Special-purpose Algorithm Research Articles

Development of the simulation model for testing the axial torque distribution in an electric vehicle with the dual-motor layout

BACKGROUND: The market of vehicles using electricity as an energy source demonstrates significant growth. Currently, there are more than twenty million electric vehicles worldwide. Leading manufacturers give the high priority to development of electric transport due to lower vehicle service costs, ease of driving as well as zero emissions in environment and almost complete noiselessness at motion. In addition, using the full-wheel drive in an electric vehicle makes it possible to improve off-road capability, ensures more balanced chassis control, precise following the path and constant accuracy of steering. AIMS: Ensuring increase in vehicle course stability, delivering the maximal torque regarding vehicle motion conditions and slip control in dual-motor layouts of electric vehicles. METHODS: In order to solve the given task, implementation of the special-purpose algorithm of torque distribution between driving axles of an electric vehicle is assumed. The paper presents the development of the simulation model of a vehicle, built in the Simcenter Amesim software and considering dynamic properties and features of the vehicle. This model was implemented into the Labcar hardware-in-the-loop facility. RESULTS: The simulation result is comparison with the data obtained during ground testing of the prototype and confirming the aim of simulation model development, in particular the capability of revision and preliminary setting up the algorithm of torque distribution between driving axles of a vehicle. CONCLUSIONS: Based on the results of the testing of the developed facility, it can be concluded that the developed simulation facility is suitable for solving the simulation tasks including research, debugging and primary calibrations of the algorithm of torque distribution between driving axles of a full-wheel driven electric vehicle. The errors at simulation of operation modes relevant to longitudinal and lateral dynamics of the prototype is no more than 7.5% that complies with the simulation aims.

Solving the One-dimensional Cutting Stock Problem under Discrete, Uncertain, Time-varying Demands using a Hybrid of Special-purpose Benders' Decomposition and Column Generation

This study shows the integration of Benders' decomposition, column generation, and a special-purpose algorithm for solving the one-dimensional cutting stock problem under discrete, uncertain, time-varying demands. The results show that there is a linear relationship between the processing time and the number of scenarios involved in the raw material cutting patterns. Moreover, the algorithm results are not different from using column generation. During the search for production patterns, the quality of the solutions relies on the convergence tolerance. As the tolerance approaches zero, the solutions become near-optimal, but the computational time increases substantially. In addition, the experimental results indicate that the proposed method is suitable for large-scale problems.

The Hungarian Method for the Assignment Problem, With Generalized Interval Arithmetic and Its Applications

In this paper, we focus on the solution procedure for fully interval assignment problem (FIAP), Hungarian method is considered into account. In consideration method the given FIAP is decayed into Interval Assignment Problem, solving it with existing method and by using its optimal solutions, an optimal interval assignment solution to the given FIAP is obtained. Although the assignment problem can be solved as an ordinary transportation problem or as Linear programming problem, its unique structure can be exploited, resulting in special purpose algorithm, is called Hungarian method. A numerical example is provided to illustrate the solution procedure developed in this paper.

Large-Scale Frequent Episode Mining from Complex Event Sequences with Hierarchies

Frequent Episode Mining (FEM), which aims at mining frequent sub-sequences from a single long event sequence, is one of the essential building blocks for the sequence mining research field. Existing studies about FEM suffer from unsatisfied scalability when faced with complex sequences as it is an NP-complete problem for testing whether an episode occurs in a sequence. In this article, we propose a scalable, distributed framework to support FEM on “big” event sequences. As a rule of thumb, “big” illustrates an event sequence is either very long or with masses of simultaneous events. Meanwhile, the events in this article are arranged in a predefined hierarchy. It derives some abstractive events that can form episodes that may not directly appear in the input sequence. Specifically, we devise an event-centered and hierarchy-aware partitioning strategy to allocate events from different levels of the hierarchy into local processes. We then present an efficient special-purpose algorithm to improve the local mining performance. We also extend our framework to support maximal and closed episode mining in the context of event hierarchy, and to the best of our knowledge, we are the first attempt to define and discover hierarchy-aware maximal and closed episodes. We implement the proposed framework on Apache Spark and conduct experiments on both synthetic and real-world datasets. Experimental results demonstrate the efficiency and scalability of the proposed approach and show that we can find practical patterns when taking event hierarchies into account.

