousinho, H.M.I.; Mendes, V.M.F.

2010-01-01

This paper is on the problem of short-term hydro scheduling, particularly concerning head-dependent cascaded hydro systems. We propose a novel mixed-integer quadratic programming approach, considering not only head-dependency, but also discontinuous operating regions and discharge ramping constraints. Thus, an enhanced short-term hydro scheduling is provided due to the more realistic modeling presented in this paper. Numerical results from two case studies, based on Portuguese cascaded hydro systems, illustrate the proficiency of the proposed approach.

Modeling an integrated hospital management planning problem using integer optimization approach

Science.gov (United States)

Sitepu, Suryati; Mawengkang, Herman; Irvan

2017-09-01

Hospital is a very important institution to provide health care for people. It is not surprising that nowadays the people’s demands for hospital is increasing. However, due to the rising cost of healthcare services, hospitals need to consider efficiencies in order to overcome these two problems. This paper deals with an integrated strategy of staff capacity management and bed allocation planning to tackle these problems. Mathematically, the strategy can be modeled as an integer linear programming problem. We solve the model using a direct neighborhood search approach, based on the notion of superbasic variables.

Parallel Integer Factorization Using Quadratic Forms

National Research Council Canada - National Science Library

McMath, Stephen S

2005-01-01

.... In 1975, Daniel Shanks used class group infrastructure to modify the Morrison-Brillhart algorithm and develop Square Forms Factorization, but he never published his work on this algorithm or provided...

The Texas Medication Algorithm Project (TMAP) schizophrenia algorithms.

Science.gov (United States)

Miller, A L; Chiles, J A; Chiles, J K; Crismon, M L; Rush, A J; Shon, S P

1999-10-01

In the Texas Medication Algorithm Project (TMAP), detailed guidelines for medication management of schizophrenia and related disorders, bipolar disorders, and major depressive disorders have been developed and implemented. This article describes the algorithms developed for medication treatment of schizophrenia and related disorders. The guidelines recommend a sequence of medications and discuss dosing, duration, and switch-over tactics. They also specify response criteria at each stage of the algorithm for both positive and negative symptoms. The rationale and evidence for each aspect of the algorithms are presented.

Adaptive generalized function matrix projective lag synchronization between fractional-order and integer-order complex networks with delayed coupling and different dimensions

International Nuclear Information System (INIS)

Dai, Hao; Si, Gangquan; Jia, Lixin; Zhang, Yanbin

2013-01-01

This paper investigates generalized function matrix projective lag synchronization between fractional-order and integer-order complex networks with delayed coupling, non-identical topological structures and different dimensions. Based on Lyapunov stability theory, generalized function matrix projective lag synchronization criteria are derived by using the adaptive control method. In addition, the three-dimensional fractional-order chaotic system and the four-dimensional integer-order hyperchaotic system as the nodes of the drive and the response networks, respectively, are analyzed in detail, and numerical simulation results are presented to illustrate the effectiveness of the theoretical results. (paper)

A motion-based integer ambiguity resolution method for attitude determination using the global positioning system (GPS)

International Nuclear Information System (INIS)

Wang, Bo; Deng, Zhihong; Wang, Shunting; Fu, Mengyin

2010-01-01

Loss of the satellite signal and noise disturbance will cause cycle slips to occur in the carrier phase observation of the attitude determination system using the global positioning system (GPS), especially in the dynamic situation. Therefore, in order to reject the error by cycle slips, the integer ambiguity should be re-computed. A motion model-based Kalman predictor is used for the ambiguity re-computation in dynamic applications. This method utilizes the correct observation of the last step to predict the current ambiguities. With the baseline length as a constraint to reject invalid values, we can solve the current integer ambiguity and the attitude angles, by substituting the obtained ambiguities into the constrained LAMBDA method. Experimental results demonstrate that the proposed method is more efficient in the dynamic situation, which takes less time to obtain new fixed ambiguities with a higher mean success rate

A mixed-integer linear programming approach to the reduction of genome-scale metabolic networks.

Science.gov (United States)

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.

Gaussian free fields at the integer quantum Hall plateau transition

Energy Technology Data Exchange (ETDEWEB)

Bondesan, R., E-mail: roberto.bondesan@phys.ox.ac.uk [Rudolf Peierls Centre for Theoretical Physics, 1 Keble Road, Oxford OX1 3NP (United Kingdom); Wieczorek, D.; Zirnbauer, M.R. [Institut für Theoretische Physik, Universität zu Köln, Zülpicher Straße 77, 50937 Köln (Germany)

2017-05-15

In this work we put forward an effective Gaussian free field description of critical wavefunctions at the transition between plateaus of the integer quantum Hall effect. To this end, we expound our earlier proposal that powers of critical wave intensities prepared via point contacts behave as pure scaling fields obeying an Abelian operator product expansion. Our arguments employ the framework of conformal field theory and, in particular, lead to a multifractality spectrum which is parabolic. We also derive a number of old and new identities that hold exactly at the lattice level and hinge on the correspondence between the Chalker–Coddington network model and a supersymmetric vertex model.

An algorithm for intelligent sorting of CT-related dose parameters

Science.gov (United States)

Cook, Tessa S.; Zimmerman, Stefan L.; Steingal, Scott; Boonn, William W.; Kim, Woojin

2011-03-01

Imaging centers nationwide are seeking innovative means to record and monitor CT-related radiation dose in light of multiple instances of patient over-exposure to medical radiation. As a solution, we have developed RADIANCE, an automated pipeline for extraction, archival and reporting of CT-related dose parameters. Estimation of whole-body effective dose from CT dose-length product (DLP)-an indirect estimate of radiation dose-requires anatomy-specific conversion factors that cannot be applied to total DLP, but instead necessitate individual anatomy-based DLPs. A challenge exists because the total DLP reported on a dose sheet often includes multiple separate examinations (e.g., chest CT followed by abdominopelvic CT). Furthermore, the individual reported series DLPs may not be clearly or consistently labeled. For example, Arterial could refer to the arterial phase of the triple liver CT or the arterial phase of a CT angiogram. To address this problem, we have designed an intelligent algorithm to parse dose sheets for multi-series CT examinations and correctly separate the total DLP into its anatomic components. The algorithm uses information from the departmental PACS to determine how many distinct CT examinations were concurrently performed. Then, it matches the number of distinct accession numbers to the series that were acquired, and anatomically matches individual series DLPs to their appropriate CT examinations. This algorithm allows for more accurate dose analytics, but there remain instances where automatic sorting is not feasible. To ultimately improve radiology patient care, we must standardize series names and exam names to unequivocally sort exams by anatomy and correctly estimate whole-body effective dose.

An algorithm for intelligent sorting of CT-related dose parameters.

Science.gov (United States)

Cook, Tessa S; Zimmerman, Stefan L; Steingall, Scott R; Boonn, William W; Kim, Woojin

2012-02-01

Imaging centers nationwide are seeking innovative means to record and monitor computed tomography (CT)-related radiation dose in light of multiple instances of patient overexposure to medical radiation. As a solution, we have developed RADIANCE, an automated pipeline for extraction, archival, and reporting of CT-related dose parameters. Estimation of whole-body effective dose from CT dose length product (DLP)--an indirect estimate of radiation dose--requires anatomy-specific conversion factors that cannot be applied to total DLP, but instead necessitate individual anatomy-based DLPs. A challenge exists because the total DLP reported on a dose sheet often includes multiple separate examinations (e.g., chest CT followed by abdominopelvic CT). Furthermore, the individual reported series DLPs may not be clearly or consistently labeled. For example, "arterial" could refer to the arterial phase of the triple liver CT or the arterial phase of a CT angiogram. To address this problem, we have designed an intelligent algorithm to parse dose sheets for multi-series CT examinations and correctly separate the total DLP into its anatomic components. The algorithm uses information from the departmental PACS to determine how many distinct CT examinations were concurrently performed. Then, it matches the number of distinct accession numbers to the series that were acquired and anatomically matches individual series DLPs to their appropriate CT examinations. This algorithm allows for more accurate dose analytics, but there remain instances where automatic sorting is not feasible. To ultimately improve radiology patient care, we must standardize series names and exam names to unequivocally sort exams by anatomy and correctly estimate whole-body effective dose.

