• International Journal of Internet, Broadcasting and Communication
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• v.16 no.2
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• pp.127-135
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• 2024

Recent studies have shown that inverse design using deep learning has the potential to rapidly generate the optimal design that satisfies the target performance without the need for iterative optimization processes. Unlike traditional methods, deep learning allows the network to rapidly generate a large number of solution candidates for the same objective after a single training, and enables the generation of diverse designs tailored to the objectives of inverse design. These inverse design techniques are expected to significantly enhance the efficiency and innovation of design processes in various fields such as aerospace, biology, medical, and engineering. We analyzes inverse design models that are mainly utilized in the nano and chemical fields, and proposes inverse design models based on supervised and unsupervised learning that can be applied to the engineering system. It is expected to present the possibility of effectively applying inverse design methodologies to the design optimization problem in the field of engineering according to each specific objective.

• Journal of the military operations research society of Korea
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• v.11 no.1
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• pp.87-110
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• 1985

This paper presents optimum policy of water supply distribution of the Osaka Prefecural Waterworks System located in the midwest of Japanese Islands. Owing to the ever increasing demand for water, the Osaka Prefectural Government endeavors to expand potable and industrial water distribution system to satisfy the growing water demand of the constituents under its jurisdiction. In this regard, the paper discusses a problem of establishing an efficient and effective water distribution system. The criteria to be considered are stability of water level at the reservoirs, stability of flow in the network, and the water treatment and distribution cost. These objective functions may be combined to form a multiple objective optimization problem or may be used independently and formulated into single objective optimization problems.

• Transactions of Materials Processing
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• v.9 no.5
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• pp.512-525
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• 2000

Designers are frequently faced with multiple quality issues in injection molded parts. These issues are usually In conflict with each other, and thus tradeoff needs to be made to reach a final compromised solutions. The objective of this study is to develop an automated injection molding design methodology, whereby part defects such as warpage and weld line are optimized. The features of the proposed methodology are as follows: first, Utility Function approach is applied to transform the original multiple objective problem into single objective problem. Second is an implementation of a direct search-based Injection molding optimization procedure with automated consideration of process variation. The Space Reduction Method based on Taguchi's DOE(Design Of Experiment) is used as a general optimization tool in this study. The computational experimental verification of the methodology was partially carried out for a can model of Cavallero Plastics Incorporation, U. S. A. Applied to production, this study will be of immense value to companies in reducing the product development time and enhancing the product quality.

• Proceedings of the Korean Society For Composite Materials Conference
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• 1999.11a
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• pp.124-129
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• 1999

In this study, a design method for the flat sound radiator is developed to make new sound radiator system, whose shape is much thinner than that of conventional loudspeaker. Piezofilm (PVDF) is used as actuators of flat sound radiator. To avoid the distortion of sound radiated from flat sound radiator, the frequency response of radiated sound to be flat is taken as the design objective. The electrode pattern and orientation angle of piezofilm actuator is optimized to satisfy the design objective. The formulation is based on the coupled finite element and boundary element method. Genetic algorithm is used in the optimization process, which is useful in the optimization of discrete design variables. Frequency response with optimized piezofilm actuator is made flat enough to satify the design objective. For the enhancement of sound power, double-layered piezofilm actuators are also considered. The sound power with double-layered actuator becomes larger than that with single-layered actuator as expected.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11a
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• pp.869-874
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• 2005

This paper proposes the Pareto artificial life algorithm for a multi-objective function optimization problem. The artificial life algorithm for a single objective function optimization problem is improved through incorporating the new method to estimate the fitness value fur a solution and the Pareto list to memorize and to improve the Pareto optimal set. The proposed algorithm is applied to the optimum design of a Journal bearing which has two objective functions. The Pareto front and the optimal solution set for the application are reported to present the possible solutions to a decision maker or a designer.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.2
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• pp.254-260
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• 2017

