scholarly journals Design, analysis and performance evaluation of parallel algorithms for solving triangular linear systems on multicore platforms

2021 ◽  
Author(s):  
Mounir Marrakchi ◽  
Mounira Belmabrouk
Keyword(s):  
Performance Evaluation ◽  
Integer Programming ◽  
Lower Bound ◽  
Linear System ◽  
Linear Algebra ◽  
Critical Path ◽  
Mixed Integer ◽  
The Third ◽  
Integer Problem ◽  
And Performance

In this paper, we focus on schedulings of 2-steps graph with constant task cost obtained when parallelizing algorithm solving triangular linear system. We present three scheduling approaches having the same least theoretical execution time. The first is designed through solving a 0-1 integer problem by Mixed Integer Programming (MIP), the second is based on the Critical Path Algorithm (CPA) and the third is a particular Column-Oriented Scheduling (COS). The MIP approach experiments were carried out and confirmed that the makespan values of the MIP scheduling coincide with those of the corresponding lower bound already reached. Experimental results of the last two approaches detailing both makespans and efficiencies are presented and show that their practical performances differ though they are theoretically identical. We compare also these results to those of the appropriate procedure in to so-called PLASMA library (Parallel Linear Algebra for Scalable Multi-core Architectures)

scholarly journals Scenario-Based Design for Multiple Microgrids with High DG Penetration Considering Uncertainty on Demand and Generation Side

2019 ◽  
Author(s):  
Alireza Sedaghati ◽  
Hossein Soory
Keyword(s):  
Distributed Generation ◽  
Mixed Integer ◽  
Program Execution ◽  
Objective Functions ◽  
Cuckoo Optimization Algorithm ◽  
Optimal Capacity ◽  
Operation Costs ◽  
Execution Speed ◽  
Integer Problem ◽  
And Performance

In this paper a new scenario-based approach is proposed to design optimized multiple-microgrids considering the uncertainty of load consumption and renewable DGs generation. The proposed method is used to determine the optimal capacity, type, number and location of renewable and controllable distributed generation resources along with the switch optimal location to cluster the traditional distribution network into a set of interconnected microgrids with economic and reliable structured. This study aims to decrease the total design costs including investment and operation costs, system loss cost, air pollution cost as well as the microgrids energy not supplied cost. Different considered objective functions have been modeled using weighted coefficients method as a single-objective nonlinear mixed integer problem. In addition, the uncertainty of the problem input parameters is modeled using scenario generation method, and in order to decrease the computational burden and increase the program execution speed, the backward scenario reduction technique is used. The Cuckoo optimization algorithm is used to optimize the objective function, and also the effect of optimization coefficients on the design problem and the robustness of the proposed algorithm are investigated using sensitivity analysis. Finally, the efficiency and performance of the proposed method are evaluated on the standard 33-bus network and the results show that the proposed method is an effective tool to design interconnected microgrids with consideration of uncertainty.

Optimization and Performance Evaluation of an Integrated Production-Distribution Plan in Supply Chains

2009 ◽  
Author(s):  
Behnam Fahimnia ◽  
Lee Luong ◽  
Romeo Marian
Keyword(s):  
Supply Chain ◽  
Performance Evaluation ◽  
End Users ◽  
Mixed Integer ◽  
Multiple Time ◽  
Supply Network ◽  
Distribution Centers ◽  
Production Distribution ◽  
And Performance ◽  
The Right

Supply Chain Management is the process of integrating and utilizing suppliers, manufacturers, distribution centers, and retailers; so that products are produced and delivered to the end-users at the right quantities and at the right time, while minimizing costs and satisfying customer requirements. From this definition, a supply chain includes three sub-systems: procurement, production, and distribution. The overall performance of a supply-chain is influenced significantly by the decisions taken in its production-distribution plan. A production-distribution plan excludes the procurement activities and integrates the decisions in production, transport and warehousing as well as inventory management. Hence, one key issue in the performance evaluation of a supply network is the modeling and optimization of production-distribution plan considering its actual complexity. This paper develops a mixed integer formulation for a two-echelon supply network that expands the previously reported production-distribution models through the integration of Aggregate Production Plan and Distribution Plan as well as considering the real-world variables and constraints. A Genetic Algorithm is designed for the optimization of the developed model. The methodology will be then implemented to solve a real-life problem incorporating multiple time periods, multiple products, multiple manufacturing plants, multiple warehouses and multiple end-users. To demonstrate the capability of the approach, the validation and performance evaluation of this model will be finally studied for the presented case study.

scholarly journals Design, Building and Performance Evaluation of a Mixed-Mode Solar Dryer for Agricultural Products

2020 ◽  
Vol 15 ◽  
Keyword(s):  
Performance Evaluation ◽  
Relative Humidity ◽  
Moisture Content ◽  
Ambient Temperature ◽  
Solar Collector ◽  
Mixed Mode ◽  
Ambient Air ◽  
Agricultural Products ◽  
The Third ◽  
And Performance

