In this paper, we consider an accelerated shrinking projection based parallel hybrid algorithm to study the split null point problem (SNPP) associated with the maximal monotone operators in Hilbert spaces. The analysi...
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In this paper, we consider an accelerated shrinking projection based parallel hybrid algorithm to study the split null point problem (SNPP) associated with the maximal monotone operators in Hilbert spaces. The analysis of the proposed algorithm provides strong convergence results under suitable set of control conditions as well as viability with the help of a numerical experiment. The results presented in this paper improve various existing results in the current literature.
The purpose of the present paper is to construct a common solution of the split null point problem associated with the maximal monotone operators and the fixed point problem associated with a finite family of k-demico...
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The purpose of the present paper is to construct a common solution of the split null point problem associated with the maximal monotone operators and the fixed point problem associated with a finite family of k-demicontractive operators in Hilbert spaces. We compute the optimal common solution via inertial parallel hybrid algorithm under a suitable set of control conditions. The viability of parallel implementation of the algorithm is demonstrated for various theoretical as well as numerical results. The results presented in this paper improve various existing results in the current literature.
This paper provides iterative construction of a common solution associated with the classes of equilibrium problems (EP) and split convex feasibility problems. In particular, we are interested in the EP defined with r...
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This paper provides iterative construction of a common solution associated with the classes of equilibrium problems (EP) and split convex feasibility problems. In particular, we are interested in the EP defined with respect to the pseudomonotone bifunction, the fixed point problem (FPP) for a finite family of -demicontractive operators, and the split null point problem. From the numerical standpoint, combining various classical iterative algorithms to study two or more abstract problems is a fascinating field of research. We, therefore, propose an iterative algorithm that combines the parallelhybrid extragradient algorithm with the inertial extrapolation technique. The analysis of the proposed algorithm comprises theoretical results concerning strong convergence under a suitable set of constraints and numerical results.
The quadratic assignment problem (QAP) is a combinatorial optimization problem, which is computationally demanding, and considered to be NP-hard. Therefore, the problem cannot be solved in polynomial time. The known s...
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The quadratic assignment problem (QAP) is a combinatorial optimization problem, which is computationally demanding, and considered to be NP-hard. Therefore, the problem cannot be solved in polynomial time. The known sequential algorithms can solve small problem instances within long computational times;moreover, parallelization may provide only a linear speed-up. Near-optimal solutions can be obtained in feasible times using heuristics like genetic algorithms and tabu search. The QAP algorithms can be modified to solve various problems like the travelling salesman problem, the data allocation problem, and the file allocation problem. In this paper, a parallel hybrid algorithm (PHA) with three stages was proposed. In the first stage, a genetic algorithm was used to obtain a high quality seed. Later, a diversification phase was run on the initial seed. Finally, a robust tabu search was run on the intermediate solution to find a near-optimal result. parallel computing was used to increase the seed quality, and a considerable speed-up was obtained in the diversification phase of the tabu search. The QAPLIB benchmark instances were used to conduct the experiments. The PHA is quite competitive with respect to the best-performing algorithms in the literature in terms of solution quality and execution time. It achieves results on average within 0.05% of the best solutions given in the QAPLIB. The PHA was able to solve even the largest problem instance size of 256 within 11 h, and with a higher accuracy than the best-known solutions. It was also observed that the solution quality improved considerably especially for larger instances, when the degree of parallelism increased. (C) 2014 Elsevier Ltd. All rights reserved.
The majority of multiobjective genetic algorithms is computationally expensive, therefore they often need to be parallelized before they can be used to solve practical tasks. parallelization of multiobjective genetic ...
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ISBN:
(纸本)9781424481262
The majority of multiobjective genetic algorithms is computationally expensive, therefore they often need to be parallelized before they can be used to solve practical tasks. parallelization of multiobjective genetic algorithms is a relatively studied area, but no clearly winning approach has appeared yet. In this paper we present a novel parallel hybrid algorithm which combines multiobjective and single-objective genetic algorithms. We show that this algorithm can be successfully used to solve multiobjective optimization problems while outperforming more traditional parallel versions of multiobjective genetic algorithms.
作者：
Sipos, András A.sa128@hszk.bme.huDepartment of Mechanics
Materials and Structures and Center of Applied Mathematics and Computational Physics Budapest University of Technology and Economics 1111 Budapest Műegyetem rkp. 3 Hungary
A globally convergent iterative algorithm for computing the spatial deformations of elastic beams without tensile strength is presented. The core of the algorithm is an iterative scheme (consistent with the classical ...
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A globally convergent iterative algorithm for computing the spatial deformations of elastic beams without tensile strength is presented. The core of the algorithm is an iterative scheme (consistent with the classical Kirchhoff rod theory) for locating the neutral axis and thus for determining the curvature. We prove uniqueness and local stability for the general case and global stability for symmetric cross sections. The scheme is embedded in an iteration-free global boundary value problem solver (the so-called parallel hybrid algorithm) to determine spatial equilibrium configurations. The obvious applications are steel reinforced concrete beams and columns, with or without pre-stressing. [ABSTRACT FROM AUTHOR]
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