• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.1927-1932
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• 2003

In a previous study, the authors have proposed the Cooperative Collision Avoidance (CCA) method which enables mobile robots to cooperatively avoid collisions, by extending the concept of the Velocity Obstacle to multiple robot systems. The method introduced an evaluation function considering an operation objective so that each robot can choose the velocity which optimizes the function. As the evaluation function could be of an arbitrary type, this method is applicable to a wide variety of tasks. However, it complicates the optimization of the function especially in real-time. In addition, construction of the evaluation function requires an operation objective of the other robot which is very hard to obtain without communication. In this paper, the CCA method is improved considering such problems for implementation. To decrease computational costs, the previous method is simplified by introducing two essential assumptions. Then, by treating the desired direction of locomotion for each robot as the operation objective, an operation objective estimator which estimates the desired direction of the other robot is introduced. The only measurement required is the other robot's relative position, since the other information can be obtained through the estimation. Hence, communicational devices that are necessary for most other cooperative methods are not required. Moreover, mobile robots employing the method can avoid collisions with uncooperative robots or moving obstacles as well as with cooperative robots. Consequently, this improved method can be applied to general dynamic environments consisting of various mobile robots.

• International Journal of Precision Engineering and Manufacturing
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• 제8권4호
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• pp.10-15
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• 2007

Taguchi methods have been used for a long time to improve the product quality and process performance of a manufacturing system, Few researchers have applied this methodology in laser beam cutting (LBC) of sheet metals and found the considerable improvement in cut qualities. In all experimental investigations of LBC so far, the objective was to optimize the single quality characteristic at a time. In this paper the simultaneous optimization of multiple quality characteristics such as Kerf width and material removal rate (MRR) during pulsed Nd:YAG LBC of thin sheet of magnetic material (high Silicon-steel) has been presented using Taguchi's quality loss function. The results show the considerable improvement in multiple S/N ratio as compared to initial cutting condition. Also, the comparison of results from single and multi-objective optimization have been presented and it was found that the loss in quality is always possible shifting from single quality to multiple quality optimization.

• International Journal of Precision Engineering and Manufacturing
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• 제1권1호
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• pp.133-145
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• 2000

Plastic molding designers are frequently faced with optimizing multiple defects in injection molded parts. these defects are usually in conflict with each other, and thus a tradeoff needs to be made reach a final compromised solution. In this study, an automated injection molding design methodology has been developed to optimize multiple defects of injection molded parts. Two features of the proposed methodology are as follows: one is to apply the utility theory to transform the original multiple objective optimization problem into single objective optimization problem with utility as objective function, the other is an implementation of a direct search-based injection molding optimization procedure with automated consideration of process variation. The modified complex method is used as a general optimization tool in this research. The developed methodology was applied to an actual molding design and the results showed that the methodology was useful through the CAE simulation using a commercial injection molding software package. Applied to production, this study will be of immense value to industry in reducing the product development time and enhancing the product quality.

• 한국시뮬레이션학회논문지
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• 제6권1호
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• pp.71-84
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• 1997

For many optimization problems where some of the system components are stochastic, the objective functions cannot be represented analytically. Therefore, modeling by computer simulation is one of the most effective means of studying such complex systems. Many, if not most, simulation optimization problems have multiple aspects. Historically, multiple aspects have been combined ad hoc to form a scalar objective function, usually through a linear combination (weighted sum) of the multiple attributes, or by turning objectives into constraints. The genetic algorithm (GA), however, is readily modified to deal with multiple aspects. In this paper we propose a MAGA (Multiple Aspects-based Genetic Algorithm) as an algorithm for finding the Pareto optimal set. We demonstrate its ability to find and maintain a diverse "Pareto optimal population" on two problems.

• 품질경영학회지
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• 제21권1호
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• pp.190-198
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• 1993

A multiple criteria model for the facility layout problem considers both of the quantitative, the cost of the work flow, and qualitative, the closeness rating score, aspect. Rosenblatt, Fortenberry & Cox and Urban have developed multiple criteria models that consider both of the quantitative and qualitative aspect. Fortenberry & Cox's multiplicity model penalizes facilities with undesirable closeness rating and high work flows more than those undesirable closeness rating and low work flow between them to contribute to the objective function regardless of the closeness rating between these facilities. In this paper, it is intended to develops a improved multiple-criteria facility layout model considering the function for maintaning the distance between facilities.

