This paper introduces a distributed self-relocation algorithm used in mobile wireless sensor networks with random initial deployments. The algorithm aims at changing the relative distance of the sensors in different d...
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ISBN:
(纸本)9781467331050;9781467331043
This paper introduces a distributed self-relocation algorithm used in mobile wireless sensor networks with random initial deployments. The algorithm aims at changing the relative distance of the sensors in different directions and converging within ten rounds. Simulation results show the algorithm produces a 95% coverage ratio on average in all different initial deployments with average initial coverage ratio from 50% to 80%. Results also show the algorithm works for different sensing models such as binary model and probability model. The algorithm is also robust against inaccurate geo-location information.
In this paper, we show the 2D and 3D scatterometry simulation software which has spectroscopy calculation and optimization algorithm systems. The scatterometry analysis for 3D-structure requires a lot of memory and al...
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ISBN:
(纸本)9780819494634
In this paper, we show the 2D and 3D scatterometry simulation software which has spectroscopy calculation and optimization algorithm systems. The scatterometry analysis for 3D-structure requires a lot of memory and along calculation time. The calculation is sped up by parallel computing using the GPU (Graphics Processor Unit). Here, we use the programming language CUDA (Compute Unified Device Architecture) and CULA (CULApack) for the NVIDIA GPU. Then, we use the real-coded GA (RCGA) to increase the population, to make a more sensitive solution and to get better fitting groove figures. The scatterometry characteristic is examined by choosing the n-th power cosine type period groove.
Modelling, simulation and optimization form an integrated part of modern design practice in engineering and industry. Tremendous progress has been observed for all three components over the last few decades. However, ...
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Modelling, simulation and optimization form an integrated part of modern design practice in engineering and industry. Tremendous progress has been observed for all three components over the last few decades. However, many challenging issues remain unresolved, and the current trends tend to use nature-inspired algorithms and surrogate-based techniques for modelling and optimization. This 4th workshop on Computational optimization, Modelling and Simulation (COMS 2013) at ICCS 2013 will further summarize the latest developments of optimization and modelling and their applications in science, engineering and industry. In this review paper, we will analyse the recent trends in modelling and optimization, and their associated challenges. We will discuss important topics for further research, including parameter-tuning, large-scale problems, and the gaps between theory and applications.
This paper proposes an Innovization procedure approach for a bio-inspired biped gait locomotion controller. We combine a multi-objective evolutionary algorithm and a bio-inspired Central Patterns Generator locomotion ...
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This paper proposes an Innovization procedure approach for a bio-inspired biped gait locomotion controller. We combine a multi-objective evolutionary algorithm and a bio-inspired Central Patterns Generator locomotion controller to generates the necessary limb movements to perform the walking gait of a biped robot. The search for the best set of CPG parameters is optimized by considering multiple objectives along a staged evolution. An innovation analysis is issued to verify relationships between the parameters and the objectives and between objectives themselves in order to find relevant motor behaviors characteristics. The simulation results show the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]
The research study proposes to examine a three-dimensional visualization program, emphasizing on improving genetic algorithms through the optimization of a layout design-based standard and discrete shipbuilding worksh...
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The research study proposes to examine a three-dimensional visualization program, emphasizing on improving genetic algorithms through the optimization of a layout design-based standard and discrete shipbuilding workshop. By utilizing a steel processing workshop as an example, the principle of minimum logistic costs will be implemented to obtain an ideological equipment layout, and a mathematical model. The objectiveness is to minimize the total necessary distance traveled between machines. An improved control operator is implemented to improve the iterative efficiency of the genetic algorithm, and yield relevant parameters. The Computer Aided Tri-Dimensional Interface Application (CATIA) software is applied to establish the manufacturing resource base and parametric model of the steel processing workshop. Based on the results of optimized planar logistics, a visual parametric model of the steel processing workshop is constructed, and qualitative and quantitative adjustments then are applied to the model. The method for evaluating the results of the layout is subsequently established through the utilization of AHP. In order to provide a mode of reference to the optimization and layout of the digitalized production workshop, the optimized discrete production workshop will possess a certain level of practical significance.
Based on the producing 1, 3-propanediol from microorganism continuous fermentation, we study the algorithm and its convergence for the optimal model in this paper. First, taking the zero of the optimality function as ...
