• Journal of Korean Institute of Industrial Engineers
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• v.28 no.4
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• pp.425-434
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• 2002

Mobility of service users makes location update and paging (L/P) procedures indispensable features in mobile communication networks. Importance of optimizing the configuration of L/P areas has been increased by the growth of L/P related signaling. In this study, we deal with the L/P configuration which an LA (Location Area) may contain multiple PAs (Paging Areas). Given the network topology, L/P related parameters, and traffics generated by each cell, is provided the problem of finding optimal LA/PA configuration minimizing the amount of L/P related signaling. The optimization problem is solved using a simulated annealing, and detailed computational results are conducted to capture the effects of mobility, call arrival patterns and boundary crossing rate on the LA and PA configurations.

• IE interfaces
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• v.19 no.4
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• pp.270-280
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• 2006

The shipping plan for an efficient augmentation of terminal is NP-hard problem which is subordinate to a shipping quantity. The load location problem and stowage planning problem are two important tactical problems for the efficient operations of container terminals. This paper is concerned with reduction of feasible region in constraints for stowage planning. After designing model which minimizes the number of shifting and the travel distance of the transfer crane, the simulated annealing algorithm is employed to search optimal solution quickly and accurately. In order to apply more realistic approach, the partial restriction through adding hatch is complemented to stowage planning decision problem applied in cluster. A variety of numerical experiments demonstrated that solutions by simulated annealing algorithm are useful and applicable in practice.

• IE interfaces
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• v.20 no.2
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• pp.204-215
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• 2007

This paper addresses vehicle routing planning in freight container transportation systems where a number of loaded containers are to be delivered to their destination places. The system under consideration is static in that all transportation requirements are predetermined at the beginning of a planning horizon. A two-phased procedure is presented for freight container transportation. In the first phase, the optimal model is presented to determine optimal total time to perform given transportation requirements and the minimum of number of vehicles required. Based on the results from the optimal model, in the second phase, ASA(Accelerated Simulated Annealing) algorithm is presented to perform all transportation requirements with the least number of vehicles by improving initial vehicle routing planning constructed by greedy method. It is found that ASA algorithm has an excellent global searching ability through various experiments in comparison with existing methods.

• Journal of Korean Institute of Industrial Engineers
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• v.24 no.2
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• pp.251-260
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• 1998

This paper deals with a simulated annealing neural network model for determining sequences of models inputted into a mixed model assembly line. We first present a energy function fitting to our problem, next determine the value of the parameters of the energy function using convergence ratio and the number of searched feasible solution. Finally we compare our model NMS with the modified Thomopoulos model. The result of the comparison shows that NMS and Thomopoulos offer a similar output in the problems having good smoothness.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.4
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• pp.226-234
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• 2004

A rapid Prototyping system that laser-cuts and laminates thick layers can fabricate 3D objects promptly with a variety of materials. Building such a system must consider the surface distortions due to both vertical-cut layers and triangular surfaces. We developed a tangential layer-cutting algorithm by rearranging tangential lines such that they reconstruct 3D surfaces more closely and also constitute smoother laser trajectories. An energy function that reflects the surface-closeness with the tangential lines was formulated and then the energy was minimized by a gradient descent method. Since this simple method tends to cause many local minima for complex 3D objects, we tried to solve this problem by adding a simulated annealing process to the proposed method. To view and manipulate 3D objects, we also implemented a 3D visual environment. Under this environment, experiments on various 3D objects showed that our algorithm effectively approximates 3D surfaces and makes laser-trajectory feasibly smooth.

• Journal of Fisheries and Marine Sciences Education
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• v.29 no.2
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• pp.544-551
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• 2017

Metaheuristic algorithms are efficient techniques for a class of mathematical optimization problems without having to deeply adapt to the inherent nature of each problem. They are very useful for structural design optimization in which the cost of gradient computation can be very expensive. Among them, the characteristics of simulated annealing and genetic algorithms are briefly discussed. In Metropolis genetic algorithm, favorable features of Metropolis criterion in simulated annealing are incorporated in the reproduction operations of simple genetic algorithm. Numerical examples of structural design optimization are presented. The example structures are truss, breakwater and steel box girder bridge. From the theoretical evaluation and numerical experience, performance and applicability of metaheuristic algorithms for structural design optimization are discussed.

• Journal of the Korea Society of Computer and Information
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• v.7 no.3
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• pp.42-48
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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 genetic algorithm searching solution space for the placement problem, and then compare it with simulated annealing by analyzing the results of each implementation.

• IE interfaces
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• v.15 no.2
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• pp.189-198
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• 2002

Simulated Annealing(SA) approach has been successfully applied to the combinatorial optimization problems with NP-hard complexity. To apply an SA algorithm to specific problems, generic parameters as well as problem-specific parameters must be determined. To overcome the embedded nature of SA, long computational time, some studies suggested the parameter design methods of determining SA related parameters. In this study, we propose a new parameter design approach based on robust design method. To show the effectiveness of the proposed method, the extensive computation experiments are conducted on the mixed-model sequencing problems.

• Journal of Korean Institute of Industrial Engineers
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• v.21 no.1
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• pp.33-49
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• 1995

Simulated annealing(SA) has been admitted as a general purpose optimization technique which can be utilized for almost all kinds of combinatorial optimization problems without much difficulty. But there are still some weak points to be resolved, one of which is the slow speed of convergence. In this study, we carefully review various previous efforts to improve SA and propose some variations of SA which can enhance the speed of convergence to the optimum solution. Then, we apply the revised SA algorithms to the scheduling and hardware allocation problems occurring in high-level synthesis(HLS) of VLSI design. We confirm the efficiency of the proposed methods through several HLS examples.

• Proceedings of the KIEE Conference
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• 1994.07a
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• pp.159-161
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• 1994

This paper presents a combined algorithm of simulated annealing and determinstic method which overcomes the defects of two methods and guarantees the fast convergence to the global optimum. This optimization method is applied to optimal design of Interior Permanent Magnet Synchronous Motor. And the result of the proposed algorithm is compared with that of simulated annealing alone.