scholarly journals An integrated platform for intuitive mathematical programming modeling using LaTeX

2018 ◽  
Vol 4 ◽  
pp. e161 ◽  
Author(s):  
Charalampos P. Triantafyllidis ◽  
Lazaros G. Papageorgiou
Keyword(s):  
Mathematical Programming ◽  
Error Detection ◽  
Development Process ◽  
Optimization Problems ◽  
Scientific Work ◽  
Input Language ◽  
Speed Up ◽  
Cross Platform ◽  
Algebraic Modeling Language ◽  
Friendly Graphical User Interface

This paper presents a novel prototype platform that uses the same LaTeX mark-up language, commonly used to typeset mathematical content, as an input language for modeling optimization problems of various classes. The platform converts the LaTeX model into a formal Algebraic Modeling Language (AML) representation based on Pyomo through a parsing engine written in Python and solves by either via NEOS server or locally installed solvers, using a friendly Graphical User Interface (GUI). The distinct advantages of our approach can be summarized in (i) simplification and speed-up of the model design and development process (ii) non-commercial character (iii) cross-platform support (iv) easier typo and logic error detection in the description of the models and (v) minimization of working knowledge of programming and AMLs to perform mathematical programming modeling. Overall, this is a presentation of a complete workable scheme on using LaTeX for mathematical programming modeling which assists in furthering our ability to reproduce and replicate scientific work.

scholarly journals Accelerating mono-domain cardiac electrophysiology simulations using OpenCL

2015 ◽  
Vol 1 (1) ◽  
pp. 413-417
Author(s):  
Eike M. Wülfers ◽  
Zhasur Zhamoliddinov ◽  
Olaf Dössel ◽  
Gunnar Seemann
Keyword(s):  
Cardiac Electrophysiology ◽  
Cardiac Tissue ◽  
Ionic Currents ◽  
Domain Model ◽  
Electrical Excitation ◽  
Simulation Domain ◽  
Speed Up ◽  
Cross Platform ◽  
Atrial Myocyte ◽  
Intel Xeon

AbstractUsing OpenCL, we developed a cross-platform software to compute electrical excitation conduction in cardiac tissue. OpenCL allowed the software to run parallelized and on different computing devices (e.g., CPUs and GPUs). We used the macroscopic mono-domain model for excitation conduction and an atrial myocyte model by Courtemanche et al. for ionic currents. On a CPU with 12 HyperThreading-enabled Intel Xeon 2.7 GHz cores, we achieved a speed-up of simulations by a factor of 1.6 against existing software that uses OpenMPI. On two high-end AMD FirePro D700 GPUs the OpenCL software ran 2.4 times faster than the OpenMPI implementation. The more nodes the discretized simulation domain contained, the higher speed-ups were achieved.

Opposition-based learning Multi-Verse Optimizer with disruption operator for optimization problems

2021 ◽  
Author(s):  
Mohammad Shehab ◽  
Laith Abualigah
Keyword(s):  
Real World ◽  
Optimization Problems ◽  
Second Stage ◽  
Opposition Based Learning ◽  
High Fitness ◽  
Fitness Value ◽  
Speed Up ◽  
Disruption Operator ◽  
The Given ◽  
Real World Problems

Abstract Multi-Verse Optimizer (MVO) algorithm is one of the recent metaheuristic algorithms used to solve various problems in different fields. However, MVO suffers from a lack of diversity which may trapping of local minima, and premature convergence. This paper introduces two steps of improving the basic MVO algorithm. The first step using Opposition-based learning (OBL) in MVO, called OMVO. The OBL aids to speed up the searching and improving the learning technique for selecting a better generation of candidate solutions of basic MVO. The second stage, called OMVOD, combines the disturbance operator (DO) and OMVO to improve the consistency of the chosen solution by providing a chance to solve the given problem with a high fitness value and increase diversity. To test the performance of the proposed models, fifteen CEC 2015 benchmark functions problems, thirty CEC 2017 benchmark functions problems, and seven CEC 2011 real-world problems were used in both phases of the enhancement. The second step, known as OMVOD, incorporates the disruption operator (DO) and OMVO to improve the accuracy of the chosen solution by giving a chance to solve the given problem with a high fitness value while also increasing variety. Fifteen CEC 2015 benchmark functions problems, thirty CEC 2017 benchmark functions problems and seven CEC 2011 real-world problems were used in both phases of the upgrade to assess the accuracy of the proposed models.