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Based on the producing 1, 3-propanediol from microorganism continuous fermentation, we study the algorithm and its convergence for the optimal model in this paper. First, taking the zero of the optimality function as the terminal criteria, an algorithm for the discrete time system of the optimal model is given with the step-size determined by Armijo line search and the search direction by gradient method. By the result that the discrete time system converges to the continuous time optimal model, the optimality function of the discrete time system is a consistent approximation to the one of the continuous time optimal model and an algorithm for the optimal model is given too. The convergence of the algorithm is proved. At last, it shows that the optimal model describes the experiment correctly and the algorithm is feasible by comparing the computing value with the dates in laboratory.
A decomposition-based optimization algorithm is proposed for solving large job shop scheduling problems with the objective of minimizing the maximum lateness. First, we use the constraint propagation theory to derive ...
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A decomposition-based optimization algorithm is proposed for solving large job shop scheduling problems with the objective of minimizing the maximum lateness. First, we use the constraint propagation theory to derive the orientation of a portion of disjunctive arcs. Then we use a simulated annealing algorithm to find a decomposition policy which satisfies the maximum number of oriented disjunctive arcs. Subsequently, each subproblem (corresponding to a subset of operations as determined by the decomposition policy) is successively solved with a simulated annealing algorithm, which leads to a feasible solution to the original job shop scheduling problem. Computational experiments are carried out for adapted benchmark problems, and the results show the proposed algorithm is effective and efficient in terms of solution quality and time performance.
Design for assembly (DFA) has proved its success in manufacturing to face the market challenge. But the assembly process parameters were rarely concerned in the design for assembly. Aimed at this problem, an algorithm...
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ISBN:
(纸本)9780878494705
Design for assembly (DFA) has proved its success in manufacturing to face the market challenge. But the assembly process parameters were rarely concerned in the design for assembly. Aimed at this problem, an algorithm for design for automated assembly of circular parts was proposed. This algorithm can help designer to select the optimal process parameters, such as dimension tolerance of mating parts, location precision of assembly device and so on, subject to budgetary constraints. Finally a case is employed to explain the optimal course.
In this paper, the social behaviors of fish swarm were classified in four ways: foraging behavior, stray behavior, reproductive behavior, and escaping behavior. Inspired by this, a novel artificial fish swarm algorith...
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In this paper, the social behaviors of fish swarm were classified in four ways: foraging behavior, stray behavior, reproductive behavior, and escaping behavior. Inspired by this, a novel artificial fish swarm algorithm (NAFSA) was proposed, which integrated the merits of the self-adaptation strategy, mutation strategy and hybrid strategy into the social behaviors of fish swarm. In the case of mutation strategy, the cloud theory was introduced into the escaping behavior, and the basic cloud generator was used as the mutation operator because of the properties of randomness and stable tendency of a normal cloud model. For the hybrid strategy, the selection, crossover and mutation operator in evolutionary algorithm were applied to define the reproductive ability of an artificial fish. Furthermore, the parameters of Step and Visual were developed in forms of hyperbolic tangent function to adjust the optimize performance dynamically during iterations process. Finally, ten standard test functions are used as the benchmark to validate the effectiveness of the NAFSA. Experimental results confirmed the superiority of NAFSA in terms of both solution quality and convergence speed.
Hybrid optimization and antioptimization of the buckling load of composite cylindrical shells is conducted. The methodology, which has been developed in previous works, is applied to a set of cylindrical composite she...
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Hybrid optimization and antioptimization of the buckling load of composite cylindrical shells is conducted. The methodology, which has been developed in previous works, is applied to a set of cylindrical composite shells, tested at German Aerospace Center. Furthermore, the existing approach is enhanced to fit within the design-optimization scheme. The shells possess traditional imperfections in the form of Fourier series coefficients of their initial imperfection profile. Additionally, two nontraditional imperfections are included in the analysis. The available experimental data is enclosed by either 11-dimensional hyperrectangle or hyperellipsoid. The minimum buckling load of the ensemble of such shells is determined by the antioptimization procedure. Then, this minimum load is maximized by varying the laminate angle. It is shown that the proposed method is a viable and relatively simple alternative to probabilistic approaches and successfully supplements them. It is shown that the proposed method is a successful supplement to probabilistic methods and the deterministic single-buckle approach, because it is deterministic in nature and thus could appeal to engineers and investigators alike, and it takes into account the actual scatter of input data.
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