Industrial waste recycling strategies optimization problem: mixed integer programming model and heuristics

Science.gov (United States)

Tang, Jiafu; Liu, Yang; Fung, Richard; Luo, Xinggang

2008-12-01

Manufacturers have a legal accountability to deal with industrial waste generated from their production processes in order to avoid pollution. Along with advances in waste recovery techniques, manufacturers may adopt various recycling strategies in dealing with industrial waste. With reuse strategies and technologies, byproducts or wastes will be returned to production processes in the iron and steel industry, and some waste can be recycled back to base material for reuse in other industries. This article focuses on a recovery strategies optimization problem for a typical class of industrial waste recycling process in order to maximize profit. There are multiple strategies for waste recycling available to generate multiple byproducts; these byproducts are then further transformed into several types of chemical products via different production patterns. A mixed integer programming model is developed to determine which recycling strategy and which production pattern should be selected with what quantity of chemical products corresponding to this strategy and pattern in order to yield maximum marginal profits. The sales profits of chemical products and the set-up costs of these strategies, patterns and operation costs of production are considered. A simulated annealing (SA) based heuristic algorithm is developed to solve the problem. Finally, an experiment is designed to verify the effectiveness and feasibility of the proposed method. By comparing a single strategy to multiple strategies in an example, it is shown that the total sales profit of chemical products can be increased by around 25% through the simultaneous use of multiple strategies. This illustrates the superiority of combinatorial multiple strategies. Furthermore, the effects of the model parameters on profit are discussed to help manufacturers organize their waste recycling network.

Scheduling of head-dependent cascaded hydro systems: Mixed-integer quadratic programming approach

Energy Technology Data Exchange (ETDEWEB)

Catalao, J.P.S.; Pousinho, H.M.I. [Department of Electromechanical Engineering, University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilha (Portugal); Mendes, V.M.F. [Department of Electrical Engineering and Automation, Instituto Superior de Engenharia de Lisboa, R. Conselheiro Emidio Navarro, 1950-062 Lisbon (Portugal)

2010-03-15

This paper is on the problem of short-term hydro scheduling, particularly concerning head-dependent cascaded hydro systems. We propose a novel mixed-integer quadratic programming approach, considering not only head-dependency, but also discontinuous operating regions and discharge ramping constraints. Thus, an enhanced short-term hydro scheduling is provided due to the more realistic modeling presented in this paper. Numerical results from two case studies, based on Portuguese cascaded hydro systems, illustrate the proficiency of the proposed approach. (author)

Quantum simulation of the integer factorization problem: Bell states in a Penning trap

Science.gov (United States)

Rosales, Jose Luis; Martin, Vicente

2018-03-01

The arithmetic problem of factoring an integer N can be translated into the physics of a quantum device, a result that supports Pólya's and Hilbert's conjecture to demonstrate Riemann's hypothesis. The energies of this system, being univocally related to the factors of N , are the eigenvalues of a bounded Hamiltonian. Here we solve the quantum conditions and show that the histogram of the discrete energies, provided by the spectrum of the system, should be interpreted in number theory as the relative probability for a prime to be a factor candidate of N . This is equivalent to a quantum sieve that is shown to require only o (ln√{N}) 3 energy measurements to solve the problem, recovering Shor's complexity result. Hence the outcome can be seen as a probability map that a pair of primes solve the given factorization problem. Furthermore, we show that a possible embodiment of this quantum simulator corresponds to two entangled particles in a Penning trap. The possibility to build the simulator experimentally is studied in detail. The results show that factoring numbers, many orders of magnitude larger than those computed with experimentally available quantum computers, is achievable using typical parameters in Penning traps.

Discrete Ziggurat: A time-memory trade-off for sampling from a Gaussian distribution over the integers

NARCIS (Netherlands)

Buchmann, J.; Cabarcas, D.; Göpfert, F.; Hülsing, A.T.; Weiden, P.; Lange, T.; Lauter, K.; Lisonek, P.

2014-01-01

Several lattice-based cryptosystems require to sample from a discrete Gaussian distribution over the integers. Existing methods to sample from such a distribution either need large amounts of memory or they are very slow. In this paper we explore a different method that allows for a flexible

A grey-forecasting interval-parameter mixed-integer programming approach for integrated electric-environmental management–A case study of Beijing

International Nuclear Information System (INIS)

Wang, Xingwei; Cai, Yanpeng; Chen, Jiajun; Dai, Chao

2013-01-01

In this study, a GFIPMIP (grey-forecasting interval-parameter mixed-integer programming) approach was developed for supporting IEEM (integrated electric-environmental management) in Beijing. It was an attempt to incorporate an energy-forecasting model within a general modeling framework at the municipal level. The developed GFIPMIP model can not only forecast electric demands, but also reflect dynamic, interactive, and uncertain characteristics of the IEEM system in Beijing. Moreover, it can address issues regarding power supply, and emission reduction of atmospheric pollutants and GHG (greenhouse gas). Optimal solutions were obtained related to power generation patterns and facility capacity expansion schemes under a series of system constraints. Two scenarios were analyzed based on multiple environmental policies. The results were useful for helping decision makers identify desired management strategies to guarantee the city's power supply and mitigate emissions of GHG and atmospheric pollutants. The results also suggested that the developed GFIPMIP model be applicable to similar engineering problems. - Highlights: • A grey-forecasting interval-parameter mixed integer programming (GFIPMIP) approach was developed. • It could reflect dynamic, interactive, and uncertain characteristics of an IEEM system. • The developed GFIPMIP approach was used for supporting IEEM system planning in Beijing. • Two scenarios were established based on different environmental policies and management targets. • Optimal schemes for power generation, energy supply, and environmental protection were identified

Optimising the selection of food items for food frequency questionnaires using Mixed Integer Linear Programming

NARCIS (Netherlands)

Lemmen-Gerdessen, van J.C.; Souverein, O.W.; Veer, van 't P.; Vries, de J.H.M.

2015-01-01

Objective To support the selection of food items for FFQs in such a way that the amount of information on all relevant nutrients is maximised while the food list is as short as possible. Design Selection of the most informative food items to be included in FFQs was modelled as a Mixed Integer Linear

An Improved Algorithm for Generating Database Transactions from Relational Algebra Specifications

Directory of Open Access Journals (Sweden)

Daniel J. Dougherty

2010-03-01

Full Text Available Alloy is a lightweight modeling formalism based on relational algebra. In prior work with Fisler, Giannakopoulos, Krishnamurthi, and Yoo, we have presented a tool, Alchemy, that compiles Alloy specifications into implementations that execute against persistent databases. The foundation of Alchemy is an algorithm for rewriting relational algebra formulas into code for database transactions. In this paper we report on recent progress in improving the robustness and efficiency of this transformation.

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)

Optimal planning of co-firing alternative fuels with coal in a power plant by grey nonlinear mixed integer programming model

Energy Technology Data Exchange (ETDEWEB)

Koa, A.S.; Chang, N.B. [University of Central Florida, Orlando, FL (United States). Dept. for Civil & Environmental Engineering

2008-07-15

Energy supply and use is of fundamental importance to society. Although the interactions between energy and environment were originally local in character, they have now widened to cover regional and global issues, such as acid rain and the greenhouse effect. It is for this reason that there is a need for covering the direct and indirect economic and environmental impacts of energy acquisition, transport, production and use. In this paper, particular attention is directed to ways of resolving conflict between economic and environmental goals by encouraging a power plant to consider co-firing biomass and refuse-derived fuel (RDF) with coal simultaneously. It aims at reducing the emission level of sulfur dioxide (SO{sub 2}) in an uncertain environment, using the power plant in Michigan City, Indiana as an example. To assess the uncertainty by a comparative way both deterministic and grey nonlinear mixed integer programming (MIP) models were developed to minimize the net operating cost with respect to possible fuel combinations. It aims at generating the optimal portfolio of alternative fuels while maintaining the same electricity generation simultaneously. To case the solution procedure stepwise relaxation algorithm was developed for solving the grey nonlinear MIP model. Breakeven alternative fuel value can be identified in the post-optimization stage for decision-making. Research findings show that the inclusion of RDF does not exhibit comparative advantage in terms of the net cost, albeit relatively lower air pollution impact. Yet it can be sustained by a charge system, subsidy program, or emission credit as the price of coal increases over time.

Optimal planning of co-firing alternative fuels with coal in a power plant by grey nonlinear mixed integer programming model.