Technological Knowledge Transfer

1992 ◽  
Vol 6 (2) ◽  
pp. 105-108
Author(s):  
Jacob Sajet
Keyword(s):  
Knowledge Transfer ◽  
Development Process ◽  
Scaling Up ◽  
Technological Knowledge ◽  
Early Stages ◽  
Speed Up ◽  
The University

The article examines the university-enterprise relationship through six scenarios. Consistent problems, such as the reluctance of industry to become involved in the early stages of a project and the tendency of universities to be relatively uninterested in scaling up, are outlined. Various solutions are proposed, such as the establishment of ‘incubator-type’ units within universities in order to speed up the development process.

scholarly journals Fresa: A Plant Propagation Algorithm for Black-Box Single and Multiple Objective Optimization

2021 ◽  
Vol 2 (4) ◽  
Keyword(s):  
Mathematical Programming ◽  
Objective Function ◽  
Optimization Problems ◽  
Population Based ◽  
Black Box ◽  
Multiple Objective ◽  
Multiple Objective Optimization ◽  
Plant Propagation ◽  
Propagation Algorithm ◽  
Multiple Dispatch

Fresa implements a nature inspired plant propagation algorithm for the solution of single and multiple objective optimization problems. The method is population based and evolutionary. Treating the objective function as a black box, the implementation is able to solve problems exhibiting behaviour that is challenging for mathematical programming methods. Fresa is easily adapted to new problems which may benefit from bespoke representations of solutions by taking advantage of the dynamic typing and multiple dispatch capabilities of the Julia language. Further, the support for threads in Julia enables an efficient implementation on multi-core computers.

scholarly journals Optimized switch-level soft error detection based on advanced switch-level models

2021 ◽  
Author(s):  
Jalal Mohammad Chikhe
Keyword(s):  
Error Detection ◽  
Early Stage ◽  
Soft Errors ◽  
Logic Gate ◽  
Soft Error ◽  
Combinational Circuits ◽  
Single Event Transient ◽  
New Techniques ◽  
Speed Up ◽  
Logic Threshold

Due to the reduction of transistor size, modern circuits are becoming more sensitive to soft errors. The development of new techniques and algorithms targeting soft error detection are important as they allow designers to evaluate the weaknesses of the circuits at an early stage of the design. The project presents an optimized implementation of soft error detection simulator targeting combinational circuits. The developed simulator uses advanced switch level models allowing the injection of soft errors caused by single event-transient pulses with magnitudes lesser than the logic threshold. The ISCAS'85 benchmark circuits are used for the simulations. The transients can be injected at drain, gate, or inputs of logic gate. This gives clear indication of the importance of transient injection location on the fault coverage. Furthermore, an algorithm is designed and implemented in this work to increase the performance of the simulator. This optimized version of the simulator achieved an average speed-up of 310 compared to the non-algorithm based version of the simulator.

scholarly journals Hybrid Genetic Algorithm and Simulated Annealing for Function Optimization

2017 ◽  
Vol 1 (2) ◽  
pp. 82 ◽  
Author(s):  
Tirana Noor Fatyanosa ◽  
Andreas Nugroho Sihananto ◽  
Gusti Ahmad Fanshuri Alfarisy ◽  
M Shochibul Burhan ◽  
Wayan Firdaus Mahmudy
Keyword(s):  
Genetic Algorithm ◽  
Simulated Annealing ◽  
Optimization Problems ◽  
Linear Optimization ◽  
Hybrid Genetic Algorithm ◽  
Optimal Solution ◽  
Function Optimization ◽  
Non Linear ◽  
Speed Up ◽  
Linear Problems

The optimization problems on real-world usually have non-linear characteristics. Solving non-linear problems is time-consuming, thus heuristic approaches usually are being used to speed up the solution’s searching. Among of the heuristic-based algorithms, Genetic Algorithm (GA) and Simulated Annealing (SA) are two among most popular. The GA is powerful to get a nearly optimal solution on the broad searching area while SA is useful to looking for a solution in the narrow searching area. This study is comparing performance between GA, SA, and three types of Hybrid GA-SA to solve some non-linear optimization cases. The study shows that Hybrid GA-SA can enhance GA and SA to provide a better result

scholarly journals MATHEMATICAL PROGRAMMING APPLICATIONS PECULIARITIES IN SHAKEDOWN PROBLEM/MATEMATINIO PROGRAMAVIMO TAIKYMO KONSTRUKCIJŲ PRISITAIKYMO UŽDAVINIUOSE YPATUMAI

2001 ◽  
Vol 7 (2) ◽  
pp. 106-114
Author(s):  
Ela Chraptovič ◽  
Juozas Atkočiūnas
Keyword(s):  
Mathematical Programming ◽  
Optimization Problems ◽  
Optimality Criteria ◽  
Point Of View ◽  
Design Matrix ◽  
Problem Solution ◽  
Strain Compatibility ◽  
Complete Set ◽  
Mechanical Interpretation

