• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.1
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• pp.69-74
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• 2007

Topology optimization of the inner reinforcement for a vehicle's hood has been performed by evolutionary structural optimization(ESO) using a smoothing scheme. The purpose of this study is to obtain optimal topology of the inner reinforcement for a vehicle's hood considering the static stiffness of bending and torsion simultaneously. To do this, the multiobjective optimization technique was implemented. Optimal topologies were obtained by the ESO method. From several combinations of weighting factors, a Pareto-optimal solution was obtained. Also, a smoothing scheme was implemented to suppress the checkerboard pattern in the procedure of topology optimization. It is concluded that ESO method with a smoothing scheme is effectively applied to topology optimization of the inner reinforcement of a vehicle's hood considering the static stiffness of bending and torsion.

• Korean System Dynamics Review
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• v.9 no.1
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• pp.143-154
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• 2008

This study has tried to suggest a new model that can effectively redistribute the tickets in the online ticket resale market, while suggesting a new allocation mechanism based on an agent negotiation. To this end, this study has analyzed and simulated the secondary ticket market through System dynamics. As a result of these simulations, it has been proved that the price stability of ticket resale market leads to an increase in revenue. An agent negotiation helps to stabilize the ticket prices that are usually inclined to rise at auction, benefiting all the participants in the negotiations, consequently showing a Pareto solution.

• Journal of Korea Water Resources Association
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• v.40 no.9
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• pp.687-696
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• 2007

Preference ordering approach is applied to optimize the parameters of Tank model using multi-objective genetic algorithm (MOGA). As more than three multi-objective functions are used in MOGA, too many non-dominated optimal solutions would be obtained thus the stakeholder hardly find the best optimal solution. In order to overcome this shortcomings of MOGA, preference ordering method is employed. The number of multi-objective functions in this study is 4 and a single Pareto-optimal solution, which is 2nd order efficiency and 3 degrees preference ordering, is chosen as the most preferred optimal solution. The comparison results among those from Powell method and SGA (simple genetic algorithm), which are single-objective function optimization, and NSGA-II, multi-objective optimization, show that the result from NSGA-II could be reasonalby accepted since the performance of NSGA-II is not deteriorated even though it is applied to the verification period which is totally different from the calibration period for parameter estimation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.4
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• pp.400-406
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• 2014

In this paper, we propose an approach to minimizing total power consumption by deploying multiple clean-up robots simultaneously in a given area. For this, we propose to use the cooperative game theoretic approaches (i.e., Nash bargaining solution (NBS)) such that the robots can optimally and fairly negotiate the area division based on available resources and characteristics of the area, thereby leading to the minimum total power consumption. We define a utility function that includes power consumptions for characteristics of areas and the robots can agree on a utility pair based on the NBS. Simulation results show that the proposed approach can reduce the total average power consumption by 15-30% compared to a random area division approach.

• Industrial Engineering and Management Systems
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• v.10 no.2
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• pp.134-139
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• 2011

The problem of scheduling in permutation flowshops has been extensively investigated by many researchers. Recently, attempts are being made to consider more than one objective simultaneously and develop algorithms to obtain a set of Pareto-optimal solutions. Varadharajan et al. (2005) presented a multi-objective simulated-annealing algorithm (MOSA) for the problem of permutation-flowshop scheduling with the objectives of minimizing the makespan and the total flowtime of jobs. The MOSA uses two initial sequences obtained using heuristics, and seeks to obtain non-dominated solutions through the implementation of a probability function, which probabilistically selects the objective of minimizing either the makespan or the total flowtime of jobs. In this paper, the same problem of heuristically developing non-dominated sequences is considered. We propose an effective heuristics based on simulated annealing (SA), in which the weighted sum of the makespan and the total flowtime is used. The essences of the heuristics are in selecting the initial sequence, setting the weight and generating a solution in the search process. Using a benchmark problem provided by Taillard (1993), which was used in the MOSA, these conditions are extracted in a large-scale experiment. The non-dominated sets obtained from the existing algorithms and the proposed heuristics are compared. It was found that the proposed heuristics drastically improved the performance of finding the non-dominated frontier.