Science.gov (United States)

Ko, Andi Setiady; Chang, Ni-Bin

2008-07-01

Energy supply and use is of fundamental importance to society. Although the interactions between energy and environment were originally local in character, they have now widened to cover regional and global issues, such as acid rain and the greenhouse effect. It is for this reason that there is a need for covering the direct and indirect economic and environmental impacts of energy acquisition, transport, production and use. In this paper, particular attention is directed to ways of resolving conflict between economic and environmental goals by encouraging a power plant to consider co-firing biomass and refuse-derived fuel (RDF) with coal simultaneously. It aims at reducing the emission level of sulfur dioxide (SO(2)) in an uncertain environment, using the power plant in Michigan City, Indiana as an example. To assess the uncertainty by a comparative way both deterministic and grey nonlinear mixed integer programming (MIP) models were developed to minimize the net operating cost with respect to possible fuel combinations. It aims at generating the optimal portfolio of alternative fuels while maintaining the same electricity generation simultaneously. To ease the solution procedure stepwise relaxation algorithm was developed for solving the grey nonlinear MIP model. Breakeven alternative fuel value can be identified in the post-optimization stage for decision-making. Research findings show that the inclusion of RDF does not exhibit comparative advantage in terms of the net cost, albeit relatively lower air pollution impact. Yet it can be sustained by a charge system, subsidy program, or emission credit as the price of coal increases over time.

DANoC: An Efficient Algorithm and Hardware Codesign of Deep Neural Networks on Chip.

Science.gov (United States)

Zhou, Xichuan; Li, Shengli; Tang, Fang; Hu, Shengdong; Lin, Zhi; Zhang, Lei

2017-07-18

Deep neural networks (NNs) are the state-of-the-art models for understanding the content of images and videos. However, implementing deep NNs in embedded systems is a challenging task, e.g., a typical deep belief network could exhaust gigabytes of memory and result in bandwidth and computational bottlenecks. To address this challenge, this paper presents an algorithm and hardware codesign for efficient deep neural computation. A hardware-oriented deep learning algorithm, named the deep adaptive network, is proposed to explore the sparsity of neural connections. By adaptively removing the majority of neural connections and robustly representing the reserved connections using binary integers, the proposed algorithm could save up to 99.9% memory utility and computational resources without undermining classification accuracy. An efficient sparse-mapping-memory-based hardware architecture is proposed to fully take advantage of the algorithmic optimization. Different from traditional Von Neumann architecture, the deep-adaptive network on chip (DANoC) brings communication and computation in close proximity to avoid power-hungry parameter transfers between on-board memory and on-chip computational units. Experiments over different image classification benchmarks show that the DANoC system achieves competitively high accuracy and efficiency comparing with the state-of-the-art approaches.

Applications of Fast Truncated Multiplication in Cryptography

Directory of Open Access Journals (Sweden)

Laszlo Hars

2006-12-01

Full Text Available Truncated multiplications compute truncated products, contiguous subsequences of the digits of integer products. For an n-digit multiplication algorithm of time complexity O(nα, with 1<α≤2, there is a truncated multiplication algorithm, which is constant times faster when computing a short enough truncated product. Applying these fast truncated multiplications, several cryptographic long integer arithmetic algorithms are improved, including integer reciprocals, divisions, Barrett and Montgomery multiplications, 2n-digit modular multiplication on hardware for n-digit half products. For example, Montgomery multiplication is performed in 2.6 Karatsuba multiplication time.

An ILP based memetic algorithm for finding minimum positive influence dominating sets in social networks

Science.gov (United States)

Lin, Geng; Guan, Jian; Feng, Huibin

2018-06-01

The positive influence dominating set problem is a variant of the minimum dominating set problem, and has lots of applications in social networks. It is NP-hard, and receives more and more attention. Various methods have been proposed to solve the positive influence dominating set problem. However, most of the existing work focused on greedy algorithms, and the solution quality needs to be improved. In this paper, we formulate the minimum positive influence dominating set problem as an integer linear programming (ILP), and propose an ILP based memetic algorithm (ILPMA) for solving the problem. The ILPMA integrates a greedy randomized adaptive construction procedure, a crossover operator, a repair operator, and a tabu search procedure. The performance of ILPMA is validated on nine real-world social networks with nodes up to 36,692. The results show that ILPMA significantly improves the solution quality, and is robust.

High-Speed Rail Train Timetabling Problem: A Time-Space Network Based Method with an Improved Branch-and-Price Algorithm

Directory of Open Access Journals (Sweden)

Bisheng He

2014-01-01

Full Text Available A time-space network based optimization method is designed for high-speed rail train timetabling problem to improve the service level of the high-speed rail. The general time-space path cost is presented which considers both the train travel time and the high-speed rail operation requirements: (1 service frequency requirement; (2 stopping plan adjustment; and (3 priority of train types. Train timetabling problem based on time-space path aims to minimize the total general time-space path cost of all trains. An improved branch-and-price algorithm is applied to solve the large scale integer programming problem. When dealing with the algorithm, a rapid branching and node selection for branch-and-price tree and a heuristic train time-space path generation for column generation are adopted to speed up the algorithm computation time. The computational results of a set of experiments on China’s high-speed rail system are presented with the discussions about the model validation, the effectiveness of the general time-space path cost, and the improved branch-and-price algorithm.

Penempatan Optimal Phasor Measurement Unit (PMU dengan Integer Programming

Directory of Open Access Journals (Sweden)

Yunan Helmy Amrulloh

2013-09-01

Full Text Available Phasor Measurement Unit (PMU merupakan peralatan yang mampu memberikan pengukuran fasor tegangan dan arus secara real-time. PMU dapat digunakan untuk monitoring, proteksi dan kontrol pada sistem tenaga listrik. Tugas akhir ini membahas penempatan PMU secara optimal berdasarkan topologi jaringan sehingga sistem tenaga listrik  dapat diobservasi. Penempatan optimal PMU dirumuskan sebagai masalah Binary Integer Programming (BIP yang akan memberikan variabel dengan pilihan nilai (0,1 yang menunjukkan tempat yang harus dipasang PMU. Dalam tugas akhir ini, BIP diterapkan untuk menyelesaikan masalah penempatan PMU secara optimal pada sistem tenaga listrik  Jawa-Bali 500 KV yang selanjutnya diterapkan dengan penambahan konsep incomplete observability. Hasil simulasi menunjukkan bahwa penerapan BIP pada sistem dengan incomplete observability memberikan jumlah PMU yang lebih sedikit dibandingkan dengan sistem tanpa konsep incomplete observability.

Theoretical and algorithmic advances in multi-parametric programming and control

KAUST Repository

Pistikopoulos, Efstratios N.; Dominguez, Luis; Panos, Christos; Kouramas, Konstantinos; Chinchuluun, Altannar

2012-01-01

This paper presents an overview of recent theoretical and algorithmic advances, and applications in the areas of multi-parametric programming and explicit/multi-parametric model predictive control (mp-MPC). In multi-parametric programming, advances include areas such as nonlinear multi-parametric programming (mp-NLP), bi-level programming, dynamic programming and global optimization for multi-parametric mixed-integer linear programming problems (mp-MILPs). In multi-parametric/explicit MPC (mp-MPC), advances include areas such as robust multi-parametric control, multi-parametric nonlinear MPC (mp-NMPC) and model reduction in mp-MPC. A comprehensive framework for multi-parametric programming and control is also presented. Recent applications include a hydrogen storage device, a fuel cell power generation system, an unmanned autonomous vehicle (UAV) and a hybrid pressure swing adsorption (PSA) system. © 2012 Springer-Verlag.

District Heating Network Design and Configuration Optimization with Genetic Algorithm

DEFF Research Database (Denmark)

Li, Hongwei; Svendsen, Svend

2011-01-01

In this paper, the configuration of a district heating (DH) network which connects from the heating plant to the end users was optimized with emphasizing the network thermal performance. Each end user in the network represents a building block. The locations of the building blocks are fixed while...... the heating plant location is allowed to vary. The connection between the heat generation plant and the end users can be represented with mixed integer and the pipe friction and heat loss formulations are non-linear. In order to find the optimal DH distribution pipeline configuration, the genetic algorithm...... by multi factors as the consumer heating load, the distance between the heating plant to the consumer, the design criteria regarding pressure and temperature limitation, as well as the corresponding network heat loss....

Theoretical and algorithmic advances in multi-parametric programming and control

KAUST Repository

Pistikopoulos, Efstratios N.

