• Structural Engineering and Mechanics
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• v.35 no.1
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• pp.19-35
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• 2010

This paper proposes a hybrid heuristic and criteria-based method of optimum design which combines the advantages of both the iterated simulated annealing (SA) algorithm and the rigorously derived optimality criteria (OC) for structural optimum design of reinforced concrete (RC) buildings under multi-load cases based on the current Chinese design codes. The entire optimum design procedure is divided into two parts: strength optimum design and stiffness optimum design. A modified SA with the strategy of adaptive feasible region is proposed to perform the discrete optimization of RC frame structures under the strength constraints. The optimum stiffness design is conducted using OC method with the optimum results of strength optimum design as the lower bounds of member size. The proposed method is integrated into the commercial software packages for building structural design, SATWE, and for finite element analysis, ANSYS, for practical applications. Finally, two practical frame-shear-wall structures (15-story and 30-story) are optimized to illustrate the effectiveness and practicality of the proposed optimum design method.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.33 no.3
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• pp.130-136
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• 2010

In this study, we propose a new method for generating candidate solutions based on both the Cauchy and the Gaussian probability distributions in order to use the merit of the solutions generated by these distributions. The Cauchy probability distribution has larger probability in the tail region than the Gaussian distribution. Thus, the Cauchy distribution can yield higher probabilities of generating candidate solutions of large-varied variables, which in turn has an advantage of searching wider area of variable space. On the contrary, the Gaussian distribution can yield higher probabilities of generating candidate solutions of small-varied variables, which in turn has an advantage of searching deeply smaller area of variable space. In order to compare and analyze the performance of the proposed method against the conventional method, we carried out experiments using benchmarking problems of real valued functions. From the result of the experiment, we found that the proposed method based on the Cauchy and the Gaussian distributions outperformed the conventional one for most of benchmarking problems, and verified its superiority by the statistical hypothesis test.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.2
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• pp.147-154
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• 1989

An effective placement of macro blocks having arbitrary width and height is very important in reducing the chip area and the signal delay. In this paper, we proposed a method of macro block placement to obtain the globally optimal placement using simulated annealing, and an efficient algorithm for eliminating the overlaps between the rectangular macro blocks which may remain even after the simulated annealing process is terminated. Each macro block was enlarged to take into account minimal routing area, and these macro blocks were compacted as much as possible during the placement. This procedure was implemented in C language running on MV10000/UNIX computer system, and good placements were obtained by applying this procedure to two circuits which were consisted of 50 and 160 macro blocks respectively. Several parameters giving great effects to final placements were investigated.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.45 no.2
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• pp.93-100
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• 2008

In this paper, we address a novel simulated annealing(SA)-based test scheduling method for testing network-on-chip (NoC)-based systems-on-chip(SoCs), on the assumption that the test platform proposed in [1] is installed. The proposed method efficiently mixed the rectangle packing method with SA and improved the scheduling results by locally changing the test access mechanism(TAM) widths for cores and the testing orders. Experimental results using ITC'02 benchmark circuits show that the proposed algorithm can efficiently reduce the overall test time.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.1
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• pp.213-221
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• 1996

An assembly sequence is considered to be optimal when is minimizes assembly cost while satisfying assembly constraints. To derive such an optimal sequence for robotic assembly, this paper proposes a method using a simulated annealing algorithm. In this method, an energy funciton is derived inconsideration of both the assembly constraints and the assembly cost. The energy function thus derived is iteratively minimized until no further change in energy occurs. During the minimization, the energy is occationally perturbed probabilistically in order to escape from local minima. The minimized energy yields an optimal assembly sequence. To show the effectiveness of the proposed method, case studies are presented for industrial products such as an electrical relay and an automobil alternator. The performance is analyzed by comparing the results with those of a neural network-based method, based upon the optimal solutions of an expert system.

