The purpose of this research is to present a straightforward and relatively efficient method for solving scheduling problems. A new heuristic algorithm, with the objective of minimizing the makespan, is developed and ...
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The purpose of this research is to present a straightforward and relatively efficient method for solving scheduling problems. A new heuristic algorithm, with the objective of minimizing the makespan, is developed and presented in this paper for job shop scheduling problems (JSP). This method determines jobs’ orders for each machine. The assessment is based on the combination of dispatching rules e.g. the “Shortest Processing Time” of each operation, the “Earliest Due Date” of each job, the “Least Tardiness” of the operations in each sequence and the “First come First Serve” idea. Also, unlike most of the heuristic algorithms, due date for each job, prescribed by the user, is considered in finding the optimum schedule. A multitude of JSP problems with different features are scheduled based on this proposed algorithm. The models are also solved with Shifting Bottleneck algorithm, known as one of the most common and reliable heuristic methods. The result of comparison between the outcomes shows that when the number of jobs are less than or equal to the number of machines, the proposed algorithm concludes smaller, and better, makespan in a significantly lower computational time, which shows the superiority of the suggested algorithm. In addition, for a category when the number of jobs are greater than the number of machines, the suggested algorithm generates more efficient results when the ratio of the number of jobs to the number of machines is less than 2.1. However, in this category for the mentioned ratio to be higher than 2.1, the smaller makespan could be generated by either of the methods, and the results do not follow any particular trend, hence, no general conclusions can be made for this case.
This paper presents an investigation into fault tolerance for the fine-grained parallel algorithm for computing an incomplete LU factorization. Results concerning the convergence of the algorithm with respect to the o...
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作者:
McKenzie, Frederic D.Modeling
Simulation and Visualization Engineering Department Old Dominion University NorfolkVA United States
The Accreditation Board for engineering and Technology (ABET) is an internationally known organization for recognizing engineering programs that work towards student attainment in learning outcomes that conform to eng...
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ISBN:
(纸本)9788897999485
The Accreditation Board for engineering and Technology (ABET) is an internationally known organization for recognizing engineering programs that work towards student attainment in learning outcomes that conform to engineering disciplines and have a process for measuring attainment and continuous improvement. There are eight general criteria to be satisfied that include student outcomes, educational objectives, curriculum, facilities and faculty. Additionally, there may be program-specific requirements depending on the particular discipline. The modeling and simulation (M&S) engineering (M&SE) program at Old Dominion University satisfies the program criteria for general engineering in the ABET engineering Accreditation Commission and declares detailed discipline-specific student outcomes to ensure unambiguous definition of a pioneering program in order to set a standard that can be utilized as a template for future up-and-coming M&SE programs. This paper presents the curriculum and programspecific outcomes that have been incorporated into our continuous improvement process for student attainment of our M&S engineering program outcomes.
This paper presents an investigation into fault tolerance for the fine-grained parallel algorithm for computing an incomplete LU factorization. Results concerning the convergence of the algorithm with respect to the o...
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ISBN:
(纸本)9781510838222
This paper presents an investigation into fault tolerance for the fine-grained parallel algorithm for computing an incomplete LU factorization. Results concerning the convergence of the algorithm with respect to the occurrence of faults, and the impact of any sub-optimality in the produced incomplete factors in Krylov subspace solvers are given. Numerical tests show that the simple algorithmic changes suggested here can ensure convergence of the fine-grained parallel incomplete factorization, and improve the performance of the use of the resulting factors as preconditioners in Krylov subspace solvers if faults do occur.
Energy-efficient computing is crucial to achieving exascale performance. Power capping and dynamic voltage/frequency scaling may be used to achieve energy savings. The Intel Xeon Phi implements a power capping strateg...
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The first undergraduate degree program in modeling and simulationengineering recently was implemented at Old Dominion University. The program awards the Bachelor of Science Degree in modeling and simulation Engineeri...
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There are frequent user studies in flow visualization for comparing different algorithms in the effectiveness. While much work is focused on statistical analysis of the collected results, considerable bias arising fro...
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As data grows at exponential rates toward exa-scale (1018) computing, it is necessary to exploit scientific visualization in the form of a visual, informative, and interactive methodology to help resolve daunting prob...
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To reduce the losses caused by natural disasters such as hurricanes, it is necessary to build effective and efficient emergency management/planning systems for cities. With increases in volume, variety and acquisition...
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The Dual Contouring algorithm (DC) is a grid-based process used to generate surface meshes from volumetric data. The advantage of DC is that it can reproduce sharp features by inserting vertices anywhere inside the gr...
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The Dual Contouring algorithm (DC) is a grid-based process used to generate surface meshes from volumetric data. The advantage of DC is that it can reproduce sharp features by inserting vertices anywhere inside the grid cube, as opposed to the Marching Cubes (MC) algorithm that can insert vertices only on the grid edges. However, DC is unable to guarantee 2-manifold and watertight meshes due to the fact that it produces only one vertex for each grid cube. We present a modified Dual Contouring algorithm that is capable of overcoming this limitation. Our method decomposes an ambiguous grid cube into a maximum of twelve tetrahedral cells; we introduce novel polygon generation rules that produce 2-manifold and watertight surface meshes. We have applied our proposed method on realistic data, and a comparison of the results of our proposed method with results from traditional DC shows the effectiveness of our method.
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