• Steel and Composite Structures
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• v.8 no.6
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• pp.475-490
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• 2008

A hybrid tabu-simulated annealing algorithm is proposed for the optimum design of steel frames. The special character of the hybrid algorithm is that it exploits both tabu search and simulated annealing algorithms simultaneously to obtain near optimum. The objective of optimum design problem is to minimize the weight of steel frames under the actual design constraints of AISC-LRFD specification. The performance and reliability of the hybrid algorithm were compared with other algorithms such as tabu search, simulated annealing and genetic algorithm using benchmark examples. The comparisons showed that the hybrid algorithm results in lighter structures for the presented examples.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.1
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• pp.138-144
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• 2011

L(2, 1)-labeling problem of a graph G = (V, E) is a problem to find an efficient way to distribute radio frequencies to various wireless equipments in wireless networks. In this work, we suggest a Simulated Annealing algorithm that can be applied to the L(2, 1)-labeling problem. By applying the suggested algorithm to various graphs we will try to show the efficiency of our algorithm.

• Structural Engineering and Mechanics
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• v.25 no.2
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• pp.239-268
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• 2007

This paper deals with optimal stacking sequence design of laminate composite structures. The stacking sequence optimisation of laminate composites is formulated as a combinatorial problem and is solved using Simulated Annealing (SA), an algorithm devised based on inspiration of physical process of annealing of solids. The combinatorial constraints are handled using a correction strategy. The SA algorithm is strengthened by embedding Tabu search in order to prevent recycling of recently visited solutions and the resulting algorithm is referred to as tabu embedded simulated Annealing (TSA) algorithm. Computational performance of the proposed TSA algorithm is enhanced through cache-fetch implementation. Numerical experiments have been conducted by considering rectangular composite panels and composite cylindrical shell with different ply numbers and orientations. Numerical studies indicate that the TSA algorithm is quite effective in providing practical designs for lay-up sequence optimisation of laminate composites. The effect of various neighbourhood search algorithms on the convergence characteristics of TSA algorithm is investigated. The sensitiveness of the proposed optimisation algorithm for various parameter settings in simulated annealing is explored through parametric studies. Later, the TSA algorithm is employed for multi-criteria optimisation of hybrid composite cylinders for simultaneously optimising cost as well as weight with constraint on buckling load. The two objectives are initially considered individually and later collectively to solve as a multi-criteria optimisation problem. Finally, the computational efficiency of the TSA based stacking sequence optimisation algorithm has been compared with the genetic algorithm and found to be superior in performance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.5C
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• pp.468-475
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• 2003

In this Paper, we design an optimal binary phase computer generated hologram for Pattern generation using combined genetic algorithm and simulated annealing algorithm together. To design an optimal binary phase computer generated hologram, in searching process of the proposed method, the simple genetic algorithm is used to get an initial random transmittance function of simulated annealing algorithm. Computer simulation shows that the proposed algorithm has better performance than the genetic algorithm or simulated annealing algorithm of terms of diffraction efficiency

• Journal of Korea Society of Digital Industry and Information Management
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• v.17 no.2
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• pp.13-20
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• 2021

Placement is a very important step in the VLSI physical design process. It is the problem of placing circuit modules to optimize the circuit performance and reliability of the circuit. It is used at the layout level to find strongly connected components that can be placed together in order to minimize the layout area and propagation delay. The most popular algorithms for circuit placement include the cluster growth, simulated annealing, integer linear programming and genetic algorithm. In this paper we propose a adapted genetic algorithm searching solution space for the placement problem, and then compare it with simulated annealing and genetic algorithm by analyzing the results of each implementation. As a result, it was found that the adaptive genetic algorithm approaches the optimal solution more effectively than the simulated annealing and genetic algorithm.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.4
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• pp.371-378
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• 1999

This paper presents an efficient algorithm for loss reduction of distribution system by automatic sectionalizing switch operation in large scale distribution systems of radial type. Simulated Annealing algorithm among optimization techniques can avoid escape from local minima by accepting improvements in cost, but the use of this algorithm is also responsible for an excessive computation time requirement. To overcome this major limitation of Simulated Annealing algorithm, we may use advanced Simulated Annealing algorithm. All constaints are divided into two constraint group by using perturbation mechanism and penalty factor, so all trail solutions are feasible. The polynomial-time cooling schedule is used which is based on the statistics calculation during the search. This approaches results in saving CPU time. Numerical examples demonstrate the validity and effectiveness of the proposed methodology.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.3A
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• pp.284-289
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• 2002

In this paper, we propose the fast simulated annealing algorithm to decrease convergence rate in image segmentation using MRF. Simulated annealing algorithm has a good performance in noisy image or texture image, But there is a problem to have a long convergence rate. To fad a solution to this problem, we have labeled each pixel adaptively according to its intensity before simulated annealing. Then, we show the superiority of proposed method through experimental results.

• Journal of Korea Society of Industrial Information Systems
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• v.10 no.4
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• pp.16-25
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• 2005

In this paper, we proposed a novel algorithm combined simulated annealing and genetic algorithms for designing optimal binary phase computer generated hologram. In the process of genetic algorithm searching by block units, after the crossover and mutation operations, simulated annealing algorithm searching by pixel units is inserted. So, the performance of BPCGH was improved. Computer simulations show that the proposed combined iterative algorithm has better performance than the simulated annealing algorithm in terms of diffraction efficiency

• Proceedings of the KSME Conference
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• 2001.06a
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• pp.939-944
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• 2001

Genetic algorithm is modelled on natural evolution and simulated annealing is based on the simulation of thermal annealing. Both genetic algorithm and simulated annealing are stochastic method. So they can find global optimum values. For compare efficiency of SA and GA's, some function value was maximized. In the result, that was a little better than GA's.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.45
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• pp.25-32
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• 1998

A modified simulated annealing algorithm is proposed and applied to the permutation flowshop scheduling with the makespan objective. Based on the job deletion and insertion method, a newly defined Max-min perturbation scheme is proposed to obtain a better candidate solution in the simulated annealing process. The simulation experiments are conducted to evaluate the effectiveness of the proposed algorithm against the existing heuristics and results are reported.