Single-Peakedness and Total Unimodularity: New Polynomial-Time Algorithms for Multi-Winner Elections

The winner determination problems of many attractive multi-winner voting rules are NP-complete. However, they often admit polynomial-time algorithms when restricting inputs to be single-peaked. Commonly, such algorithms employ dynamic programming along the underlying axis. We introduce a new technique: carefully chosen integer linear programming (IP) formulations for certain voting problems admit an LP relaxation which is totally unimodular if preferences are single-peaked, and which thus admits an integral optimal solution. This technique gives efficient algorithms for finding optimal committees under Proportional Approval Voting (PAV) and the Chamberlin-Courant rule with single-peaked preferences, as well as for certain OWA-based rules. For PAV, this is the first technique able to efficiently find an optimal committee when preferences are single-peaked. An advantage of our approach is that no special-purpose algorithm needs to be used to exploit structure in the input preferences: any standard IP solver will terminate in the first iteration if the input is single-peaked, and will continue to work otherwise.

Parametric Detection and Classification of Compact Conductivity Contrasts With Electrical Impedance Tomography

Electrical impedance tomography is a noninvasive and cost-effective imaging method that is increasingly attractive in the field of medical diagnostics. Several health conditions, such as stroke and solid tumors, are characterized by compact conductivity anomalies surrounded by a fairly regular background. Commonly employed voxel-by-voxel reconstruction methods for impedance imaging share the disadvantages of high computational cost and substantial sensitivity to measurement noise and imperfections in the electrical model describing the domain of interest. We present a special purpose algorithm for automatic detection and identification of compact conductivity variations. The technique exploits a priori structural information and, by reconstructing only the limited number of parameters required to describe a compact conductivity contrast, does not depend on a critical regularization parameter. The most demanding kernels are implemented to run on graphics processing units to accelerate computation. The parametric reconstruction is quicker and more robust than widely employed approaches with respect to measurement noise and imperfections in the electrical model, as shown by computational analysis performed on a segmented head domain and experimental measurements acquired on a cylindrical phantom. When the goal is quick detection of compact conductivity contrasts in complex 3-D domains, the inclusion of specific constraints relating to the problem considered leads to enhanced quality of reconstruction, making the presented technique a promising alternative to common voxel-by-voxel reconstruction methods.

An adaptive special purpose algorithm for a class of two - stage single constrained linear fractional programming problem

This paper presents the development of a special purpose procedure for solving the two - stage single constrained linear fractional programming with bounded variables. This model consists of a constraint under uncertainties on the right hand side. A graphical - based method of Wichakul et al. (2007) was used sequentially along with interpolations of the corresponding Lagrange Multiplier to solve the problem. A comparative study of computational time on various large scale problem sizes with the state of the art Solver-Gurobi was conducted and reported.

A method for comparing flexibility performance for the lifecycle of manufacturing systems under capacity planning constraints

The objective of this work is to describe a method for comparing the flexibility performance of manufacturing systems, in an uncertain environment, under lifecycle considerations and capacity planning constraints. The manufacturing systems costs are estimated over a time horizon and for a large variety of possible market scenarios. In order for the lifecycle cost values to be comparable among different systems, their values are calculated with the use of a special purpose algorithm. Statistical analysis of the estimated cost values is then employed for assessing the flexibility of each manufacturing system. The method is applied in an industrial case for checking, also from a flexibility point of view, the investment on a production system, using real life industrial data.

Deterministic parallel selection algorithms on coarse‐grained multicomputers

AbstractWe present two deterministic parallel Selection algorithms for distributed memory machines, under the coarse‐grained multicomputer model. Both are based on the use of two weighted 3‐medians, that allows discarding at least 1/3 of the elements in each iteration. The first algorithm slightly improves the current experimentally fastest algorithm by Saukas and Song where at least 1/4 of the elements are discarded in each iteration, while the second one is a fast, special purpose algorithm working for a particular class of input, namely an input that can be sorted in linear time using RadixSort. Copyright © 2009 John Wiley & Sons, Ltd.

Scheduling of corrugated paper production

Corrugated paper is produced by gluing three types of papers of the same breadth. Given a set of orders, we first assign each order to one of the standard breadths, and then sequence those assigned to each standard breadth so that they are continuously manufactured from the three rolls of the specified standard breadth equipped in the machine called corrugator. Here we are asked to achieve multi-goals of minimizing total length of roll papers, total loss of papers caused by the differences between standard breadths and real breadths of the orders, and the number of machine stops needed during production. We use integer programming to assign orders to standard breadths, and then develop a special purpose algorithm to sequence the orders assigned to each standard breadth. This is a first attempt to handle scheduling problems of the corrugator machine.

