Many real-world multiple-objective optimization problems have objectives that change over time. These multiple-objective optimization problems are called dynamic multiple-objective optimization problems (DMOPs) and ha...
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Many real-world multiple-objective optimization problems have objectives that change over time. These multiple-objective optimization problems are called dynamic multiple-objective optimization problems (DMOPs) and have received an increased attention. To track the changing Pareto front in DMOPs, the Pareto front at a certain moment needs to be obtained as efficiently as possible, which is challenging for most of existing methods. To this end, we propose a two-level parallel decomposition-based artificial bee colony method for solving DMOPs. To sufficiently accelerate the process of obtaining the Pareto front, a two-level parallel structure is designed in our method. In the first-level parallel structure, the dynamic multi-objective optimization problem at a certain moment is decomposed into a set of single-objective optimization problems that could be solved in parallel. In the second-level parallel structure, a parallel artificial bee colony algorithm is applied to solve each decomposed single -objective optimization problem. Specially, the parallel bee colony algorithm in our method is improved to support the exchange of information among neighbor problems, which is widely accepted to be effective in improving the efficiency of obtaining optimal solutions. To support the implementation of our improved parallel artificial bee colony algorithm, a two-level shared memory structure is designed. Our proposed method is compared with 4 widely used methods on CEC' 2018 multi-objective optimization benchmarks and two constrained dynamic multi-objective optimization problems. The experimental results show that our method outperforms other compared methods in efficiency while maintaining good scalability and convergence.(c) 2023 Published by Elsevier B.V.
We numerically demonstrate that a random dopant fluctuation (RDF) in a source region causes a noticeable variability in the on-current of Si nanowire (NW) transistors, and its effect is much larger than that of a rand...
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ISBN:
(纸本)9781479980000
We numerically demonstrate that a random dopant fluctuation (RDF) in a source region causes a noticeable variability in the on-current of Si nanowire (NW) transistors, and its effect is much larger than that of a random telegraph noise (RTN). This work assesses the static and dynamic variability of NW device characteristics using the ensemble Monte Carlo/molecular dynamics (EMC/MD) simulation, which employs parallel computing technique using a graphic processing unit (GPU). The current flow in a one-dimensional NW device is determined by the number of dopants at the source edge, indicating the importance of forming an abrupt source-channel boundary to suppress the variability.
A full three-dimensional (3D) finite difference time domain (FDTD) approach has been developed to model microwave indoor propagation at 2.4 GHz. Simulations take into account traditional office furniture, dielectric w...
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A full three-dimensional (3D) finite difference time domain (FDTD) approach has been developed to model microwave indoor propagation at 2.4 GHz. Simulations take into account traditional office furniture, dielectric walls, windows etc. Owing to the large computation resources needed to perform the 3D simulations, the algorithm was implemented on a cluster using a parallel computing technique. FDTD results are compared with a multi-wall model and measured data. Good agreement between FDTD and measurements is reported.
The formation and evolution of the microstructure of casting are important research areas in the field of material science and engineering. The solidified microstructure of aluminum alloy was simulated by combining th...
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The formation and evolution of the microstructure of casting are important research areas in the field of material science and engineering. The solidified microstructure of aluminum alloy was simulated by combining the CA (Cellular Automaton) model with macro heat transfer. A modified CA (MCA) model, which uses a more similar shape to the actual dendrite to describe the growth grain, was proposed and studied. Because of the huge computational capacity to simulate the microstructure of casting, a relevant parallel computing technique based on the serial arithmetic was developed, which can greatly improve the computing scale and efficiency and can also ensure the computing accuracy as well. The simulation results are compared with the experimental results and agreed quite well.
parallel design optimization of large structural systems calls for a multilevel approach to the optimization problem. The general optimization problem is decomposed into a number of non-interacting suboptimization pro...
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parallel design optimization of large structural systems calls for a multilevel approach to the optimization problem. The general optimization problem is decomposed into a number of non-interacting suboptimization problems on the first level. They are controlled from the second level through coordination variables. Thus, the solutions of the independent first-level subsystems are directed towards the overall system optimum. In the present paper, optimal design of truss structures using parallel computing technique is described. In this method, optimization of a large truss structure has been carried out by decomposing the structure into sub-domains and suboptimization tasks. Each sub-domain has independent design variables and a small number of behaviour constraints. The two-level sub-domain optimum design approach is summarized by several numerical examples with speedups and efficiencies of algorithms on message passing systems. It has been noticed that the efficiency of the algorithm for design optimization increases with the size of the structure.
In the case of optimizing the circuit configurations such as multi-way power dividers, the planar circuit approach is useful because of its merit of short calculation time. However, as the number of design variable in...
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ISBN:
(纸本)078039433X
In the case of optimizing the circuit configurations such as multi-way power dividers, the planar circuit approach is useful because of its merit of short calculation time. However, as the number of design variable increases, the CPU time required in the optimization becomes large. This paper describes a parallel computing technique of Powell's optimization algorithm using a PC-Cluster, and applies to an integration design of microstrip multi-way power dividers. As a result, it is shown that the parallel processing technique can speed up the circuit optimization with facility.
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