• Ocean Systems Engineering
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• 제5권2호
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• pp.91-107
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• 2015

Ship hull optimization is categorized as a bound, multi variable, multi objective problem with nonlinear constraints. In such analysis, where the objective function representing the performance of the ship generally requires computationally involved hydrodynamic interaction evaluation methods, the objective functions are not smooth. Hence, the evolutionary techniques to attain the optimum hull forms is considered as the most practical strategy. In this study, a parametric ship hull form represented by B-Spline curves is optimized for multiple performance criteria using Genetic Algorithm. The methodology applied to automate the hull form generation, selection of optimization solvers and hydrodynamic parameter calculation for objective function and constraint definition are discussed here.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.73-76
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• 1996

This paper presents a dynamical anti-reset windup (ARW) compensation method for saturating control systems with multiple controllers and/or multiloop configuration. By regarding the difference of the controller states in the absence and presence of saturating actuators as an objective function, the dynamical compensator which minimize the objective function are derived in an integrated fashion. The proposed dynamical compensator is a closed form of the plant and controller parameters. The proposed method guarantees total stability of resulting system. An illustrative example is given to show the effectiveness of the proposed method.

• 지식경영연구
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• 제21권1호
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• pp.27-40
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• 2020

Response surface methodology (RSM) empirically studies the relationship between a response variable and input variables in the product or process development phase. The ultimate goal of RSM is to find an optimal condition of the input variables that optimizes (maximizes or minimizes) the response variable. RSM can be seen as a knowledge management tool in terms of creating and utilizing data, information, and knowledge about a product production and service operations. In the field of product or process development, most real-world problems often involve a simultaneous consideration of multiple response variables. This is called a multiple response surface (MRS) problem. Various approaches have been proposed for MRS optimization, which can be classified into loss function approach, priority-based approach, desirability function approach, process capability approach, and probability-based approach. In particular, the loss function approach is divided into univariate and multivariate approaches at large. This paper focuses on the univariate approach. The univariate approach first obtains the mean square error (MSE) for individual response variables. Then, it aggregates the MSE's into a single objective function. It is common to employ the weighted sum or the Tchebycheff metric for aggregation. Finally, it finds an optimal condition of the input variables that minimizes the objective function. When aggregating, the relative weights on the MSE's should be taken into account. However, there are few studies on how to determine the weights systematically. In this study, we propose an interactive procedure to determine the weights through considering a decision maker's preference. The proposed method is illustrated by the 'colloidal gas aphrons' problem, which is a typical MRS problem. We also discuss the extension of the proposed method to the weighted MSE (WMSE).

• 대한기계학회논문집A
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• 제21권8호
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• pp.1195-1208
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• 1997

Bellows is a component in piping systems which absorbs mechanical deformation with flexibility. Its geometry is an axial symmetric shell which consists of two toroidal shells and one annular plate or conical shell. In order to analyze bellows, this study presents the finite element analysis using a conical frustum shell element. A finite element analysis is developed to analyze various bellows. The validity of the developed program is verified by the experimental results for axial and lateral stiffness. The formula for calculating the natural frequency of bellows is made by the simple beam theory. The formula for fatigue life is also derived by experiments. The shape optimal design problem is formulated using multiple objective optimization. The multiple objective functions are transformed to a scalar function by weighting factors. The stiffness, strength and specified stiffness are considered as the multiple objective function. The formulation has inequality constraints imposed on the fatigue limit, the natural frequencies, and the manufacturing conditions. Geometric parameters of bellows are the design variables. The recursive quadratic programming algorithm is selected to solve the problem. The results are compared to existing bellows, and the characteristics of bellows is investigated through optimal design process. The optimized shape of bellows is expected to give quite a good guideline to practical design.

• 한국정밀공학회지
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• 제18권12호
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• pp.116-123
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• 2001

An automated injection molding design methodology has been developed to optimize multiple quality attributes, which are usually in conflict with each other, in injection molded parts. For the optimization, commercial CAE simulation tools and optimization techniques are integrated into the methodology. To decal with the multiple objective problem the relative closeness computed in TOPSIS(Technique for Order Preference by Similarity to Ideal Solution) is used as a performance measurement index for optimization multiple part defects. To attain robustness against process variation, Taguchi's quadratic loss function is introduced in the TOPSIS. Also, the modified complex method is used as an optimization tool to optimize objective function. The verification of the developed design methodology was carried out on simulation software with an actual model. Applied to production this methodology will be useful to companies in reducing their product development time and enhancing their product quality.