New weak keys in RSA

The security of the RSA system with the prime pairs of some special form is investigated. A new special-purpose algorithm for factoring RSA numbers is proposed. The basic idea of the method is to factor RSA numbers by factoring a well-chosen quadratic polynomial with integral coefficients. When viewed as a general-purpose algorithm, the new algorithm has a high computational complexity. It is shown that the RSA numbern=pq can be easily factored ifp andq have the special form ofp=as+b, q=cs+d, wherea, b, c, d are relatively small numbers. Such prime pairs (p, q) are the weak keys of RSA, so when we generate RSA modulus, we should avoid using such prime pairs (p, q).

Integrated Chance Constraints: Reduced Forms and an Algorithm

We consider integrated chance constraints (ICCs), which provide quantitative alternatives for traditional chance constraints. We derive explicit polyhedral descriptions for the convex feasible sets induced by ICCs, for the case that the underlying distribution is discrete. Based on these reduced forms, we propose an efficient algorithm for this problem class. The relation to conditional value-at-risk models and (simple) recourse models is discussed, leading to a special purpose algorithm for simple recourse models with discretely distributed technology matrix. For both algorithms, numerical results are presented.

Efficient and accurate waveguide mode computation using BI-RME and Lanczos methods

In this paper, a special purpose algorithm for solving large eigenvalue problems based on the Lanczos method is successfully applied to an engineering problem: the electromagnetic analysis and design of passive waveguide devices. For dealing with such complex problems, the boundary integral-resonant mode expansion (BI-RME) technique has been recently proposed. This technique solves integral equations (IEs) through the well-known method of moments (MoM), thus leading to structured eigenvalue problems. These problems frequently become very large when solving complex arbitrary geometries with high accuracy. In such cases, the eigenvalue problem cannot be efficiently solved with standard methods by means of personal computers, essentially due to CPU time and memory allocation requirements. In this paper, we propose an alternative technique, based on the Lanczos method, for the fast and accurate solution of large BI-RME generalized eigenvalue problems. The novel theoretical aspects of this approach, as well as the impacton the original BI-RME formulation, are described. Comparative benchmarks are also successfully presented for the full-wave analysis and design of real passive microwave devices. Copyright © 2005 John Wiley Sons, Ltd.

Localização de escolas do ensino fundamental com modelos capacitado e não-capacitado: caso de Vitória/ES

O presente estudo está dividido em três partes. Na primeira parte, o objetivo do estudo é avaliar a atual localização das escolas públicas, identificando regiões onde há excesso ou escassez de vagas. Para a aplicação prática reportada, foram usados os setores censitários do IBGE, bem como suas informações de população escolarizável em cada setor, enquanto que para o cálculo dos diversos indicadores foi utilizado o software Arcview. Na segunda parte, apresenta-se uma proposta de relocalização resultante da aplicação do modelo da p-mediana. Essa proposta sugere uma distribuição ideal que leva em conta os rearranjos demográficos da área estudada. A terceira parte do estudo considera o modelo da p-mediana capacitado e refaz o estudo de relocalização, mas supondo unidades escolares com capacidade definida. O estudo foi conduzido com as escolas públicas do ensino fundamental na cidade de Vitória/ES, com cerca de 300.000 habitantes, 271 setores censitários e 45.766 escolares na idade 7-14 anos.

Résolution Numérique De Problèmes De Complémentarité Linéaire Et Évaluation D'Options Américaines

In the Black-Scholes framework, the American option pricing problem can be discretized into a finite-dimensional linear complementarity problem. We compare the numerical performances of three algorithms for the linear complementarity problem: the pivotal algorithms of Lemke and of Boriçi and Lüthi, and the iterative approach “Projected Successive Over-Relaxation”. We conclude that a special-purpose algorithm can provide performances vastly superior to those of generic algorithms.

