• Transactions of the Korean Society of Mechanical Engineers B
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• v.29 no.10 s.241
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• pp.1163-1171
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• 2005

The shape optimization of an airfoil has been performed for an incompressible viscous flow. In this study, Pareto frontier sets, which are global and non-dominated solutions, can be obtained without various weighting factors by using the multi-objective genetic algorithm An NACA0012 airfoil is considered as a baseline model, and the profile of the airfoil is parameterized and rebuilt with four Bezier curves. Two curves, front leading to maximum thickness, are composed of five control points and the rest, from maximum thickness to tailing edge, are composed of four control points. There are eighteen design variables and two objective functions such as the lift and drag coefficients. A generation is made up of forty-five individuals. After fifteenth evolutions, the Pareto individuals of twenty can be achieved. One Pareto, which is the best of the . reduction of the drag furce, improves its drag to $13\%$ and lift-drag ratio to $2\%$. Another Pareto, however, which is focused on increasing the lift force, can improve its lift force to $61\%$, while sustaining its drag force, compared to those of the baseline model.

• 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 for Railway
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• v.13 no.5
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• pp.535-540
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• 2010

We present an optimization model for how to assign the freight trains to transshipment tracks and allocate the containers to the freight trains in a rail container terminal. We formulate this problem as a multi-criteria integer programming to minimize the makespan of job schedule and simultaneously to maximize the loading throughput, i.e. the number of containers to be disposed per day. We also apply our model to the instance obtained from the real-world data of the Uiwang Inner Container Depot. From the experiments, we can see an improvement of approximately 6% in makespan, which means that our model can contribute to the improvement of the disposal capacity of containers without additional expansion of facilities.

• Journal of the Korean Society of Hazard Mitigation
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• v.10 no.1
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• pp.73-80
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• 2010

The optimal design of water distribution system have started with the least cost design of single objective function using fixed hydraulic variables, eg. fixed water demand and pipe roughness. However, more adequate design is accomplished with considering uncertainties laid on water distribution system such as uncertain future water demands, resulting in successful estimation of real network's behaviors. So, many researchers have suggested a variety of approaches to consider uncertainties in water distribution system using uncertainties quantification methods and the optimal design of multi-objective function is also studied. This paper suggests the new approach of a multi-objective optimization seeking the minimum cost and maximum robustness of the network based on two uncertain variables, nodal demands and pipe roughness uncertainties. Total design procedure consists of two folds: least cost design and final optimal design under uncertainties. The uncertainties of demands and roughness are considered with Latin Hypercube sampling technique with beta probability density functions and multi-objective genetic algorithms (MOGA) is used for the optimization process. The suggested approach is tested in a case study of real network named the New York Tunnels and the applicability of new approach is checked. As the computation time passes, we can check that initial populations, one solution of solutions of multi-objective genetic algorithm, spread to lower right section on the solution space and yield Pareto Optimum solutions building Pareto Front.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.7
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• pp.601-608
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• 2015

The static aeroelastic analysis and optimization of flexible wings are conducted for steady state conditions while both aerodynamic and structural parameters can be used as optimization variables. The system of multidisciplinary design optimization as a robust methodology to couple commercial codes for a static aeroelastic optimization purpose to yield a convenient adaptation to engineering applications is developed. Aspect ratio, taper ratio, sweepback angle are chosen as optimization variables and the skin thickness of the wing. The real-coded adaptive range multi-objective genetic algorithm code, which represents the global multi-objective optimization algorithm, was used to control the optimization process. The support vector regression(SVR) is applied for optimization, in order to reduce the time of computation. For this multi-objective design optimization problem, numerical results show that several useful Pareto optimal designs exist for the flexible wing.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2006.05a
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• pp.95-108
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• 2006

Because of rapid expansion of third party logistics, fierce competition in the transportation industry, and the diversification and globalization of transportation channels, an effective transportation planning by means of multimodal transport is badly needed. Accordingly, this study aims to suggest an optimal transport algorithm for the multimodal transport in the international logistics. Cargoes and stopovers can be changed numerously according to the change of transportation modes, thus being a NP-hard problem. As a solution for this problem, first of all, we have applied a pruning algorithm to simplify it, suggesting a heuristic algorithm for constrained shortest path problem to find out a feasible area with an effective time range and effective cost range, which has been applied to the Label Setting Algorithm, consequently leading to multiple Pareto optimal solutions. Also, in order to test the efficiency of the algorithm for constrained shortest path problem, this paper has applied it to the actual transportation path from Busan port of Korea to Rotterdam port of Netherlands.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.3C
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• pp.314-322
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• 2007

This paper proposes a new optimization algorithm named by GBNSGA(Goal-Pareto Based Non-dominated Sorting Genetic Algorithm) which determines the best configuration for CR(Cognitive Radio) communication systems. Conventionally, in order to select the proper radio configuration, genetic algorithm has been introduced so as to alleviate computational burden along the execution of the cognition cycle proposed by Mitola. This paper proposes a novel optimization algorithm designated as GBNSGA for cognitive engine which can be described as a hybrid algorithm combining well-known Pareto-based NSGA(Non-dominated Sorting Genetic Algorithm) as well as GP(Goal Programming). By conducting computer simulations, it will be verified that the proposed method not only satisfies the user's service requirements in the form of goals. It reveals the fast optimization capability and more various solutions rather than conventional NSGA or weighted-sum approach.

• 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.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.11
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• pp.1106-1110
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• 2010

This paper proposes a method of optimizing a stacking strategy for an automated container terminal using multi-objective evolutionary algorithms (MOEAs). Since the yard productivities of seaside and landside are conflicting objectives to be optimized, it is impossible to maximize them simultaneously. Therefore, we derive a Pareto optimal set instead of a single best solution using an MOEA. Preliminary experiments showed that the population is frequently stuck in local optima because of the difficulty of the given problem depending on the yard occupancy rate. To cope with this problem, we propose another method of simultaneously optimizing two problems with different difficulties so that diverse solutions can be preserved in the population. Experimental results showed the proposed method can derive better stacking policies than the compared method solving a single problem given the same computational costs.

• Journal of KIISE:Software and Applications
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• v.32 no.10
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• pp.963-973
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• 2005

Increasing attention is being recently devoted to various problems inherent in the topological design of networks systems. The topological structure of these networks can be based on service centers, terminals (users), and connection cable. Lately, these network systems are well designed with tiber optic cable, because the requirements from users become increased. But considering the high cost of the fiber optic cable, it is more desirable that the network architecture is composed of a spanning tree. In this paper, we present a GA (Genetic Algorithm) for solving bicriteria network topology design problems of wide-band communication networks connected with fiber optic cable, considering the connection cost, average message delay, and the network reliability We also employ the $Pr\ddot{u}fer$ number (PN) and cluster string in order to represent chromosomes. Finally, we get some experiments in order to certify that the proposed GA is the more effective and efficient method in terms of the computation time as well as the Pareto optimality.