The service life of civil infrastructure needs to be maintained or extended through appropriate inspections and maintenance planning, which results from the optimization process. A multi-objective optimization process can lead to more rational and flexible trade-off solutions rather than a single-objective optimization for the service life management of civil infrastructure. Recent investigations on the service life management of civil infrastructure were generally based on minimizing the life-cycle cost analysis and maximizing the structural performance. Various objectives for service life management have been developed using novel probabilistic concepts and methods over the last few decades. On the other hand, an increase in the number of objectives in a multi-objective optimization problem can lead to difficulties in computational efficiency, visualization, and decision making. These difficulties can be overcome using the objective reduction approach to identify the redundant and essential objectives. As a result, the efficiency in computational efforts, visualization, and decision making can be improved. In this paper, the multi-objective optimization using the objective reduction approach was applied to the service life management of concrete bridges. The results showed that four initial objectives can be reduced by two objectives for the optimal service life management.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.2063-2081
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• 2018

A resource allocation algorithm is proposed in this paper to simultaneously minimize the total system power consumption and maximize the system throughput for the downlink of multi-user multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) systems. With the Lagrange dual decomposition method, we transform the original problem to its convex dual problem and prove that the duality gap between the two problems is zero, which means the optimal solution of the original problem can be obtained by solving its dual problem. Then, we use convex optimization method to solve the dual problem and utilize bisection method to obtain the optimal dual variable. The numerical results show that the proposed algorithm is superior to traditional single-objective optimization method in both the system throughput and the system energy consumption.

• Journal of Electrical Engineering and Technology
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• v.8 no.3
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• pp.581-587
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• 2013

Among different linear motors, single-sided linear induction motors have been widely used in industry due to their simplicity and low construction cost. However, these types of motors suffer from low efficiency and power factor. In this paper, an effective procedure is proposed to design single-sided linear induction motors. The designed motor is simulated in MATLAB software in order to investigate the effect of design parameters on the performance of the machine. Regarding the obtained results, the Genetic Algorithm is employed to optimize the design considering product of efficiency and power factor as objective function. The results show significant improvement of the performance. Finally, experimental results and 2D finite element method is used to validate the model parameters and the optimization results.

• Structural Engineering and Mechanics
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• v.63 no.6
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• pp.825-835
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• 2017

Significant improvements to methodologies on structural damage detection (SDD) have emerged in recent years. However, many methods are related to inversion computation which is prone to be ill-posed or ill-conditioning, leading to low-computing efficiency or inaccurate results. To explore a more accurate solution with satisfactory efficiency, a PSO-INM algorithm, combining particle swarm optimization (PSO) algorithm and an improved Nelder-Mead method (INM), is proposed to solve multi-sample objective function defined based on Bayesian inference in this study. The PSO-based algorithm, as a heuristic algorithm, is reliable to explore solution to SDD problem converted into a constrained optimization problem in mathematics. And the multi-sample objective function provides a stable pattern under different level of noise. Advantages of multi-sample objective function and its superior over traditional objective function are studied. Numerical simulation results of a two-storey frame structure show that the proposed method is sensitive to multi-damage cases. For further confirming accuracy of the proposed method, the ASCE 4-storey benchmark frame structure subjected to single and multiple damage cases is employed. Different kinds of modal identification methods are utilized to extract structural modal data from noise-contaminating acceleration responses. The illustrated results show that the proposed method is efficient to exact locations and extents of induced damages in structures.

• International Journal of Naval Architecture and Ocean Engineering
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• v.8 no.6
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• pp.602-614
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• 2016

It is necessary to develop an efficient optimization technique to perform optimum designs which have given design spaces, discrete design values and several design goals. As optimization techniques, direct search method and stochastic search method are widely used in designing of ship structures. The merit of the direct search method is to search the optimum points rapidly by considering the search direction, step size and convergence limit. And the merit of the stochastic search method is to obtain the global optimum points well by spreading points randomly entire the design spaces. In this paper, Pareto Strategy (PS) multi-objective function method is developed by considering the search direction based on Pareto optimal points, the step size, the convergence limit and the random number generation. The success points between just before and current Pareto optimal points are considered. PS method can also apply to the single objective function problems, and can consider the discrete design variables such as plate thickness, longitudinal space, web height and web space. The optimum design results are compared with existing Random Search (RS) multi-objective function method and Evolutionary Strategy (ES) multi-objective function method by performing the optimum designs of double bottom structure and double hull tanker which have discrete design values. Its superiority and effectiveness are shown by comparing the optimum results with those of RS method and ES method.