• Journal of Power Electronics
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• v.17 no.5
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• pp.1327-1337
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• 2017

Photovoltaic (PV) systems are influenced by disproportionate impacts on energy production caused by frequent mismatch cases. The occurrence of multiple maximum power points (MPPs) adds complexity to the tracking process in various PV systems. However, current maximum-power point tracking (MPPT) techniques exhibit limited performance. This paper introduces an enhanced simulated annealing (ESA)-based GMPPT technique against multiple MPP issues in P-V curve with different PV system structures. The proposed technique not only distinguishes global and local MPPs but also performs rapid convergence speed and high tracking accuracy of irradiance changing and restart capability detection. Moreover, the proposed global maximum power tracking algorithm can be applied in the central converter of DMPPT and hybrid PV system to meet various application scenarios. Its effectiveness is verified by simulation and test results.

• Nuclear Engineering and Technology
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• v.49 no.1
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• pp.267-276
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• 2017

In any reactor physics analysis, the instantaneous power distribution in the core can be calculated when the actual bundle-wise burnup distribution is known. Considering the fact that CANDU (Canada Deuterium Uranium) utilizes on-power refueling to compensate for the reduction of reactivity due to fuel burnup, in the CANDU fuel management analysis, snapshots of power and burnup distributions can be obtained by simulating and tracking the reactor operation over an extended period using various tools such as the $^*SIMULATE$ module of the Reactor Fueling Simulation Program (RFSP) code. However, for some studies, such as an evaluation of a conceptual design of a next-generation CANDU reactor, the preferred approach to obtain a snapshot of the power distribution in the core is based on the patterned-channel-age model implemented in the $^*INSTANTAN$ module of the RFSP code. The objective of this approach is to obtain a representative snapshot of core conditions quickly. At present, such patterns could be generated by using a program called RANDIS, which is implemented within the $^*INSTANTAN$ module. In this work, we present an alternative approach to derive the patterned-channel-age model where a simulated-annealing-based algorithm is used to find such patterns, which produce reasonable power distributions.

• Journal of Information Processing Systems
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• v.16 no.1
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• pp.132-144
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• 2020

Cloud computing is an emerging technology based on the concept of enabling data access from anywhere, at any time, from any platform. The exponential growth of cloud users has resulted in the emergence of multiple issues, such as the workload imbalance between the virtual machines (VMs) of data centers in a cloud environment greatly impacting its overall performance. Our axis of research is the load balancing of a data center's VMs. It aims at reducing the degree of a load's imbalance between those VMs so that a better resource utilization will be provided, thus ensuring a greater quality of service. Our article focuses on two phases to balance the workload between the VMs. The first step will be the determination of the threshold of each VM before it can be considered overloaded. The second step will be a task allocation to the VMs by relying on an improved and faster version of the meta-heuristic "simulated annealing (SA)". We mainly focused on the acceptance probability of the SA, as, by modifying the content of the acceptance probability, we could ensure that the SA was able to offer a smart task distribution between the VMs in fewer loops than a classical usage of the SA.

• Journal of Korea Game Society
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• v.19 no.4
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• pp.97-108
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• 2019

Recently interests in voice game commands have been increasing due to the diversity and convenience of the input method, but also by the distance between commands. The command distance is the phonetic difference between command utterances, and as such distance increases, the recognition rate improves. In this paper, we propose an IP(Integer Programming) modeling of the problem which is to select a combination of commands from given candidate commands for maximizing the average distance. We also propose a SA(Simulated Annealing)-based algorithm for solving the problem. We analyze the characteristics of our method using experiments under various conditions such as the number of commands, allowable command length, and so on.

• Journal of Convergence for Information Technology
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• v.11 no.8
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• pp.207-211
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• 2021

This paper addresses a two-stage flexible flow shop scheduling problem in which there is one machine in stage 1 and two identical machines in stage 2. The objective is the minimization of the total completion time. The problem is formulated by a mixed integer quadratic programming (MIQP) and a hybrid simulated annealing (HSA) is proposed to solve the MIQP. The HSA adopts the exploration capabilities of a genetic algorithm and incorporates a simulated annealing to reduce the premature convergence. Extensive computational tests on randomly generated problems are carried out to evaluate the performance of the HSA.