2012-04-21

This paper presents an overview of recent theoretical and algorithmic advances, and applications in the areas of multi-parametric programming and explicit/multi-parametric model predictive control (mp-MPC). In multi-parametric programming, advances include areas such as nonlinear multi-parametric programming (mp-NLP), bi-level programming, dynamic programming and global optimization for multi-parametric mixed-integer linear programming problems (mp-MILPs). In multi-parametric/explicit MPC (mp-MPC), advances include areas such as robust multi-parametric control, multi-parametric nonlinear MPC (mp-NMPC) and model reduction in mp-MPC. A comprehensive framework for multi-parametric programming and control is also presented. Recent applications include a hydrogen storage device, a fuel cell power generation system, an unmanned autonomous vehicle (UAV) and a hybrid pressure swing adsorption (PSA) system. © 2012 Springer-Verlag.

2D massless QED Hall half-integer conductivity and graphene

International Nuclear Information System (INIS)

Martínez, A Pérez; Querts, E Rodriguez; Rojas, H Pérez; Gaitan, R; Rodriguez-Romo, S

2011-01-01

Starting from the photon self-energy tensor in a magnetized medium, the 3D complete antisymmetric form of the conductivity tensor is found in the static limit of a fermion system C-non-invariant under fermion–antifermion exchange. The massless relativistic 2D fermion limit in QED is derived by using the compactification along the dimension parallel to the magnetic field. In the static limit and at zero temperature, the main features of the quantum Hall effect (QHE) are obtained: the half-integer QHE and the minimum value proportional to e 2 /h for the Hall conductivity. For typical values of graphene the plateaus of the Hall conductivity are also reproduced. (paper)

Integrative improvement method and mixed-integer programming in system planning

International Nuclear Information System (INIS)

Sadegheih, A.

2002-01-01

In this paper, system planning network is formulated for mixed-integer programming and a Ga. The cost function of this problem consists of the capital investment cost in discrete form, the cost of transmission losses and the power generation costs. The Dc load flow equations for the network are embedded in the constraints of the mathematical model to avoid sub-optimal solutions that can arise if the enforcement of such constraints is done in an indirect way. The solution of the model gives the best line additions. and also provides information regarding the optimal generation at each generation point. This method of solutions is demonstrated on the expansion of a 5 bus -bar system to 6 bus-bars

The integer quantum hall effect revisited

Energy Technology Data Exchange (ETDEWEB)

Michalakis, Spyridon [Los Alamos National Laboratory; Hastings, Matthew [Q STATION, CALIFORNIA

2009-01-01

For T - L x L a finite subset of Z{sup 2}, let H{sub o} denote a Hamiltonian on T with periodic boundary conditions and finite range, finite strength intetactions and a unique ground state with a nonvanishing spectral gap. For S {element_of} T, let q{sub s} denote the charge at site s and assume that the total charge Q = {Sigma}{sub s {element_of} T} q{sub s} is conserved. Using the local charge operators q{sub s}, we introduce a boundary magnetic flux in the horizontal and vertical direction and allow the ground state to evolve quasiadiabatically around a square of size one magnetic flux, in flux space. At the end of the evolution we obtain a trivial Berry phase, which we compare, via a method reminiscent of Stokes Theorem. to the Berry phase obtained from an evolution around an exponentially small loop near the origin. As a result, we show, without any averaging assumption, that the Hall conductance is quantized in integer multiples of e{sup 2}/h up to exponentially small corrections of order e{sup -L/{zeta}}, where {zeta}, is a correlation length that depends only on the gap and the range and strength of the interactions.

A Statistically-Hiding Integer Commitment Scheme Based on Groups with Hidden Order

DEFF Research Database (Denmark)

Damgård, Ivan Bjerre; Fujisaki, Eiichiro

2002-01-01

We present a statistically-hiding commitment scheme allowing commitment to arbitrary size integers, based on any (Abelian) group with certain properties, most importantly, that it is hard for the committer to compute its order. We also give efficient zero-knowledge protocols for proving knowledge...... input is chosen by the (possibly cheating) prover. -  - Our results apply to any group with suitable properties. In particular, they apply to a much larger class of RSA moduli than the safe prime products proposed in [14] - Potential examples include RSA moduli, class groups and, with a slight...

Integer, fractional, and anomalous quantum Hall effects explained with Eyring's rate process theory and free volume concept.

Science.gov (United States)

Hao, Tian

2017-02-22

The Hall effects, especially the integer, fractional and anomalous quantum Hall effects, have been addressed using Eyring's rate process theory and free volume concept. The basic assumptions are that the conduction process is a common rate controlled "reaction" process that can be described with Eyring's absolute rate process theory; the mobility of electrons should be dependent on the free volume available for conduction electrons. The obtained Hall conductivity is clearly quantized as with prefactors related to both the magnetic flux quantum number and the magnetic quantum number via the azimuthal quantum number, with and without an externally applied magnetic field. This article focuses on two dimensional (2D) systems, but the approaches developed in this article can be extended to 3D systems.

Elementary theory of numbers

CERN Document Server

LeVeque, William J

1990-01-01

Superb introduction to Euclidean algorithm and its consequences, congruences, continued fractions, powers of an integer modulo m, Gaussian integers, Diophantine equations, more. Problems, with answers. Bibliography.

Control Algorithms Along Relative Equilibria of Underactuated Lagrangian Systems on Lie Groups

DEFF Research Database (Denmark)

Nordkvist, Nikolaj; Bullo, F.

2008-01-01

We present novel algorithms to control underactuated mechanical systems. For a class of invariant systems on Lie groups, we design iterative small-amplitude control forces to accelerate along, decelerate along, and stabilize relative equilibria. The technical approach is based upon a perturbation...

Control algorithms along relative equilibria of underactuated Lagrangian systems on Lie groups

DEFF Research Database (Denmark)

Nordkvist, Nikolaj; Bullo, Francesco

2007-01-01

We present novel algorithms to control underactuated mechanical systems. For a class of invariant systems on Lie groups, we design iterative small-amplitude control forces to accelerate along, decelerate along, and stabilize relative equilibria. The technical approach is based upon a perturbation...

Clinical Applications of a CT Window Blending Algorithm: RADIO (Relative Attenuation-Dependent Image Overlay).

Science.gov (United States)

Mandell, Jacob C; Khurana, Bharti; Folio, Les R; Hyun, Hyewon; Smith, Stacy E; Dunne, Ruth M; Andriole, Katherine P

2017-06-01

A methodology is described using Adobe Photoshop and Adobe Extendscript to process DICOM images with a Relative Attenuation-Dependent Image Overlay (RADIO) algorithm to visualize the full dynamic range of CT in one view, without requiring a change in window and level settings. The potential clinical uses for such an algorithm are described in a pictorial overview, including applications in emergency radiology, oncologic imaging, and nuclear medicine and molecular imaging.

Two-Part Models for Fractional Responses Defined as Ratios of Integers

Directory of Open Access Journals (Sweden)

Harald Oberhofer

2014-09-01

Full Text Available This paper discusses two alternative two-part models for fractional response variables that are defined as ratios of integers. The first two-part model assumes a Binomial distribution and known group size. It nests the one-part fractional response model proposed by Papke and Wooldridge (1996 and, thus, allows one to apply Wald, LM and/or LR tests in order to discriminate between the two models. The second model extends the first one by allowing for overdispersion in the data. We demonstrate the usefulness of the proposed two-part models for data on the 401(k pension plan participation rates used in Papke and Wooldridge (1996.

Optimal Allocation of Static Var Compensator via Mixed Integer Conic Programming

Energy Technology Data Exchange (ETDEWEB)

Zhang, Xiaohu [ORNL; Shi, Di [Global Energy Interconnection Research Institute North America (GEIRI North America), California; Wang, Zhiwei [Global Energy Interconnection Research Institute North America (GEIRI North America), California; Huang, Junhui [Global Energy Interconnection Research Institute North America (GEIRI North America), California; Wang, Xu [Global Energy Interconnection Research Institute North America (GEIRI North America), California; Liu, Guodong [ORNL; Tomsovic, Kevin [University of Tennessee, Knoxville (UTK)

2017-01-01

Shunt FACTS devices, such as, a Static Var Compensator (SVC), are capable of providing local reactive power compensation. They are widely used in the network to reduce the real power loss and improve the voltage profile. This paper proposes a planning model based on mixed integer conic programming (MICP) to optimally allocate SVCs in the transmission network considering load uncertainty. The load uncertainties are represented by a number of scenarios. Reformulation and linearization techniques are utilized to transform the original non-convex model into a convex second order cone programming (SOCP) model. Numerical case studies based on the IEEE 30-bus system demonstrate the effectiveness of the proposed planning model.

Spoofing cyber attack detection in probe-based traffic monitoring systems using mixed integer linear programming

KAUST Repository

Canepa, Edward S.