Applying a Network Programming Algorithm to a Networkwide Traffic Control Scheme: Simulation-Based Performance Studies

A complete optimal formulation of a network traffic control scheme in the form of arc flows in a time-expanded network is presented. The platoon dispersion model used in the proposed optimal control formulation forms linear constraints. The integer-linear network programming formulation is solved by using a modified network simplex and branch-and-bound scheme. The formulation does not assume fixed cycle lengths or phase sequences. It assumes full information on external inputs, but it can be incorporated into a sensor-based environment, as well as into a feedback control framework. The integer-linear program formulation may not be efficiently solved by standard simplex and branch-and-bound techniques. Network programming formulations that can be used to handle the linear equations and the integer constraints at the intersections are discussed. A special-purpose network simplex algorithm for fast solution is also mentioned. The optimization model takes the form of mixed integer-linear programming. The control strategies generated by these optimization models were compared with those derived from conventional signal timing models by using the TRAF-NETSIM microscopic simulation model. The proposed optimization models consistently outperformed the conventional signal control methods with respect to the system delay objective. It was found that the optimization models successfully produced optimal signal timing plans for the various signalized intersections, including simulated and real-world networks.

The transportation problem with exclusionary side constraints and two branch-and-bound algorithms

The transportation problem with exclusionary side constraints, a practical distribution and logistics problem, is formulated as a 0–1 mixed integer programming model. Two branch-and-bound (B&B) algorithms are developed and implemented in this study to solve this problem. Both algorithms use the Driebeek penalties to strengthen the lower bounds so as to fathom some of the subproblems, to peg variables, and to guide the selection of separation variables. One algorithm also strongly exploits the problem structure in selecting separation variables in order to find feasible solutions sooner. To take advantage of the underlying network structure of the problem, the algorithms employ the primal network simplex method to solve network relaxations of the problem. A computational experiment was conducted to test the performance of the algorithms and to characterize the problem difficulty. The commercial mixed integer programming software CPLEX and an existing special purpose algorithm specifically designed for this problem were used as benchmarks to measure the performance of the algorithms. Computational results show that the new algorithms completely dominate the existing special purpose algorithm and run from two to three orders of magnitude faster than CPLEX.

Nonlinear Stability of Ring-Stiffened Prestressed Domes

Stability of a newly proposed structural system, namely, the prebuckled or prestressed dome with ring stiffener, is investigated. The prestressed dome is different from traditional domes in that it is made by first elastically buckling shallow, straight radial members and then attaching them to their supports. A special-purpose algorithm devised to consider a staged construction method of the system using nonlinear finite-element models is implemented into the program named DOME3D. Stability of the prestressed dome with two different rise-to-span ratios is studied with a varying number of ring stiffeners. The study shows that the stiffened system is not vulnerable to loading imperfections leading to side-sway buckling. The stiffening methods increased the limit load by more than 100% and changed the buckling mode of the system. For some stiffener configurations, the behavior of the stiffened domes was similar to shell-like domes. The results showed that the stiffening system leads to significant increase in the strength-to-weight ratio of the novel type structure, and improvement in the overall stability behavior of the dome.

Network Traffic Signal Optimization Formulation with Embedded Platoon Dispersion Simulation

The existing network traffic signal optimization formulations usually do not include traffic flow models, except for control schemes such as SCOOT that use simulation for heuristic optimization. Other conventional models normally use isolated intersection optimization with traffic arrival prediction using detector information, or optimization schemes based on green bandwidth. A complete formulation of the problem is presented, including explicit constraints to model the movement of traffic along the streets between the intersections in a time-expanded network, as well as constraints to capture the permitted movements from modern signal controllers. The platoon dispersion model used is the well-known Robertson’s model, which forms linear constraints. Thus, it is a rare example of a traffic simulation being analytically embedded in an optimization formulation. The formulation is an integer-linear program and does not assume fixed cycle lengths or phase sequences. It assumes full information on external inputs but can be incorporated in a sensor-based environment as well as in a feedback control framework. The formulation is an integer-linear program that may not be efficiently solved with standard simplex and branch and bound techniques. Network programming formulations to handle the linear platoon dispersion equations and the integer constraints at the intersections are discussed. A special-purpose network simplex algorithm for fast solutions is also mentioned.

