• Journal of Energy Engineering
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• v.13 no.2
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• pp.128-132
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• 2004

This paper presents a new methodology to get pareto-optimal solution for generation planning. First, we apply dynamic programming, and we can get an optimal economic dispatch considering total quantity of contamination for the specified term. Second, we developed a method which can get pareto-optimal solution. This solution is consisted of a set of optimal generation planning. As a result, decision maker can get pareto-optimal solutions, and can choose a solution. We applied this method to the test system, and showed the usefulness.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.11 s.254
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• pp.1358-1368
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• 2006

This paper proposes a Pareto artificial life algorithm for solving multi-objective optimization problems. The artificial life algorithm for optimization problem with a single objective function is improved to handle Pareto optimization problem through incorporating the new method to estimate the fitness value for a solution and the Pareto list to memorize and to improve the Pareto optimal set. The proposed algorithm was 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 were presented to give the possible solutions to a decision maker or a designer. Furthermore, the relation between linearly combined single-objective optimization problem and Pareto optimization problem has been studied.

• Journal of Distribution Science
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• v.15 no.2
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• pp.15-20
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• 2017

Purpose - This paper aims to suggest a delivery constrained internet shopping optimization problem (DISOP) which must be solved for online recommendation system to provide a customized service considering cost and delivery conditions at the same time. Research design, data, and methodology - To solve a (DISOP), we propose a multi-objective formulation and a solution approach. By using a commercial optimization software (LINDO), a (DISOP) can be solved iteratively and a pareto optimal set can be calculated for real-sized problem. Results - We propose a new research problem which is different with internet shopping optimization problem since our problem considers not only the purchasing cost but also delivery conditions at the same time. Furthermore, we suggest a multi-objective mathematical formulation for our research problem and provide a solution approach to get a pareto optimal set by using numerical example. Conclusions - This paper proposes a multi-objective optimization problem to solve internet shopping optimization problem with delivery constraint and a solution approach to get a pareto optimal set. The results of research will contribute to develop a customized comparison and recommendation system to help more easy and smart online shopping service.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.12
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• pp.1793-1803
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• 2010

The weighting method and goal programming require weighting factors or target values to obtain a Pareto optimal solution. However, it is difficult to define these parameters, and a Pareto solution is not guaranteed when the choice of the parameters is incorrect. Recently, the Mahalanobis Taguchi System (MTS) has been introduced to minimize the Mahalanobis distance (MD). However, the MTS method cannot obtain a Pareto optimal solution. We propose a function called the skewed Mahalanobis distance (SMD) to obtain a Pareto optimal solution while retaining the advantages of the MD. The SMD is a new distance scale that multiplies the skewed value of a design point by the MD. The weighting factors are automatically reflected when the SMD is calculated. The SMD always gives a unique Pareto optimal solution. To verify the efficiency of the SMD, we present two numerical examples and show that the SMD can obtain a unique Pareto optimal solution without any additional information.

• Proceedings of the KIEE Conference
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• 2003.11a
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• pp.233-235
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• 2003

This paper describes a new methodology to get pareto-optimal generation planning for decision-making. To get optimal generation planning consider total quantity of contamination for the specified term, authors employ dynamic programming. And, in the course of dynamic programming, pareto optimal solution can be obtained. So, a most proper solution can be selected by derision-maker. The usefulness is verified by applying It to the test system.

• 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.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.17 no.4
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• pp.67-74
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• 2008

The important dynamic specifications in the aluminum automobile body design are the vibrations and crashworthiness in the views of ride comforts and safety. Thus, considerable effort has been invested into improving the performance of mechanical structures comprised of the interactive multiple sub-structures. Most mechanical structures are complex and are essentially multi-criteria optimization problems with objective functions retained as constraints. Each weight factor can be defined according to the effects and priorities among objective functions, and a feasible Pareto-optimal solution exists for the criteria-defined constraints. In this paper, a multi-criteria design based on the Pareto-optimal sensitivity is applied to the vibration qualities and crushing characteristics of front structure in the automobile body design. The vibration qualities include the idle, wheel unbalance and road shake. The crushing characteristic of front structure is the axial maximum peak load.

• Journal of the Society of Naval Architects of Korea
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• v.46 no.4
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• pp.409-416
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• 2009

The structural design problems are acknowledged to be commonly multi-criteria in nature. The various multi-criteria optimization methods are reviewed and the most efficient and easy-to-use Pareto optimal solution methods are applied to structural optimization of a truss and a beam. The result of the study shows that Pareto optimal solution methods can easily be applied to structural optimization with multiple objectives, and the designer can have a choice from those Pareto optimal solutions to meet an appropriate design environment.

• Journal of Electrical Engineering and Technology
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• v.3 no.2
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• pp.218-223
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• 2008

A new Pareto-optimal design algorithm, requiring least computational work, is proposed for a single phase AC solenoid actuator with multi-design-objectives: maximizing holding force and minimizing eddy current loss simultaneously. In the algorithm, the design space is successively reduced by a suitable factor, as iteration repeats, with the center of pseudo-optimal point. At each iteration, the objective functions are approximated to a simple second-order response surface with the CCD sampling points generated within the reduced design space, and Pareto-optimal solutions are obtained by applying($1+{\lambda}$) evolution strategy with the fitness values of Pareto strength.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.380-383
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• 2003

In this paper, we propose a fuzzy group decision making method for multiple decision maker-multiple objective programming problems to obtain the agreeable solution. In the proposed method, considering the vague nature of human subjective judgement it is assumed that each of multiple decision makers has a fuzzy goal for each of his/her own objective functions. After eliciting the membership functions from the decision makers for their fuzzy goals, total M-Pareto optimal solution concept is defined in membership spaces in order to deal with multiple decision maker-multiple objective programming problems. For generating a candidate of the agreeable solution which is total M-Pareto optimal, the extended weighted minimax problem is formulated and solved for some weighting vector which is specified by the decision makers in their subjective manner, Given the total M-Pareto optimal solution, each of the derision makers must either be satisfied with the current values of the membership functions, or update his/her weighting vector, However, in general, it seems to be very difficult to find the agreeable solution with which all of the decision makers are satisfied perfectly because of the conflicts between their membership functions. In the proposed method, each of the decision makers is requested to estimate the degree of satisfaction for the candidate of the agreeable solution. Using the estimated values or satisfaction of each of the decision makers, the core concept is desnfied, which is a set of undominated candidates. The interactive algorithm is developed to obtain the agreeable solution which satisfies core conditions.