2013-01-01

Traffic sensing systems rely more and more on user generated (insecure) data, which can pose a security risk whenever the data is used for traffic flow control. In this article, we propose a new formulation for detecting malicious data injection in traffic flow monitoring systems by using the underlying traffic flow model. The state of traffic is modeled by the Lighthill-Whitham- Richards traffic flow model, which is a first order scalar conservation law with concave flux function. Given a set of traffic flow data, we show that the constraints resulting from this partial differential equation are mixed integer linear inequalities for some decision variable. We use this fact to pose the problem of detecting spoofing cyber-attacks in probe-based traffic flow information systems as mixed integer linear feasibility problem. The resulting framework can be used to detect spoofing attacks in real time, or to evaluate the worst-case effects of an attack offline. A numerical implementation is performed on a cyber-attack scenario involving experimental data from the Mobile Century experiment and the Mobile Millennium system currently operational in Northern California. © 2013 IEEE.

Spoofing cyber attack detection in probe-based traffic monitoring systems using mixed integer linear programming

KAUST Repository

Canepa, Edward S.

2013-09-01

Traffic sensing systems rely more and more on user generated (insecure) data, which can pose a security risk whenever the data is used for traffic flow control. In this article, we propose a new formulation for detecting malicious data injection in traffic flow monitoring systems by using the underlying traffic flow model. The state of traffic is modeled by the Lighthill- Whitham-Richards traffic flow model, which is a first order scalar conservation law with concave flux function. Given a set of traffic flow data generated by multiple sensors of different types, we show that the constraints resulting from this partial differential equation are mixed integer linear inequalities for a specific decision variable. We use this fact to pose the problem of detecting spoofing cyber attacks in probe-based traffic flow information systems as mixed integer linear feasibility problem. The resulting framework can be used to detect spoofing attacks in real time, or to evaluate the worst-case effects of an attack offliine. A numerical implementation is performed on a cyber attack scenario involving experimental data from the Mobile Century experiment and the Mobile Millennium system currently operational in Northern California. © American Institute of Mathematical Sciences.

Relating 2-Rainbow Domination To Roman Domination

Directory of Open Access Journals (Sweden)

Alvarado José D.

2017-11-01

Full Text Available For a graph G, let R(G and yr2(G denote the Roman domination number of G and the 2-rainbow domination number of G, respectively. It is known that yr2(G ≤ R(G ≤ 3/2yr2(G. Fujita and Furuya [Difference between 2-rainbow domination and Roman domination in graphs, Discrete Appl. Math. 161 (2013 806-812] present some kind of characterization of the graphs G for which R(G − yr2(G = k for some integer k. Unfortunately, their result does not lead to an algorithm that allows to recognize these graphs efficiently. We show that for every fixed non-negative integer k, the recognition of the connected K4-free graphs G with yR(G − yr2(G = k is NP-hard, which implies that there is most likely no good characterization of these graphs. We characterize the graphs G such that yr2(H = yR(H for every induced subgraph H of G, and collect several properties of the graphs G with R(G = 3/2yr2(G.

Algorithmic analysis of relational learning processes in instructional technology: Some implications for basic, translational, and applied research.

Science.gov (United States)

McIlvane, William J; Kledaras, Joanne B; Gerard, Christophe J; Wilde, Lorin; Smelson, David

2018-07-01

A few noteworthy exceptions notwithstanding, quantitative analyses of relational learning are most often simple descriptive measures of study outcomes. For example, studies of stimulus equivalence have made much progress using measures such as percentage consistent with equivalence relations, discrimination ratio, and response latency. Although procedures may have ad hoc variations, they remain fairly similar across studies. Comparison studies of training variables that lead to different outcomes are few. Yet to be developed are tools designed specifically for dynamic and/or parametric analyses of relational learning processes. This paper will focus on recent studies to develop (1) quality computer-based programmed instruction for supporting relational learning in children with autism spectrum disorders and intellectual disabilities and (2) formal algorithms that permit ongoing, dynamic assessment of learner performance and procedure changes to optimize instructional efficacy and efficiency. Because these algorithms have a strong basis in evidence and in theories of stimulus control, they may have utility also for basic and translational research. We present an overview of the research program, details of algorithm features, and summary results that illustrate their possible benefits. It also presents arguments that such algorithm development may encourage parametric research, help in integrating new research findings, and support in-depth quantitative analyses of stimulus control processes in relational learning. Such algorithms may also serve to model control of basic behavioral processes that is important to the design of effective programmed instruction for human learners with and without functional disabilities. Copyright © 2018 Elsevier B.V. All rights reserved.

WORKFORCE SIZING AND SCHEDULING FOR A SERVICE CONTRACTOR USING INTEGER PROGRAMMING

Directory of Open Access Journals (Sweden)

D.G. Conradie

2012-01-01

Full Text Available

ENGLISH ABSTRACT: Operations Research is perceived to be on the verge of demise as a decision support tool in industry. However, this is not true, since the relevancy and interdisciplinary nature of Operations Research makes it an indispensable part of operations management. What should rather be asked is how Operations Research is introduced to undergraduate industrial engineering students. This paper reports on one of the optimisation initiatives undertaken for a service contractor using integer programming as part of a semester project. Although the model addresses specific business issues related to the contractor, it can easily be generalised for other applications.

AFRIKAANSE OPSOMMING: Operasionele Navorsing word geag as ’n kwynende besluitnemingsinstrument in die nywerheid. Dit is egter onwaar, aangesien die toepaslikheid en interdissiplinêre karakter van Operasionele Navorsing dit ‘n onmisbare rol laat speel in operasionele bestuur. Die vraag wat eerder gevra moet word is hoe Operasionele Navorsing aan voorgraadse bedryfsingenieurswesestudente aangebied word. Hierdie artikel doen verslag oor een van die optimerings-inisiatiewe wat as deel van ‘n semesterprojek vir ‘n diensverskaffer uitgevoer is, en maak van heeltal-programmering gebruik. Alhoewel die model kontrakteur-spesifieke besigheidsreëls aanspreek, kan dit maklik veralgemeen word vir wyer toepassing.

Combinatorial Integer Labeling Thorems on Finite Sets with an Application to Discrete Systems of Nonlinear Equations

NARCIS (Netherlands)

van der Laan, G.; Talman, A.J.J.; Yang, Z.F.

2007-01-01

Tucker's well-known combinatorial lemma states that for any given symmetric triangulation of the n-dimensional unit cube and for any integer labeling that assigns to each vertex of the triangulation a label from the set f§1;§2; ¢ ¢ ¢ ;§ng with the property that antipodal vertices on the boundary of

A simple approximation of moments of the quasi-equilibrium distribution of an extended stochastic theta-logistic model with non-integer powers.

Science.gov (United States)

Bhowmick, Amiya Ranjan; Bandyopadhyay, Subhadip; Rana, Sourav; Bhattacharya, Sabyasachi

2016-01-01

The stochastic versions of the logistic and extended logistic growth models are applied successfully to explain many real-life population dynamics and share a central body of literature in stochastic modeling of ecological systems. To understand the randomness in the population dynamics of the underlying processes completely, it is important to have a clear idea about the quasi-equilibrium distribution and its moments. Bartlett et al. (1960) took a pioneering attempt for estimating the moments of the quasi-equilibrium distribution of the stochastic logistic model. Matis and Kiffe (1996) obtain a set of more accurate and elegant approximations for the mean, variance and skewness of the quasi-equilibrium distribution of the same model using cumulant truncation method. The method is extended for stochastic power law logistic family by the same and several other authors (Nasell, 2003; Singh and Hespanha, 2007). Cumulant truncation and some alternative methods e.g. saddle point approximation, derivative matching approach can be applied if the powers involved in the extended logistic set up are integers, although plenty of evidence is available for non-integer powers in many practical situations (Sibly et al., 2005). In this paper, we develop a set of new approximations for mean, variance and skewness of the quasi-equilibrium distribution under more general family of growth curves, which is applicable for both integer and non-integer powers. The deterministic counterpart of this family of models captures both monotonic and non-monotonic behavior of the per capita growth rate, of which theta-logistic is a special case. The approximations accurately estimate the first three order moments of the quasi-equilibrium distribution. The proposed method is illustrated with simulated data and real data from global population dynamics database. Copyright © 2015 Elsevier Inc. All rights reserved.

