• International Journal of Naval Architecture and Ocean Engineering
• /
• v.11 no.2
• /
• pp.809-818
• /
• 2019

The current trend in shipyard industry is to reduce the weight of ships to support the reduction of CO₂ emissions. In this study, the stiffened plate was optimized that is used for building most of the ship-structure. Further, this study proposed the hybrid Genetic Algorithm (GA) technique, which combines a genetic algorithm and subsequent optimization methods. The design variables included the number and type of stiffeners, stiffener spacing, and plate thickness. The number and type of stiffeners are discrete design variables that were optimized using the genetic algorithm. The stiffener spacing and plate thickness are continuous design variables that were determined by subsequent optimization. The plate deformation was classified into global and local displacement, resulting in accurate estimations of the maximum displacement. The optimization result showed that the proposed hybrid GA is effective for obtaining optimal solutions, for all the design variables.

• Journal of Computational Design and Engineering
• /
• v.2 no.3
• /
• pp.165-175
• /
• 2015

One of the current challenges in the domain of the multicriteria shape optimization is to reduce the calculation time required by conventional methods. The high computational cost is due to the high number of simulation or function calls required by these methods. Recently, several studies have been led to overcome this problem by integrating a metamodel in the overall optimization loop. In this paper, we perform a coupling between the Normal Boundary Intersection - NBI - algorithm with Radial Basis Function - RBF - metamodel in order to have a simple tool with a reasonable calculation time to solve multicriteria optimization problems. First, we apply our approach to academic test cases. Then, we validate our method against an industrial case, namely, shape optimization of the bottom of an aerosol can undergoing nonlinear elasto-plastic deformation. Then, in order to select solutions among the Pareto efficient ones, we use the same surrogate approach to implement a method to compute Nash and Kalai-Smorodinsky equilibria.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.25 no.9
• /
• pp.1444-1451
• /
• 2001

The evolutionary structural optimization(ESO) method has been under continuous development since 1992. The bidirectional evolutionary structural optimization(BESO) method is made of additive and removal procedure. The BESO method is very useful to search the global optimum and to reduce the computational time. This paper presents the ranked bidirectional evolutionary structural optimization(R-BESO) method which adds elements based on a rank, and the performance indicator which can estimate a fully stressed model. The R-BESO method can obtain the optimum design using less iteration number than iteration number of the BESO.

• Journal of the Korean Institute of Telematics and Electronics C
• /
• v.34C no.12
• /
• pp.61-69
• /
• 1997

This paper proposes a new method for improving the performances of the neural network for optimization using a hyubrid of gradient descent method and dynamic tunneling system. The update rule of gradient descent method, which has the fast convergence characteristic, is applied for high-speed optimization. The update rule of dynamic tunneling system, which is the deterministic method with a tunneling phenomenon, is applied for global optimization. Having converged to the for escaping the local minima by applying the dynamic tunneling system. The proposed method has been applied to the travelling salesman problems and the optimal task partition problems to evaluate to that of hopfield model using the update rule of gradient descent method.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.26 no.6_spc
• /
• pp.736-743
• /
• 2016

This study describes optimization methods for adjustment of helicopter main rotor tracking and balancing (RTB). RTB is a essential process for helicopter operation and maintenance. Linear and non-linear models were developed with past RTB test results for estimation of RTB adjustment. Then global and sequential optimization methods were applied to the each of models. Utilization of the individual optimization method with each model is hard to fulfill the RTB requirements because of different characteristics of each blade. Therefore an ensemble model was used to integrate every estimated adjustment result, and an adaptive method was also applied to adjustment values of the linear model to update for next estimations. The goal of this developed RTB adjustment optimization program is to achieve the requirements within 2 run. Additional tests for comparison of weight factor of the ensemble model are however necessary.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.28 no.4
• /
• pp.370-377
• /
• 2004

The density approach and the homogenization design method are representative methods in topology optimization problems. In the topology optimization in magnetic fields, those methods are applied based on the results of the applications In elastic fields. In this study, the density method is modified considering the concept of the homogenization design method. Also, the results of the topology optimization in magnetic fields by the modified density method as well as the homogenization method are compared especially focusing the change of the penalization parameter in the density approach. The effect of the definition of the design domain such as global/local design domain is also discussed.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2017.05a
• /
• pp.184-184
• /
• 2017

A nation-wide water-energy-food (WEF) nexus simulation model has been developed by the authors and successfully applied to South Korea to predict the sustainability of those three resources in the next 30 years. The model was also capable of simulating future scenarios of resources allocation based on priority rules aiming to maximize resources sustainability. However, the process was still relying on several assumptions and trial-and-error approach, which sometimes resulted in non-optimal solutions of resources allocation. In this study, an optimization module was introduced to enhance the model in generating optimal resources management rules. The objective of the optimization was to maximize the reliability index of resources by determining the resources' allocation and/or priority rules for each demand type that accordingly reflect the resources management policies. Implementation of the optimization module would result in balanced allocation and management of limited resources and assist the stakeholders in deciding resources' management plans, either by fulfilling the domestic production or by global trading.

• Journal of Information Processing Systems
• /
• v.15 no.1
• /
• pp.116-126
• /
• 2019

In this paper, an improved one-against-one support vector machine algorithm is used to classify multiple power quality disturbances. To solve the problem of parameter selection, an improved particle swarm optimization algorithm is proposed to optimize the parameters of the support vector machine. By proposing a new inertia weight expression, the particle swarm optimization algorithm can effectively conduct a global search at the outset and effectively search locally later in a study, which improves the overall classification accuracy. The experimental results show that the improved particle swarm optimization method is more accurate than a grid search algorithm optimization and other improved particle swarm optimizations with regard to its classification of multiple power quality disturbances. Furthermore, the number of support vectors is reduced.

• Coupled systems mechanics
• /
• v.11 no.3
• /
• pp.259-266
• /
• 2022

Non-Traditional Optimization methods are successfully used in solving many engineering problems. Shaft is one of important element of machines and it is used to transmit power from a machine which produces power to a machine which absorbs power. In this paper, ten non-traditional optimization methods that are ALO, GWO, DA, FPA, FA, WOA, CSO, PSO, BA and GSA are used to find minimum weight of hollow shaft to get global optimal solution. The problem has two design variables and two inequality constraints. The comparative results show that the Particle Swarm Optimization outperforms other methods and the results are validated using ANSYS.

• International Journal of Naval Architecture and Ocean Engineering
• /
• v.9 no.6
• /
• pp.693-704
• /
• 2017

Blended-Wing-Body Underwater Glider (BWBUG), which has excellent hydrodynamic performance, is a new kind of underwater glider in recent years. In the shape optimization of BWBUG, the lift to drag ratio is often used as the optimization target. However this results in lose of internal space. In this paper, the energy reserve is defined as the direct proportional function of the internal space of BWBUG. A motion model, which relates gliding range to steady gliding motion parameters as well as energy consumption, is established by analyzing the steady-state gliding motion. The maximum gliding range is used as the optimization target instead of the lift to drag ratio to optimizing the shape of BWBUG. The result of optimization shows that the maximum gliding range of initial design is increased by 32.1% though an Efficient Global Optimization (EGO) process.