• Proceedings of the Computational Structural Engineering Institute Conference
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• 2003.10a
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• pp.527-534
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• 2003

This paper presents the LRB-based hybrid base isolation systems employing additional active/semiactive control devices for seismic protection of cable-stayed bridges by examining the ASCE first generation benchmark problem for a cable-stayed bridge. In this study, ideal hydraulic actuators (HAs) and ideal magnetorheological dampers (MRDs) are considered as additional active and semiactive control devices, respectively. Numerical simulation results show that all the hybrid base isolation systems are effective in reducing the structural responses of the benchmark cable-stayed bridge under the historical earthquakes considered. The simulation results also demonstrate that the hybrid base isolation system employing semiactive MRBs is robust to the stiffness uncertainty of the structure, while the hybrid system with active HAs is not. Therefore, the LRB-based hybrid base isolation system employing MRDs could be more appropriate in real applications for full-scale civil infrastructures.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.25 no.3
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• pp.93-106
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• 2021

In this paper, an efficient hybrid numerical method for solving two-asset option pricing problem is presented based on the Crank-Nicolson and the radial basis function methods. For this purpose, the two-asset Black-Scholes partial differential equation is considered. Also, the convergence of the proposed method are proved and implementation of the proposed hybrid method is specifically studied on Exchange and Call on maximum Rainbow options. In addition, this method is compared to the explicit finite difference method as the benchmark and the results show that the proposed method can achieve a noticeably higher accuracy than the benchmark method at a similar computational time. Furthermore, the stability of the proposed hybrid method is numerically proved by considering the effect of the time step size to the computational accuracy in solving these problems.

• Structural Engineering and Mechanics
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• v.86 no.2
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• pp.197-209
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• 2023

In the case of designing control devices in a building, reliance on experimental formulation or engineering concepts without using optimization algorithms leads to non-optimal solutions or design parameters, which makes the use of control devices costly and unreasonable. The optimization algorithms are capable of identifying the required number of parameters for a specific design problem, however, this process is difficult and inefficient in dealing with some specific optimal design processes. This paper aims to introduce an upgraded version of the salp swarm algorithm to handle some engineering design. The performance of the new upgraded algorithm is tested using some benchmark test functions as well as a six-story benchmark building equipped with semi-active MR dampers. The simulation results show that the proposed algorithm can be successfully applied to get an optimal design of the MR dampers in the building.

• Tunnel and Underground Space
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• v.34 no.2
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• pp.127-142
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• 2024

The robustness of a numerical method means that its computational performance is maintained under various modeling conditions. New numerical methods or codes need to be assessed for robustness through benchmark testing. The TOUGH-FLAC modeling approach has been applied to various fields such as subsurface carbon dioxide storage, geological disposal of spent nuclear fuel, and geothermal development both domestically and internationally, and the modeling validity has been examined by comparing the results with experimental measurements and other numerical codes. In the present study, a benchmark test of the TOUGH-FLAC approach was performed based on a coupled thermal-hydro-mechanical behavior problem with an analytical solution. The analytical solution is related to the temperature, pore water pressure, and mechanical behavior of a fully saturated porous medium that is subjected to a point heat source. The robustness of the TOUGH-FLAC approach was evaluated by comparing the analytical solution with the results of numerical simulation. Additionally, the effects of thermal-hydro-mechanical coupling terms, fluid phase change, and timestep on the computation of coupled behavior were investigated.

• Industrial Engineering and Management Systems
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• v.10 no.1
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• pp.7-14
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• 2011

In solving the Job Shop Scheduling Problem, the best solution rarely is completely random; it follows one or more rules (heuristics). The Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Simulated Annealing, and Tabu search, which belong to the Evolutionary Computations Algorithms (ECs), are not efficient enough in solving this problem as they neglect all conventional heuristics and hence they need to be hybridized with different heuristics. In this paper a new algorithm titled "Shaking Optimization Algorithm" is proposed that follows the common methodology of the Evolutionary Computations while utilizing different heuristics during the evolution process of the solution. The results show that the proposed algorithm outperforms the GA, PSO, SA, and TS algorithms, while being a good competitor to some other hybridized techniques in solving a selected number of benchmark Job Shop Scheduling problems.

• Structural Engineering and Mechanics
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• v.59 no.6
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• pp.1071-1094
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• 2016

We employ the so-called problem-dependent linked interpolation concept to develop two cubic 4-node quadrilateral plate finite elements with 12 external degrees of freedom that pass the constant bending patch test for arbitrary node positions of which the second element has five additional internal degrees of freedom to get polynomial completeness of the cubic form. The new elements are compared to the existing linked-interpolation quadratic and nine-node cubic elements presented by the author earlier and to the other elements from literature that use the cubic linked interpolation by testing them on several benchmark examples.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.33 no.3
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• pp.170-177
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• 2009

In the present study, a finite element analysis of conjugate heat transfer problem inside a cavity with a heat-generating conducting body, where constant heat flux is generated, is conducted. A conduction heat transfer problem inside the solid body is automatically coupled with natural convection inside the cavity by using a finite element formulation. A finite element formulation based on SIMPLE type algorithm is adopted for the solution of the incompressible Navier-Stokes equations coupled with energy equation. The proposed algorithm is verified by solving the benchmark problem of conjugate heat transfer inside a cavity having a centered body. Then a conjugate natural heat transfer problem inside a cavity having a heat-generating conducting body with constant heat flux is solved and the effect of the Rayleigh number on the heat transfer characteristics inside a cavity is investigated.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.12
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• pp.1096-1100
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• 2012

Most of previous genetic algorithms for solving graph problems have used a vertex-based encoding. We proposed an edge encoding based new genetic algorithm using a spanning tree. Contrary to general edge-based encoding, a spanning tree-based encoding represents only feasible partitions. As a target problem, we adopted the MAX CUT problem, which is well known as a representative NP-hard problem, and examined the performance of the proposed genetic algorithm. The experiments on benchmark graphs are executed and compared with vertex-based encoding. Performance improvements of the spanning tree-based encoding on sparse graphs was observed.

• Industrial Engineering and Management Systems
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• v.10 no.3
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• pp.203-208
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• 2011

Job shop scheduling is well-known as one of the hardest combinatorial optimization problems and has been demonstrated to be NP-hard problem. In the past decades, several researchers have devoted their effort to develop evolutionary algorithms such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) for job shop scheduling problem. Differential Evolution (DE) algorithm is a more recent evolutionary algorithm which has been widely applied and shown its strength in many application areas. However, the applications of DE on scheduling problems are still limited. This paper proposes a one-stage differential evolution algorithm (1ST-DE) for job shop scheduling problem. The proposed algorithm employs random key representation and permutation of m-job repetition to generate active schedules. The performance of proposed method is evaluated on a set of benchmark problems and compared with results from an existing PSO algorithm. The numerical results demonstrated that the proposed algorithm is able to provide good solutions especially for the large size problems with relatively fast computing time.

• Journal of the Korea Safety Management & Science
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• v.10 no.1
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• pp.145-153
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• 2008

The vehicle routing problem determines each vehicle routes to find the transportation costs, subject to meeting the customer demands of all delivery points in geography. Vehicle routing problem is known to be NP-hard, and it needs a lot of computing time to get the optimal solution, so that heuristics are more frequently developed than optimal algorithms. This study aims to develop a heuristic method which combines guided local search with a tabu search in order to minimize the transportation costs for the vehicle routing assignment and uses ILOG programming library to solve. The computational tests were performed using the benchmark problems. And computational experiments on these instances show that the proposed heuristic yields better results than the simple tabu search does.