Order Batching in Warehouses by Minimizing Total Tardiness: A Hybrid Approach of Weighted Association Rule Mining and Genetic Algorithms

Directory of Open Access Journals (Sweden)

Amir Hossein Azadnia

2013-01-01

Full Text Available One of the cost-intensive issues in managing warehouses is the order picking problem which deals with the retrieval of items from their storage locations in order to meet customer requests. Many solution approaches have been proposed in order to minimize traveling distance in the process of order picking. However, in practice, customer orders have to be completed by certain due dates in order to avoid tardiness which is neglected in most of the related scientific papers. Consequently, we proposed a novel solution approach in order to minimize tardiness which consists of four phases. First of all, weighted association rule mining has been used to calculate associations between orders with respect to their due date. Next, a batching model based on binary integer programming has been formulated to maximize the associations between orders within each batch. Subsequently, the order picking phase will come up which used a Genetic Algorithm integrated with the Traveling Salesman Problem in order to identify the most suitable travel path. Finally, the Genetic Algorithm has been applied for sequencing the constructed batches in order to minimize tardiness. Illustrative examples and comparisons are presented to demonstrate the proficiency and solution quality of the proposed approach.

Entanglement Properties of a Higher-Integer-Spin AKLT Model with Quantum Group Symmetry

Directory of Open Access Journals (Sweden)

Chikashi Arita

2012-10-01

Full Text Available We study the entanglement properties of a higher-integer-spin Affleck-Kennedy-Lieb-Tasaki model with quantum group symmetry in the periodic boundary condition. We exactly calculate the finite size correction terms of the entanglement entropies from the double scaling limit. We also evaluate the geometric entanglement, which serves as another measure for entanglement. We find the geometric entanglement reaches its maximum at the isotropic point, and decreases with the increase of the anisotropy. This behavior is similar to that of the entanglement entropies.

Extension of P-adic Exact Scientific Computational Library (ESCL) to Compute the Exponential of Rational Matrix

National Research Council Canada - National Science Library

Lu, Chao

2008-01-01

...) using p-adic arithmetic. New algorithms have been designed and implemented for matrix operations with rational numbers by representing numerator and denominator with arbitrary length integers, all integers and fractional...

Precise fixpoint computation through strategy iteration

DEFF Research Database (Denmark)

Gawlitza, Thomas; Seidl, Helmut

2007-01-01

We present a practical algorithm for computing least solutions of systems of equations over the integers with addition, multiplication with positive constants, maximum and minimum. The algorithm is based on strategy iteration. Its run-time (w.r.t. the uniform cost measure) is independent of the s......We present a practical algorithm for computing least solutions of systems of equations over the integers with addition, multiplication with positive constants, maximum and minimum. The algorithm is based on strategy iteration. Its run-time (w.r.t. the uniform cost measure) is independent...

System network planning expansion using mathematical programming, genetic algorithms and tabu search

International Nuclear Information System (INIS)

Sadegheih, A.; Drake, P.R.

2008-01-01

In this paper, system network planning expansion is formulated for mixed integer programming, a genetic algorithm (GA) and tabu search (TS). Compared with other optimization methods, GAs are suitable for traversing large search spaces, since they can do this relatively rapidly and because the use of mutation diverts the method away from local minima, which will tend to become more common as the search space increases in size. GA's give an excellent trade off between solution quality and computing time and flexibility for taking into account specific constraints in real situations. TS has emerged as a new, highly efficient, search paradigm for finding quality solutions to combinatorial problems. It is characterized by gathering knowledge during the search and subsequently profiting from this knowledge. The attractiveness of the technique comes from its ability to escape local optimality. The cost function of this problem consists of the capital investment cost in discrete form, the cost of transmission losses and the power generation costs. The DC load flow equations for the network are embedded in the constraints of the mathematical model to avoid sub-optimal solutions that can arise if the enforcement of such constraints is done in an indirect way. The solution of the model gives the best line additions and also provides information regarding the optimal generation at each generation point. This method of solution is demonstrated on the expansion of a 10 bus bar system to 18 bus bars. Finally, a steady-state genetic algorithm is employed rather than generational replacement, also uniform crossover is used

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

Science.gov (United States)

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

2018-02-01

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

An Efficient Two-Objective Hybrid Local Search Algorithm for Solving the Fuel Consumption Vehicle Routing Problem

Directory of Open Access Journals (Sweden)

Weizhen Rao

2016-01-01

Full Text Available The classical model of vehicle routing problem (VRP generally minimizes either the total vehicle travelling distance or the total number of dispatched vehicles. Due to the increased importance of environmental sustainability, one variant of VRPs that minimizes the total vehicle fuel consumption has gained much attention. The resulting fuel consumption VRP (FCVRP becomes increasingly important yet difficult. We present a mixed integer programming model for the FCVRP, and fuel consumption is measured through the degree of road gradient. Complexity analysis of FCVRP is presented through analogy with the capacitated VRP. To tackle the FCVRP’s computational intractability, we propose an efficient two-objective hybrid local search algorithm (TOHLS. TOHLS is based on a hybrid local search algorithm (HLS that is also used to solve FCVRP. Based on the Golden CVRP benchmarks, 60 FCVRP instances are generated and tested. Finally, the computational results show that the proposed TOHLS significantly outperforms the HLS.

An Algoritm for the Alocation Optimization of Trading Executions

Directory of Open Access Journals (Sweden)

Claudiu Vinte

2006-02-01

Full Text Available In this paper, I wish to propose the Integer Allocation employing Tabu Search in conjunction with Simulated Annealing Heuristics for optimizing the distribution of trading executions in investors’ accounts. There is no polynomial algorithm discovered for Integer Linear Programming (a problem which is NP-complete. Generally, the practical experience shows that large-scale integer linear programs seem as yet practically unsolvable or extremely time-consuming. The algorithm described herein proposes an alternative approach to the problem. The algorithm consists of three steps: allocate the total executed quantity proportionally on the accounts, based on the allocation instructions (pro-rata basis; construct an initial solution, distributing the executed prices; improve the solution iteratively, employing Tabu Search in conjunction with Simulated Annealing heuristics.

Efficient sequential and parallel algorithms for finding edit distance based motifs.

Science.gov (United States)

Pal, Soumitra; Xiao, Peng; Rajasekaran, Sanguthevar

2016-08-18

Motif search is an important step in extracting meaningful patterns from biological data. The general problem of motif search is intractable and there is a pressing need to develop efficient, exact and approximation algorithms to solve this problem. In this paper, we present several novel, exact, sequential and parallel algorithms for solving the (l,d) Edit-distance-based Motif Search (EMS) problem: given two integers l,d and n biological strings, find all strings of length l that appear in each input string with atmost d errors of types substitution, insertion and deletion. One popular technique to solve the problem is to explore for each input string the set of all possible l-mers that belong to the d-neighborhood of any substring of the input string and output those which are common for all input strings. We introduce a novel and provably efficient neighborhood exploration technique. We show that it is enough to consider the candidates in neighborhood which are at a distance exactly d. We compactly represent these candidate motifs using wildcard characters and efficiently explore them with very few repetitions. Our sequential algorithm uses a trie based data structure to efficiently store and sort the candidate motifs. Our parallel algorithm in a multi-core shared memory setting uses arrays for storing and a novel modification of radix-sort for sorting the candidate motifs. The algorithms for EMS are customarily evaluated on several challenging instances such as (8,1), (12,2), (16,3), (20,4), and so on. The best previously known algorithm, EMS1, is sequential and in estimated 3 days solves up to instance (16,3). Our sequential algorithms are more than 20 times faster on (16,3). On other hard instances such as (9,2), (11,3), (13,4), our algorithms are much faster. Our parallel algorithm has more than 600 % scaling performance while using 16 threads. Our algorithms have pushed up the state-of-the-art of EMS solvers and we believe that the techniques introduced in

Efficient numerical simulation of non-integer-order space-fractional reaction-diffusion equation via the Riemann-Liouville operator

Science.gov (United States)

Owolabi, Kolade M.

2018-03-01

In this work, we are concerned with the solution of non-integer space-fractional reaction-diffusion equations with the Riemann-Liouville space-fractional derivative in high dimensions. We approximate the Riemann-Liouville derivative with the Fourier transform method and advance the resulting system in time with any time-stepping solver. In the numerical experiments, we expect the travelling wave to arise from the given initial condition on the computational domain (-∞, ∞), which we terminate in the numerical experiments with a large but truncated value of L. It is necessary to choose L large enough to allow the waves to have enough space to distribute. Experimental results in high dimensions on the space-fractional reaction-diffusion models with applications to biological models (Fisher and Allen-Cahn equations) are considered. Simulation results reveal that fractional reaction-diffusion equations can give rise to a range of physical phenomena when compared to non-integer-order cases. As a result, most meaningful and practical situations are found to be modelled with the concept of fractional calculus.