This research work presents the detailed explanation of the design, construction and performance evaluation of mixed-mode solar agricultural products dryer. The experimental set up used for testing the performance of the mixed-mode solar agricultural products dryer and determining the influence of various drying methods on the drying behaviour of agricultural products. Evaluation of the dryer was centered on the moisture content reduction, temperatures and relative humidities variations. 1680 g of freshly potato slides were used for evaluation. The test results gave that the temperatures inside the dryer cabinet and the solar collector were much higher than the ambient temperature during most hours of the daylight. The temperature inside the solar collector was up to 27 o C approximately higher than the ambient temperature. The temperature inside the drying cabinet was up to 22 o C approximately higher than the ambient temperature for about three hours immediately after 12.00 h (noon). The relative humidity in the solar collector and drying cabinet were lower than the ambient air relative humidity, with the ambient air recording the highest relative humidity at each reading followed by the drying cabinet and finally by the solar collector. Because of the decreased relative humidity inside the dryer, all the time, the temperature inside the dryer was high which is sufficient enough to dry the potato at an early time. Based on the results obtained during the test, temperature above 65 o C was recorded inside the drying cabinet. This high temperature in the drying cabinet causes 419 g of moisture to be removed on the first day, 257 g on the second day, 191 g on the third day, 136 g on the fourth day and finally 108 g on the fifth day. At the end of the five days of drying process, the mass of 1680 g of potato was reduced to 569 g. Total amount of moisture removed was 1111 g and total moisture loss was 66.1 %, which is the required amount of moisture to be removed for safe drying of freshly potato slides. The moisture content of the freshly potato slides was 24.9 % at the end of drying for the first day at about 5:00 pm, 20.4 % at the end of drying for the second day, 19 % at the end of drying for the third day, 16.7 % at the end of drying for the fourth day and finally 15.9% at the end of drying for the fifth day. It was observed that the drying rate increased from the end of one day to another, which shows the earlier and faster removal of moisture from the dried item.

scholarly journals A Numeric-Symbolic Solution of GNSS Phase Ambiguity

2020 ◽  
Author(s):  
Béla Paláncz ◽  
Lajos Völgyesi
Keyword(s):  
Global Navigation Satellite Systems ◽  
Mixed Integer ◽  
Phase Ambiguity ◽  
Satellite Systems ◽  
Weighting Matrix ◽  
The Third ◽  
Integer Problem ◽  
Geometric Dilution Of Precision ◽  
Global Navigation Satellite ◽  
Quadratic Mixed Integer Programming

Solution of the Global Navigation Satellite Systems (GNSS) phase ambiguity is considered as a global quadratic mixed integer programming task, which can be transformed into a pure integer problem with a given digit of accuracy. In this paper, three alter-native algorithms are suggested. Two of them are based on local and global linearization via McCormic Envelopes, respectively. These algorithms can be effective in case of simple configuration and relatively modest number of satellites. The third method is a locally nonlinear, iterative algorithm handling the problem as {-1, 0, 1} programming and also lets compute the next best integer solution easily. However, it should keep in mind that the algorithm is a heuristic one, which does not guarantee to find the global integer optimum always exactly. The procedure is very powerful utilizing the ability of the numeric-symbolic abilities of a computer algebraic system, like Wolfram Mathematica and it is properly fast for minimum 4 satellites with normal configuration, which means the Geometric Dilution of Precision (GDOP) should be between 1 and 8. Wolfram Alpha and Wolfram Clouds Apps give possibility to run the suggested code even via cell phones. All of these algorithms are illustrated with numerical examples. The result of the third one was successfully compared with the LAMBDA method, in case of ten satellites sending signals on two carrier frequencies (L1 and L2) with weighting matrix used to weight the GNSS observation and computed as the inverse of the corresponding covariance matrix.

scholarly journals MIPLIB 2017: data-driven compilation of the 6th mixed-integer programming library

2021 ◽  
Author(s):  
Ambros Gleixner ◽  
Gregor Hendel ◽  
Gerald Gamrath ◽  
Tobias Achterberg ◽  
Michael Bastubbe ◽  
...  
Keyword(s):  
Integer Programming ◽  
Mixed Integer Programming ◽  
Optimization Problems ◽  
Selection Process ◽  
Data Driven ◽  
Mixed Integer ◽  
Integer Optimization ◽  
Programming Library ◽  
And Performance ◽  
First Time

AbstractWe report on the selection process leading to the sixth version of the Mixed Integer Programming Library, MIPLIB 2017. Selected from an initial pool of 5721 instances, the new MIPLIB 2017 collection consists of 1065 instances. A subset of 240 instances was specially selected for benchmarking solver performance. For the first time, these sets were compiled using a data-driven selection process supported by the solution of a sequence of mixed integer optimization problems, which encode requirements on diversity and balancedness with respect to instance features and performance data.

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