• International conference on construction engineering and project management
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• 2007.03a
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• pp.777-786
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• 2007

This paper presents a modified simulated annealing algorithm to optimize linear scheduling projects with multiple resource constraints and its effectiveness is verified with a proposed problem. A two-stage solution-finding procedure is used to model the problem. Then the simulated annealing and the modified simulated annealing are compared in the same condition. The comparison results and the reasons of improvement by the modified simulated annealing are presented at the end.

• Journal of the Korean institute of surface engineering
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• v.28 no.5
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• pp.259-266
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• 1995

In order to manufacture an attractive waste glass for the permanent and secure disposal of high-level radioactive waste, the complex composition of the simulated nuclear waste glass PNL-7668 was simplified to a composition of sodium borosilicate glass. The substitutions of $Fe_2O_3$ and $Al_2O_3$ were added to examine on the leaching characteristics of simulated nuclear waste glass with variable composition. The leach tests for these glasses were performed according to 'MCC-1, Static Leach Test Procedure' in acid and basic solution. In this study, for the $Al_2O_3$-containing glasses, Na ion release from these glasses was higher in acid solution than in basic solution. As the content of $Fe_2O_3$ was increased in glasses, Na ion release was increased in acid solution, in spite of decrease of amount of total mass diminution.

• Nuclear Engineering and Technology
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• v.55 no.4
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• pp.1300-1309
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• 2023

Simulated debris was synthesized using UO₂, Zr, and stainless steel and a heat treatment method under inert or oxidizing conditions. The primary U solid phase of the debris synthesized at 1473 K under inert conditions was UO₂, whereas a (U, Zr)O₂ solid solution formed at 1873 K. Under oxidizing conditions, a mixture of U₃O₈ and (Fe, Cr)UO₄ phases formed at 1473 K, whereas a (U, Zr)O_2+x solid solution formed at 1873 K. The leaching behavior of the fission products from the simulated debris was evaluated using two methods: the irradiation method, for which fission products were produced via neutron irradiation, and the doping method, for which trace amounts of non-radioactive elements were doped into the debris. The dissolution behavior of U depended on the properties of the debris and aqueous solution for immersion. Cs, Sr, and Ba leached out regardless of the primary solid phases. The leaching of high-valence Eu and Ru ions was suppressed, possibly owing to their solid-solution reaction with or incorporation into the uranium compounds of the simulated debris.

• Journal of the Korean Operations Research and Management Science Society
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• v.31 no.4
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• pp.139-155
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• 2006

The facility location problem of this paper is distinguished from the maximal covering location problem and the flxed-charge facility location problem. We propose the maximal profiting location problem (MPLP) that is the facility location problem maximizing profit with multi-product. We apply to the simulated annealing algorithm, the stochastic evolution algorithm and the accelerated simulated annealing algorithm to solve this problem. Through a scale-down and extension experiment, the MPLP was validated and all the three algorithm enable the near optimal solution to produce. As the computational complexity is increased, it is shown that the simulated annealing algorithm' is able to find the best solution than the other two algorithms in a relatively short computational time.

• IE interfaces
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• v.18 no.4
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• pp.370-381
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• 2005

This study is concerned with seeking the optimal allocation(disposition) for maximizing utility of consolidating old fashioned and new air defense weapon system like SAM-X(Patriot missile) and developing efficient solution algorithm based on simulated annealing(SA) algorithm. The SED(selection by effectiveness degree) procedure is implemented with an enhanced SA algorithm in which neighboring solutions could be generated only within the optimal feasible region by using a specially designed PERTURB function. Computational results conducted on the problem sets with a variety of size and parameters shows the significant efficiency of our SED algorithm over existing methods in terms of both the computation time and the solution quality.

• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.3
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• pp.145-155
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• 2004

The design of a communication network has long been a challenging optimization problem. Since the optimal design of a network topology is a well known as a NP-complete problem, many researches have been conducted to obtain near optimal solutions in polynomial time instead of exact optimal solutions. All of these researches suggested diverse heuristic algorithms that can be applied to network design problems. Among these algorithms, a simulated annealing algorithm has been proved to guarantee a good solution for many NP-complete problems. in applying the simulated annealing algorithms to network design problems, generating mechanisms for initial solutions and candidate solutions play an important role in terms of goodness of a solution and efficiency. This study aims at analyzing these mechanisms through experiments, and then suggesting reliable mechanisms.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.1
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• pp.87-92
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• 2002

Placement is an important step in the physical design of VLSI circuits. It is the problem of placing a set of circuit modules on a chip to optimize the circuit performance. The most popular algorithms for placement include the cluster growth, simulated annealing and integer linear programming. In this paper we propose a stochastic evolution algorithm searching solution space for the placement problem, and then compare it with simulated annealing by analyzing the results of each implementation.

• 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 Journal of the Korea Contents Association
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• v.21 no.7
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• pp.164-170
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• 2021

In VLSI design, partitioning is a task of clustering objects into groups so that a given objective circuit is optimized. 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 partitioning include the Kernighan-Lin algorithm, Fiduccia-Mattheyses heuristic and simulated annealing. In this paper, we propose a adapted genetic algorithm searching solution space for the circuit partitioning problem, and then compare it with simulated annealing and genetic algorithm by analyzing the results of implementation. As a result, it was found that an adaptive genetic algorithm approaches the optimal solution more effectively than the simulated annealing and genetic algorithm.

• Journal of the Korean Operations Research and Management Science Society
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• v.30 no.1
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• pp.177-185
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• 2005

We consider the optimization problem of the geostationary satellite orbital positions. which is very fundamental and important in setting up the new satellite launching plan. We convert the problem into a discrete optimization problem. However, the converted problem is too complex to find an optimal solution. Therefore, we develope the solution procedures using simulated annealing technique. The results of applying our method to some examples are reported.