An ILP based Algorithm for Optimal Customer Selection for Demand Response in SmartGrids

Energy Technology Data Exchange (ETDEWEB)

Kuppannagari, Sanmukh R. [Univ. of Southern California, Los Angeles, CA (United States); Kannan, Rajgopal [Louisiana State Univ., Baton Rouge, LA (United States); Prasanna, Viktor K. [Univ. of Southern California, Los Angeles, CA (United States)

2015-12-07

Demand Response (DR) events are initiated by utilities during peak demand periods to curtail consumption. They ensure system reliability and minimize the utility’s expenditure. Selection of the right customers and strategies is critical for a DR event. An effective DR scheduling algorithm minimizes the curtailment error which is the absolute difference between the achieved curtailment value and the target. State-of-the-art heuristics exist for customer selection, however their curtailment errors are unbounded and can be as high as 70%. In this work, we develop an Integer Linear Programming (ILP) formulation for optimally selecting customers and curtailment strategies that minimize the curtailment error during DR events in SmartGrids. We perform experiments on real world data obtained from the University of Southern California’s SmartGrid and show that our algorithm achieves near exact curtailment values with errors in the range of 10^-7 to 10^-5, which are within the range of numerical errors. We compare our results against the state-of-the-art heuristic being deployed in practice in the USC SmartGrid. We show that for the same set of available customer strategy pairs our algorithm performs 103 to 107 times better in terms of the curtailment errors incurred.

Relatively Inexact Proximal Point Algorithm and Linear Convergence Analysis

Directory of Open Access Journals (Sweden)

Ram U. Verma

2009-01-01

Full Text Available Based on a notion of relatively maximal (m-relaxed monotonicity, the approximation solvability of a general class of inclusion problems is discussed, while generalizing Rockafellar's theorem (1976 on linear convergence using the proximal point algorithm in a real Hilbert space setting. Convergence analysis, based on this new model, is simpler and compact than that of the celebrated technique of Rockafellar in which the Lipschitz continuity at 0 of the inverse of the set-valued mapping is applied. Furthermore, it can be used to generalize the Yosida approximation, which, in turn, can be applied to first-order evolution equations as well as evolution inclusions.

CPAC: Energy-Efficient Data Collection through Adaptive Selection of Compression Algorithms for Sensor Networks

Science.gov (United States)

Lee, HyungJune; Kim, HyunSeok; Chang, Ik Joon

2014-01-01

We propose a technique to optimize the energy efficiency of data collection in sensor networks by exploiting a selective data compression. To achieve such an aim, we need to make optimal decisions regarding two aspects: (1) which sensor nodes should execute compression; and (2) which compression algorithm should be used by the selected sensor nodes. We formulate this problem into binary integer programs, which provide an energy-optimal solution under the given latency constraint. Our simulation results show that the optimization algorithm significantly reduces the overall network-wide energy consumption for data collection. In the environment having a stationary sink from stationary sensor nodes, the optimized data collection shows 47% energy savings compared to the state-of-the-art collection protocol (CTP). More importantly, we demonstrate that our optimized data collection provides the best performance in an intermittent network under high interference. In such networks, we found that the selective compression for frequent packet retransmissions saves up to 55% energy compared to the best known protocol. PMID:24721763

Universal conductance and conductivity at critical points in integer quantum Hall systems.

Science.gov (United States)

Schweitzer, L; Markos, P

2005-12-16

The sample averaged longitudinal two-terminal conductance and the respective Kubo conductivity are calculated at quantum critical points in the integer quantum Hall regime. In the limit of large system size, both transport quantities are found to be the same within numerical uncertainty in the lowest Landau band, and , respectively. In the second-lowest Landau band, a critical conductance is obtained which indeed supports the notion of universality. However, these numbers are significantly at variance with the hitherto commonly believed value . We argue that this difference is due to the multifractal structure of critical wave functions, a property that should generically show up in the conductance at quantum critical points.

Comparison of Integer Programming (IP) Solvers for Automated Test Assembly (ATA). Research Report. ETS RR-15-05

Science.gov (United States)

Donoghue, John R.

2015-01-01

At the heart of van der Linden's approach to automated test assembly (ATA) is a linear programming/integer programming (LP/IP) problem. A variety of IP solvers are available, ranging in cost from free to hundreds of thousands of dollars. In this paper, I compare several approaches to solving the underlying IP problem. These approaches range from…

Optimization of constrained multiple-objective reliability problems using evolutionary algorithms

International Nuclear Information System (INIS)

Salazar, Daniel; Rocco, Claudio M.; Galvan, Blas J.

2006-01-01

This paper illustrates the use of multi-objective optimization to solve three types of reliability optimization problems: to find the optimal number of redundant components, find the reliability of components, and determine both their redundancy and reliability. In general, these problems have been formulated as single objective mixed-integer non-linear programming problems with one or several constraints and solved by using mathematical programming techniques or special heuristics. In this work, these problems are reformulated as multiple-objective problems (MOP) and then solved by using a second-generation Multiple-Objective Evolutionary Algorithm (MOEA) that allows handling constraints. The MOEA used in this paper (NSGA-II) demonstrates the ability to identify a set of optimal solutions (Pareto front), which provides the Decision Maker with a complete picture of the optimal solution space. Finally, the advantages of both MOP and MOEA approaches are illustrated by solving four redundancy problems taken from the literature

Optimization of constrained multiple-objective reliability problems using evolutionary algorithms

Energy Technology Data Exchange (ETDEWEB)

Salazar, Daniel [Instituto de Sistemas Inteligentes y Aplicaciones Numericas en Ingenieria (IUSIANI), Division de Computacion Evolutiva y Aplicaciones (CEANI), Universidad de Las Palmas de Gran Canaria, Islas Canarias (Spain) and Facultad de Ingenieria, Universidad Central Venezuela, Caracas (Venezuela)]. E-mail: danielsalazaraponte@gmail.com; Rocco, Claudio M. [Facultad de Ingenieria, Universidad Central Venezuela, Caracas (Venezuela)]. E-mail: crocco@reacciun.ve; Galvan, Blas J. [Instituto de Sistemas Inteligentes y Aplicaciones Numericas en Ingenieria (IUSIANI), Division de Computacion Evolutiva y Aplicaciones (CEANI), Universidad de Las Palmas de Gran Canaria, Islas Canarias (Spain)]. E-mail: bgalvan@step.es

2006-09-15

This paper illustrates the use of multi-objective optimization to solve three types of reliability optimization problems: to find the optimal number of redundant components, find the reliability of components, and determine both their redundancy and reliability. In general, these problems have been formulated as single objective mixed-integer non-linear programming problems with one or several constraints and solved by using mathematical programming techniques or special heuristics. In this work, these problems are reformulated as multiple-objective problems (MOP) and then solved by using a second-generation Multiple-Objective Evolutionary Algorithm (MOEA) that allows handling constraints. The MOEA used in this paper (NSGA-II) demonstrates the ability to identify a set of optimal solutions (Pareto front), which provides the Decision Maker with a complete picture of the optimal solution space. Finally, the advantages of both MOP and MOEA approaches are illustrated by solving four redundancy problems taken from the literature.

An Adaptive Test Sheet Generation Mechanism Using Genetic Algorithm

Directory of Open Access Journals (Sweden)

Huan-Yu Lin

2012-01-01

Full Text Available For test-sheet composition systems, it is important to adaptively compose test sheets with diverse conceptual scopes, discrimination and difficulty degrees to meet various assessment requirements during real learning situations. Computation time and item exposure rate also influence performance and item bank security. Therefore, this study proposes an Adaptive Test Sheet Generation (ATSG mechanism, where a Candidate Item Selection Strategy adaptively determines candidate test items and conceptual granularities according to desired conceptual scopes, and an Aggregate Objective Function applies Genetic Algorithm (GA to figure out the approximate solution of mixed integer programming problem for the test-sheet composition. Experimental results show that the ATSG mechanism can efficiently, precisely generate test sheets to meet the various assessment requirements than existing ones. Furthermore, according to experimental finding, Fractal Time Series approach can be applied to analyze the self-similarity characteristics of GA’s fitness scores for improving the quality of the test-sheet composition in the near future.