The theory of mathematical programming widely spread as a method of a solution of extreme problems. It accompanies the study of plastic theory problem from its posing up to final solution. However, here again from our point of view not all possibilities are realized. Unfortunately, the use of mathematical programming as an instrument of a numerical solution for structural analysis frequently is also restricted by that. The possibilities of mechanical interpretation of optimality criteria of applied algorithms are not uncovered. The global solution of the problem of mathematical programming exists, if Kuhn-Tucker conditions are satisfied. These conditions do not depend on the applied algorithm of a problem solution. The identity of Kuhn-Tucker conditions with a optimality criteria of Rosen algorithm is finding out in this research. The role of a design matrix for the creating of strain compatibility equations is clarified. The Kuhn-Tucker conditions mean the residual strain compatibility equations in analysis of elastic-plastic systems. It is proved in the article that for problems of limiting equilibrium the Kuhn-Tucker conditions include the dependences of the associated law of plastic flow. The Kuhn-Tucker conditions together with limitations of a source problem of account represent a complete set of dependences of the theory of shakedown. The correct mathematical and mechanical interpretation of the Kuhn-Tucker conditions allows to refuse a direct solution of a dual problem of mathematical programming. It makes easier the solution of optimization problems of structures at shakedown.

Modeling Short-Range Interactions in Concentrated Newtonian Fiber Bundle Suspensions

2021 ◽  
Vol 36 (3) ◽  
pp. 255-263
Author(s):  
N. Meyer ◽  
A. N. Hrymak ◽  
L. Kärger
Keyword(s):  
Short Range ◽  
Development Process ◽  
Contact Point ◽  
Separation Distance ◽  
Fiber Bundles ◽  
Fiber Architecture ◽  
Simulation Framework ◽  
Transient Rheology ◽  
Speed Up ◽  
Cost Efficient

Abstract Sheet Molding Compounds (SMC) offer a cost efficient way to enhance mechanical properties of a polymer with long discontinuous fibers, while maintaining formability to integrate functions, such as ribs, beads or other structural reinforcements. During SMC manufacturing, fibers remain often in a bundled configuration and the resulting fiber architecture determines part properties. Accurate prediction of this architecture by simulation of flow under consideration of the transient rheology and transient fiber orientations can speed up the development process. In particular, the interaction of bundles is of significance to predict molding pressures correctly in a direct simulation approach, which resolves individual fiber bundles. Thus, this work investigates the tangential short-range lubrication forces between fiber bundles with analytical and numerical techniques. A relation between the effective sheared gap between bundles and the bundle separation distance at the contact point is found and compared to experimental results from literature. The result is implemented in an ABAQUS contact subroutine to incorporate short-range interactions in a direct bundle simulation framework.

scholarly journals Differential Evolution with Linear Bias Reduction in Parameter Adaptation

Algorithms ◽  
2020 ◽  
Vol 13 (11) ◽  
pp. 283
Author(s):  
Vladimir Stanovov ◽  
Shakhnaz Akhmedova ◽  
Eugene Semenkin
Keyword(s):  
Differential Evolution ◽  
Optimization Problems ◽  
Differential Evolution Algorithm ◽  
Bias Reduction ◽  
Benchmark Problems ◽  
Basic Algorithm ◽  
Optimization Stage ◽  
Speed Up ◽  
Comparison Of The Results ◽  
Lehmer Mean

In this study, a new parameter control scheme is proposed for the differential evolution algorithm. The developed linear bias reduction scheme controls the Lehmer mean parameter value depending on the optimization stage, allowing the algorithm to improve the exploration properties at the beginning of the search and speed up the exploitation at the end of the search. As a basic algorithm, the L-SHADE approach is considered, as well as its modifications, namely the jSO and DISH algorithms. The experiments are performed on the CEC 2017 and 2020 bound-constrained benchmark problems, and the performed statistical comparison of the results demonstrates that the linear bias reduction allows significant improvement of the differential evolution performance for various types of optimization problems.

scholarly journals An Empirical Investigation on System and Statement Level Parallelism Strategies for Accelerating Scatter Search Using Handel-C and Impulse-C

VLSI Design ◽  
2012 ◽  
Vol 2012 ◽  
pp. 1-11
Author(s):  
M. Walton ◽  
O. Ahmed ◽  
G. Grewal ◽  
S. Areibi
Keyword(s):  
Optimization Problems ◽  
Scatter Search ◽  
Population Based ◽  
Field Programmable ◽  
Speed Up ◽  
Time Required ◽  
High Level ◽  
Level Parallelism ◽  
Code Optimizations ◽  
Established Population

Scatter Search is an effective and established population-based metaheuristic that has been used to solve a variety of hard optimization problems. However, the time required to find high-quality solutions can become prohibitive as problem sizes grow. In this paper, we present a hardware implementation of Scatter Search on a field-programmable gate array (FPGA). Our objective is to improve the run time of Scatter Search by exploiting the potentially massive performance benefits that are available through the native parallelism in hardware. When implementing Scatter Search we employ two different high-level languages (HLLs): Handel-C and Impulse-C. Our empirical results show that by effectively exploiting source-code optimizations, data parallelism, and pipelining, a 28x speed up over software can be achieved.

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