• International Journal of Automotive Technology
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• v.8 no.3
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• pp.337-342
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• 2007

A multi-objective optimization technique was implemented to obtain optimal topologies of the inner reinforcement for a vehicle's hood simultaneously considering the static stiffness of bending and torsion and natural frequency. In addition, a smoothing scheme was used to suppress the checkerboard patterns in the ESO method. Two models with different curvature were chosen in order to investigate the effect of curvature on the static stiffness and natural frequency of the inner reinforcement. A scale factor was employed to properly reflect the effect of each objective function. From several combinations of weighting factors, a Pareto-optimal topology solution was obtained. As the weighting factor for the elastic strain efficiency went from 1 to 0, the optimal topologies transmitted from the optimal topology of a static stiffness problem to that of a natural frequency problem. It was also found that the higher curvature model had a larger static stiffness and natural frequency than the lower curvature model. From the results, it is concluded that the ESO method with a smoothing scheme was effectively applied to topology optimization of the inner reinforcement of a vehicle's hood.

• Journal of Computational Design and Engineering
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• v.1 no.4
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• pp.256-265
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• 2014

Energy efficiency is an essential consideration in sustainable manufacturing. This study presents the car fender-based injection molding process optimization that aims to resolve the trade-off between energy consumption and product quality at the same time in which process parameters are optimized variables. The process is specially optimized by applying response surface methodology and using non-dominated sorting genetic algorithm II (NSGA II) in order to resolve multi-object optimization problems. To reduce computational cost and time in the problem-solving procedure, the combination of CAE-integration tools is employed. Based on the Pareto diagram, an appropriate solution is derived out to obtain optimal parameters. The optimization results show that the proposed approach can help effectively engineers in identifying optimal process parameters and achieving competitive advantages of energy consumption and product quality. In addition, the engineering analysis that can be employed to conduct holistic optimization of the injection molding process in order to increase energy efficiency and product quality was also mentioned in this paper.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.14 no.4
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• pp.28-33
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• 2015

In this study, the optimal design for the support and the binding device for the protection of crops for the maximum allowable stress of the shape necessary to minimize volume has been proposed. Optimization of the support and the binding device for the crops should be designed to support businesses in terms of profit, in part to reduce the material, and to profit from the ease and speed of working that part of the farmers. We used CATIA for the mechanical design and the ANSYS program for the structural analysis. Additionally, the optimization was performed by PIAnO with seven design variables for the binding device and three parameters for the support. The weight method using a multi-objective function was also determined by the Pareto optimal solution. The volume of the binding device in the optimum design result was found to be reduced by 16%, from $2.278e-005m^3to1.912e-005m^3$. From the result, we confirmed the effectiveness of the design method proposed as a multi-objective function optimization problem.

• The Journal of Society for e-Business Studies
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• v.14 no.4
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• pp.133-148
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• 2009

This study has tried to suggest a new model that can effectively redistribute the tickets in the online ticket resale market, while suggesting a new allocation mechanism based on an agent negotiation. To this end, this study has analyzed an auction in the online ticket resale market through Game theory. As a result of new agent mechanism, it has been proved that the price stability of ticket resale market leads to an increase. An agent negotiation helps to stabilize the ticket prices that are usually inclined to rise at auction, benefiting all the participants in the negotiations, consequently showing a Pareto solution. Especially, a framework for a negotiation process is suggested and domain and processes ontology are designed interrelatedly. With this modeling, a possibility of Ontology based agent negotiation is suggested.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.21 no.6
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• pp.954-960
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• 2012

Nowadays, rapidly changing and unstable global economic environments request a lot of roles to engineers. In this situation, product should be designed to make more profit by cost down and to satisfy distinguished performance comparing to other competitive ones. In this research, the optimization design of the industrial robot casting will be done. The weight and deflection have to be reduced as objective functions and stress has to be constrained under some constant value. To reduce time cost, CCD (Central Composite Design) will be used to make experimental design. And RSM (Response Surface Methodology) will be taken to make regression model for objective functions and constraint function. Finally, optimization will be done with Genetic Algorithm. In this problem, the objective functions are multiple, so NSGA-II which is brilliant and efficient for such a problem will be used. For the solution quality check, the diversity between Pareto solutions will be also checked.