Developing Subdomain Allocation Algorithms Based on Spatial and Communicational Constraints to Accelerate Dust Storm Simulation

Science.gov (United States)

Gui, Zhipeng; Yu, Manzhu; Yang, Chaowei; Jiang, Yunfeng; Chen, Songqing; Xia, Jizhe; Huang, Qunying; Liu, Kai; Li, Zhenlong; Hassan, Mohammed Anowarul; Jin, Baoxuan

2016-01-01

Dust storm has serious disastrous impacts on environment, human health, and assets. The developments and applications of dust storm models have contributed significantly to better understand and predict the distribution, intensity and structure of dust storms. However, dust storm simulation is a data and computing intensive process. To improve the computing performance, high performance computing has been widely adopted by dividing the entire study area into multiple subdomains and allocating each subdomain on different computing nodes in a parallel fashion. Inappropriate allocation may introduce imbalanced task loads and unnecessary communications among computing nodes. Therefore, allocation is a key factor that may impact the efficiency of parallel process. An allocation algorithm is expected to consider the computing cost and communication cost for each computing node to minimize total execution time and reduce overall communication cost for the entire simulation. This research introduces three algorithms to optimize the allocation by considering the spatial and communicational constraints: 1) an Integer Linear Programming (ILP) based algorithm from combinational optimization perspective; 2) a K-Means and Kernighan-Lin combined heuristic algorithm (K&K) integrating geometric and coordinate-free methods by merging local and global partitioning; 3) an automatic seeded region growing based geometric and local partitioning algorithm (ASRG). The performance and effectiveness of the three algorithms are compared based on different factors. Further, we adopt the K&K algorithm as the demonstrated algorithm for the experiment of dust model simulation with the non-hydrostatic mesoscale model (NMM-dust) and compared the performance with the MPI default sequential allocation. The results demonstrate that K&K method significantly improves the simulation performance with better subdomain allocation. This method can also be adopted for other relevant atmospheric and numerical

Extension of the direct statistical approach to a volume parameter model (non-integer splitting)

International Nuclear Information System (INIS)

Burn, K.W.

1990-01-01

The Direct Statistical Approach is a rigorous mathematical derivation of the second moment for surface splitting and Russian Roulette games attached to the Monte Carlo modelling of fixed source particle transport. It has been extended to a volume parameter model (involving non-integer ''expected value'' splitting), and then to a cell model. The cell model gives second moment and time functions that have a closed form. This suggests the possibility of two different methods of solution of the optimum splitting/Russian Roulette parameters. (author)

Groebner bases in perturbative calculations

Energy Technology Data Exchange (ETDEWEB)

Gerdt, Vladimir P. [Laboratory of Information Technologies, Joint Institute for Nuclear Research, 141980 Dubna (Russian Federation)

2004-10-01

In this paper we outline the most general and universal algorithmic approach to reduction of loop integrals to basic integrals. The approach is based on computation of Groebner bases for recurrence relations derived from the integration by parts method. In doing so we consider generic recurrence relations when propagators have arbitrary integer powers treated as symbolic variables (indices) for the relations.

Groebner bases in perturbative calculations

International Nuclear Information System (INIS)

Gerdt, Vladimir P.

2004-01-01

In this paper we outline the most general and universal algorithmic approach to reduction of loop integrals to basic integrals. The approach is based on computation of Groebner bases for recurrence relations derived from the integration by parts method. In doing so we consider generic recurrence relations when propagators have arbitrary integer powers treated as symbolic variables (indices) for the relations

Absence of even-integer ζ-function values in Euclidean physical quantities in QCD

Science.gov (United States)

Jamin, Matthias; Miravitllas, Ramon

2018-04-01

At order αs4 in perturbative quantum chromodynamics, even-integer ζ-function values are present in Euclidean physical correlation functions like the scalar quark correlation function or the scalar gluonium correlator. We demonstrate that these contributions cancel when the perturbative expansion is expressed in terms of the so-called C-scheme coupling αˆs which has recently been introduced in Ref. [1]. It is furthermore conjectured that a ζ4 term should arise in the Adler function at order αs5 in the MS ‾-scheme, and that this term is expected to disappear in the C-scheme as well.

Edit distance for marked point processes revisited: An implementation by binary integer programming

Energy Technology Data Exchange (ETDEWEB)

Hirata, Yoshito; Aihara, Kazuyuki [Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505 (Japan)

2015-12-15

We implement the edit distance for marked point processes [Suzuki et al., Int. J. Bifurcation Chaos 20, 3699–3708 (2010)] as a binary integer program. Compared with the previous implementation using minimum cost perfect matching, the proposed implementation has two advantages: first, by using the proposed implementation, we can apply a wide variety of software and hardware, even spin glasses and coherent ising machines, to calculate the edit distance for marked point processes; second, the proposed implementation runs faster than the previous implementation when the difference between the numbers of events in two time windows for a marked point process is large.

The role of integer-mode rational surface on peaked profile formation in toroidal rotation velocity and ion temperature

International Nuclear Information System (INIS)

Koide, Yoshihiko; Ishida, Shin-ichi; Sakasai, Akira

1991-03-01

A particular role of integer-mode rational surfaces on the formation of peaked T i (r) and V t (r) is observed. In the case of JT-60 hot-ion regime, the plasma spontaneously changes its peaking region from the inside of q=2 surface to that of broader q=3 surface. (author)

Topologically induced fractional Hall steps in the integer quantum Hall regime of MoS 2

Science.gov (United States)

Firoz Islam, SK; Benjamin, Colin

2016-09-01

The quantum magnetotransport properties of a monolayer of molybdenum disulfide are derived using linear response theory. In particular, the effect of topological terms on longitudinal and Hall conductivity is analyzed. The Hall conductivity exhibits fractional steps in the integer quantum Hall regime. Further complete spin and valley polarization of the longitudinal conductivitity is seen in presence of these topological terms. Finally, the Shubnikov-de Hass oscillations are suppressed or enhanced contingent on the sign of these topological terms.

Trial latencies estimation of event-related potentials in EEG by means of genetic algorithms

Science.gov (United States)

Da Pelo, P.; De Tommaso, M.; Monaco, A.; Stramaglia, S.; Bellotti, R.; Tangaro, S.

2018-04-01

Objective. Event-related potentials (ERPs) are usually obtained by averaging thus neglecting the trial-to-trial latency variability in cognitive electroencephalography (EEG) responses. As a consequence the shape and the peak amplitude of the averaged ERP are smeared and reduced, respectively, when the single-trial latencies show a relevant variability. To date, the majority of the methodologies for single-trial latencies inference are iterative schemes providing suboptimal solutions, the most commonly used being the Woody’s algorithm. Approach. In this study, a global approach is developed by introducing a fitness function whose global maximum corresponds to the set of latencies which renders the trial signals most aligned as possible. A suitable genetic algorithm has been implemented to solve the optimization problem, characterized by new genetic operators tailored to the present problem. Main results. The results, on simulated trials, showed that the proposed algorithm performs better than Woody’s algorithm in all conditions, at the cost of an increased computational complexity (justified by the improved quality of the solution). Application of the proposed approach on real data trials, resulted in an increased correlation between latencies and reaction times w.r.t. the output from RIDE method. Significance. The above mentioned results on simulated and real data indicate that the proposed method, providing a better estimate of single-trial latencies, will open the way to more accurate study of neural responses as well as to the issue of relating the variability of latencies to the proper cognitive and behavioural correlates.

A cooperative control algorithm for camera based observational systems.

Energy Technology Data Exchange (ETDEWEB)

Young, Joseph G.

2012-01-01

Over the last several years, there has been considerable growth in camera based observation systems for a variety of safety, scientific, and recreational applications. In order to improve the effectiveness of these systems, we frequently desire the ability to increase the number of observed objects, but solving this problem is not as simple as adding more cameras. Quite often, there are economic or physical restrictions that prevent us from adding additional cameras to the system. As a result, we require methods that coordinate the tracking of objects between multiple cameras in an optimal way. In order to accomplish this goal, we present a new cooperative control algorithm for a camera based observational system. Specifically, we present a receding horizon control where we model the underlying optimal control problem as a mixed integer linear program. The benefit of this design is that we can coordinate the actions between each camera while simultaneously respecting its kinematics. In addition, we further improve the quality of our solution by coupling our algorithm with a Kalman filter. Through this integration, we not only add a predictive component to our control, but we use the uncertainty estimates provided by the filter to encourage the system to periodically observe any outliers in the observed area. This combined approach allows us to intelligently observe the entire region of interest in an effective and thorough manner.