Performance of Several Optimization Methods on Robot Trajectory Planning Problems

Previous article Next article Performance of Several Optimization Methods on Robot Trajectory Planning ProblemsJoseph G. Ecker, Michael Kupferschmid, and Samuel P. MarinJoseph G. Ecker, Michael Kupferschmid, and Samuel P. Marinhttps://doi.org/10.1137/0915084PDFBibTexSections ToolsAdd to favoritesExport CitationTrack CitationsEmail SectionsAboutAbstractThis paper provides a comparison and analysis of the performance of a special purpose algorithm and several specific available nonlinear programming codes applied to a robot trajectory problem.[1] Mokhtar S. Bazaraa and , C. M. Shetty, Nonlinear programming, John Wiley & Sons, New York-Chichester-Brisbane, 1979xiv+560 80f:90110 0476.90035 Google Scholar[2] C. deBoor, A practical guide to splines, Applied Mathematical Sciences, Vol. 27, Springer-Verlag, New York, 1978xxiv+392 80a:65027 0406.41003 CrossrefGoogle Scholar[3] A. Ech-Cherif, , J. G. Ecker, , M. Kupferschmid and , S. P. Marin, Robot Trajectory Planning by Nonlinear Programming, General Motors Research Publication, GMR-6460, General Motors Research Laboratories, Warren, MI, 1988, December Google Scholar[4] J. G. Ecker and , M. Kupferschmid, A computational comparison of the ellipsoid algorithm with several nonlinear programming algorithms, SIAM J. Control Optim., 23 (1985), 657–674 10.1137/0323042 86j:90127 0581.90078 LinkISIGoogle Scholar[5] J. G. Ecker and , M. Kupferschmid, Introduction to Operations Research, Wiley, New York, 1988 0647.90053 Google Scholar[6] D. Goldfarb and , A. Idnani, A numerically stable dual method for solving strictly convex quadratic programs, Math. Programming, 27 (1983), 1–33 84k:90058 0537.90081 CrossrefISIGoogle Scholar[7] Users Manual Math/Library, Sugarland, TX, 1987, April Google Scholar[8] M. Kupferschmid and , J. G. Ecker, EA3: A Practical Implementation of an Ellipsoid Algorithm for Nonlinear Programming, Dept. Mathematical Sciences, Rensselaer Polytechnic Institute, Troy, NY, 1984 Google Scholar[9] L. S. Lasdon, , A. Waren, , A. Jain and , M. W. Ratner, Design and testing of a generalized reduced gradient code for nonlinear programming, Trans. Math. Software, 4 (1978), 34–50 10.1145/355769.355773 0378.90080 CrossrefGoogle Scholar[10] S. P. Marin, Optimal Parametrization of Curves in RN, General Motors Research Publication, GMR-4878, General Motors Research Laboratories, Warren, MI, 1985, August Google Scholar[11] S. P. Marin, Optimal parametrization of curves for robot trajectory design, IEEE Trans. Automat. Control, 33 (1988), 14–31 10.1109/9.393 CrossrefISIGoogle Scholar[12] M. J. D. Powell, VMCWD: A Fortran Subroutine for Constrained Optimization, Paper DAMTP, 1982/NA4, Dept. of Applied Mathematics and Theoretical Physics, University of Cambridge, Cambridge, England, 1982 Google Scholar[13] K. Schittkowski, NLPQL: a FORTRAN subroutine solving constrained nonlinear programming problems, Ann. Oper. Res., 5 (1986), 485–500 89d:90200 CrossrefGoogle ScholarKeywordsnonlinear programmingalgorithm evaluationrobot modeling Previous article Next article FiguresRelatedReferencesCited ByDetails On the Minimum-Time Control Problem for Differential Drive Robots with Bearing ConstraintsJournal of Optimization Theory and Applications, Vol. 173, No. 3 | 11 April 2017 Cross Ref Calculating a near time-optimal jerk-constrained trajectory along a specified smooth pathThe International Journal of Advanced Manufacturing Technology, Vol. 45, No. 9-10 | 19 April 2009 Cross Ref Volume 15, Issue 6| 1994SIAM Journal on Scientific Computing1251-1505 History Submitted:05 December 1988Accepted:21 September 1993Published online:13 July 2006 InformationCopyright © 1994 Society for Industrial and Applied MathematicsKeywordsnonlinear programmingalgorithm evaluationrobot modelingMSC codes90PDF Download Article & Publication DataArticle DOI:10.1137/0915084Article page range:pp. 1401-1412ISSN (print):1064-8275ISSN (online):1095-7197Publisher:Society for Industrial and Applied Mathematics